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US labour unions fight to contain AI disruption - RTE
|
US labour unions fight to contain AI disruption
|
https://www.rte.ie
|
[] |
As artificial intelligence threatens to upend entire sectors of the economy, American labour unions are scrambling to protect workers, ...
|
As artificial intelligence threatens to upend entire sectors of the economy, American labour unions are scrambling to protect workers, demand corporate transparency, and rally political support - an uphill battle in a rapidly changing world.
"As laborers, the ability to withhold our labour is one of our only tools to improve our lives," explained Aaron Novik, a key organizer with Amazon's ALU union.
"What happens when that disappears [to AI]? It's a real existential issue," he added.
Automation has already transformed most industries since the 1960s, typically reducing workforce numbers in the process.
But the emergence of advanced 'physical AI' promises a new generation of intelligent robots that won't be limited to repetitive tasks - potentially displacing far more blue-collar workers than ever before.
The threat extends beyond manufacturing.
The CEO of Anthropic, which created Claude as a competitor to ChatGPT, warned last week that generative AI could eliminate half of all low-skilled white-collar jobs, potentially driving unemployment rates up to 10-20%.
"The potential displacement of workers and elimination of jobs is a significant concern not just for our members, but for the public in general," said Peter Finn of the International Brotherhood of Teamsters, America's largest union.
The Teamsters have focused their efforts on passing legislation limiting the spread of automation, but face significant political obstacles.
California's governor has twice vetoed bills that would ban autonomous trucks from public roads, despite intense lobbying from the state's hundreds of thousands of union members.
Colorado's governor followed suit last week, and similar battles are playing out in Indiana, Maryland, and other states.
At the federal level, the landscape shifted dramatically with the change in the White House.
Under former president Joe Biden, the Department of Labor issued guidelines encouraging companies to be transparent about AI use, involve workers in strategic decisions, and support employees whose jobs face elimination.
But US President Donald Trump canceled the protections within hours of taking office in January.
"Now it's clear. They want to fully open up AI without the safeguards that are necessary to ensure workers' rights and protections at work," said HeeWon Brindle-Khym of the Retail, Wholesale and Department Store Union (RWDSU), which represents workers in the retail sector.
Meanwhile, companies are racing to implement AI technologies, often with poor results.
"By fear of missing out on innovations, there's been a real push (to release AI products)," observed Dan Reynolds of the Communications Workers of America (CWA).
The CWA has taken a proactive approach, publishing a comprehensive guide for members that urges negotiators to include AI provisions in all collective bargaining agreements.
The union is also developing educational toolkits to help workers understand and negotiate around AI implementation.
A handful of unions have successfully negotiated AI protections into their contracts.
Notable examples include agreements with media company Ziff Davis (which owns Mashable) and video game publisher ZeniMax Studios, a Microsoft subsidiary.
The most significant victories belong to two powerful unions: the International Longshoremen's Association, representing dock workers, secured a moratorium on full automation of certain port operations, while the Screen Actors Guild (SAG-AFTRA) won guarantees that actors must be consulted and compensated whenever their AI likeness is created.
These successes remain exceptional, however.
The American labour movement, as a whole, lacks the bargaining power enjoyed by those highly strategic or publicly visible sectors, said Brindle-Khym.
"Smaller contract-by-contract improvements are a long, slow process," she added.
Despite frequent accusations by corporate interests, the unions say their goal is not to halt technological progress entirely.
"Workers are usually not seeking to stop the march of technology," noted Virginia Doellgast, a Cornell University professor specializing in labour relations.
"They just want to have some control."
As AI continues its rapid advance, the question remains whether unions can adapt quickly enough to protect workers in an economy increasingly dominated by artificial intelligence.
| 2025-06-04T00:00:00 |
2025/06/04
|
https://www.rte.ie/news/business/2025/0604/1516614-us-union-ai/
|
[
{
"date": "2025/06/04",
"position": 96,
"query": "artificial intelligence labor union"
}
] |
US labor unions fight to contain AI disruption - France 24
|
US labor unions fight to contain AI disruption
|
https://www.france24.com
|
[] |
As artificial intelligence threatens to upend entire sectors of the economy, American labor unions are scrambling to protect workers, ...
|
"As laborers, the ability to withhold our labor is one of our only tools to improve our lives," explained Aaron Novik, a key organizer with Amazon's ALU union.
"What happens when that disappears (to AI)? It's a real existential issue," he added.
Automation has already transformed most industries since the 1960s, typically reducing workforce numbers in the process.
But the emergence of advanced "physical AI" promises a new generation of intelligent robots that won't be limited to repetitive tasks -- potentially displacing far more blue-collar workers than ever before.
The threat extends beyond manufacturing.
The CEO of Anthropic, which created Claude as a competitor to ChatGPT, warned last week that generative AI could eliminate half of all low-skilled white-collar jobs, potentially driving unemployment rates up to 10-20 percent.
"The potential displacement of workers and elimination of jobs is a significant concern not just for our members, but for the public in general," said Peter Finn of the International Brotherhood of Teamsters, America's largest union.
Vetoes
The Teamsters union is backing legislation limiting the spread of automation, despite which governors in California and Colorado have vetoed bills that would ban autonomous trucks from public roads © Robyn Beck / AFP/File
The Teamsters have focused their efforts on passing legislation limiting the spread of automation, but face significant political obstacles.
California's governor has twice vetoed bills that would ban autonomous trucks from public roads, despite intense lobbying from the state's hundreds of thousands of union members.
Colorado's governor followed suit last week, and similar battles are playing out in Indiana, Maryland, and other states.
At the federal level, the landscape shifted dramatically with the change in the White House.
Under former president Joe Biden, the Department of Labor issued guidelines encouraging companies to be transparent about AI use, involve workers in strategic decisions, and support employees whose jobs face elimination.
But US President Donald Trump canceled the protections within hours of taking office in January.
"Now it's clear. They want to fully open up AI without the safeguards that are necessary to ensure workers' rights and protections at work," said HeeWon Brindle-Khym of the Retail, Wholesale and Department Store Union (RWDSU), which represents workers in the retail sector.
Rush to AI
Meanwhile, companies are racing to implement AI technologies, often with poor results.
"By fear of missing out on innovations, there's been a real push (to release AI products)," observed Dan Reynolds of the Communications Workers of America (CWA).
The CWA has taken a proactive approach, publishing a comprehensive guide for members that urges negotiators to include AI provisions in all collective bargaining agreements.
The union is also developing educational toolkits to help workers understand and negotiate around AI implementation.
A handful of unions have successfully negotiated AI protections into their contracts.
Notable examples include agreements with media company Ziff Davis (which owns Mashable) and video game publisher ZeniMax Studios, a Microsoft subsidiary.
The most significant victories belong to two powerful unions: the International Longshoremen's Association, representing dock workers, secured a moratorium on full automation of certain port operations, while the Screen Actors Guild (SAG-AFTRA) won guarantees that actors must be consulted and compensated whenever their AI likeness is created.
These successes remain exceptional, however.
The American labor movement, as a whole, lacks the bargaining power enjoyed by those highly strategic or publicly visible sectors, said Brindle-Khym.
"Smaller contract-by-contract improvements are a long, slow process," she added.
Despite frequent accusations by corporate interests, the unions' goal isn't to halt technological progress entirely.
"Workers are usually not seeking to stop the march of technology," noted Virginia Doellgast, a Cornell University professor specializing in labor relations.
"They just want to have some control."
As AI continues its rapid advance, the question remains whether unions can adapt quickly enough to protect workers in an economy increasingly dominated by artificial intelligence.
© 2025 AFP
| 2025-06-04T00:00:00 |
2025/06/04
|
https://www.france24.com/en/live-news/20250604-us-labor-unions-fight-to-contain-ai-disruption
|
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"date": "2025/06/04",
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Putting AI to Work in Schools Is Difficult. A New Toolkit ...
|
Putting AI to Work in Schools Is Difficult. A New Toolkit Outlines How to Do It
|
https://www.edweek.org
|
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Common Sense Media has released an AI toolkit for school districts to help them figure how how to use this new technology.
|
Some districts are ahead of the curve in putting generative artificial intelligence to work in instruction and other school operations . The majority of districts, however, have either just started conversations or are still figuring out where to begin.
While a majority of states and a handful of education organizations have provided AI guidance for schools , many district leaders still need “practical” support for “pain points related to AI implementation,” said Robbie Torney, the senior director of AI programs for Common Sense Media.
For instance, a common challenge Torney has heard from district leaders is how to have conversations with educators or parents who are skeptical about AI or worried about what AI use in schools might look like.
That’s why Common Sense Media has released an AI toolkit for school districts to help them figure how how to use this new technology.
In an interview with Education Week, Torney discussed the challenges districts face when trying to put AI to use in schools.
This interview has been edited for length and clarity.
What’s a common challenge districts are facing?
One of the questions we get a lot is: Where do we start? That can be a really daunting place. Part of how we’ve organized the tool is we have a “getting started” guide and a readiness assessment that are bundled together that are meant to help districts think through all of the different facets of what getting started means in a K-12 system. That’s everything from thinking about systems and technical infrastructure to thinking about some of those enabling conditions that are on the ground, in terms of AI literacy for different stakeholders, to engaging in the stakeholder conversations to thinking about this from a policy or a compliance framework.
What’s different about using AI compared with other educational technologies?
Implementation in K-12 is hard . You’re adopting a new curriculum. How do you get stakeholder input and make sure that you’re thinking through all of the requirements related to that curriculum, thinking about how it fits into your schedule, planning for how you’re going to train your teachers, thinking about how you’re going to measure whether or not the curriculum is actually being implemented, if it’s having the effects that you want it to? These are the types of systems change that skilled and seasoned school administrators are used to navigating.
There’s a lot about AI that feels very familiar when you’re thinking about your approach to that. There’s also some differences, of course, which is that district administrators themselves may be much more familiar with different types of curriculum and have much more experience or content knowledge [about that] than they do with AI. AI literacy is a huge and a really important part of the solution. But it’s not the only part, and this toolkit is meant to point toward some of these other parts that need to be in place as districts are thinking about implementation.
What would you say is the most important step schools should take?
The first domain that we encourage people to start on if they are novices or are still developing their understanding of AI is about leadership and vision. Some of the questions associated with that are: Is there a shared districtwide understanding of AI’s potential , opportunities, and risks? Is there a mission statement for AI use that’s been developed or endorsed by leadership?
AI is not something to implement for the sake of implementation. AI is a tool, and districts have to have a clear vision for what that tool can do. That feeds into some of these other pieces related to policy and governance, infrastructure and systems readiness, staff capacity and professional learning, community and stakeholder engagement. But all of that has to be rooted in developing a leadership orientation and a vision for what the technology can be used for, and some knowledge of the technology is necessary for that.
How should districts help teachers learn more about AI’s role in education?
Part of the work there is giving educators very concrete insight into what these technologies can do for them , and that starts with generating examples, either from other districts or in your own district, of how this can actually ... demonstrate some of those proof points , positive wins, and exemplars that can help get staff excited about something that they may not necessarily understand or feel like they have the time for.
How should districts engage families in this process?
From Common Sense Media’s research, when we last polled on this as part of our “Dawn of AI ” report, 83% of parents reported that schools had not communicated with them about AI policies. One of the comments that [we’ve heard from districts] was something to the effect of “OK, we feel like we’ve communicated information, but have parents really heard it or do parents feel supported by it?”
Administrators have reached out to us to talk about how they can bring training and apply some of these tools within a family engagement perspective. The toolkit does contain some specific resources for thinking about how to engage parents, how to build basic parent literacy, how to help parents understand things like the impact that AI might have on the economy in the future, or the jobs in the future, or college readiness. This is a really critical stakeholder group, and it’s really down to districts to be able to help support parents with some of that work. Parent partnership is going to be critical to the success or failure of an initiative like this.
| 2025-06-04T00:00:00 |
2025/06/04
|
https://www.edweek.org/technology/putting-ai-to-work-in-schools-is-difficult-a-new-toolkit-outlines-how-to-do-it/2025/06
|
[
{
"date": "2025/06/04",
"position": 39,
"query": "AI education"
}
] |
29 Examples of AI in Education [2025] - Digital Adoption
|
29 Examples of AI in education [2025]
|
https://www.digital-adoption.com
|
[
"Nieem Sekiri",
"Digital Adoption Team"
] |
This article will explore twenty-nine examples of AI in education, dividing each entry into three categories: Student-Focused AI, Teacher-Focused AI, and ...
|
Almost every global sector has entered the AI adoption race, with the upper limits of artificial intelligence’s (AI) potential still unknown.
Intelligence systems siphon huge data sets to learn, understand, and perform complex actions independently. Key decisions, pattern detection, and data analysis, which once required a human touch, can now be augmented with the help of AI.
AI in education is no exception, as the technology finds numerous applications for enhancing learning and teaching experiences.
This article will explore twenty-nine examples of AI in education, dividing each entry into three categories: Student-Focused AI, Teacher-Focused AI, and Institution-Focused AI.
AI in education examples at a glance:
AI Technology Function Category Adaptive learning AI Adjusts lessons in real-time based on a student’s performance. Student-focused AI Intelligent tutoring Gives step-by-step help like a private tutor. Student-focused AI Assistive learning technologies Helps students with disabilities learn using tools like speech-to-text. Student-focused AI Smart content and lesson creation Builds quizzes, summaries, or lessons from textbooks or topics. Student-focused AI Student engagement and behavior tracking Monitors attention, activity, or drop-off using video or platform data. Student-focused AI Skill gap detection and intervention Identifies what a student doesn’t understand and suggests extra practice. Student-focused AI Learning disability detection Flag patterns that suggest dyslexia or other learning issues. Student-focused AI Gamification and edutainment Adds game-like features or stories to keep students interested. Student-focused AI 3D and virtual learning spaces Creates online worlds where students can explore subjects interactively. Student-focused AI AI digital learning modules Offers small lessons that adjust based on the student’s pace. Student-focused AI Virtual campus life and extracurriculars Simulates clubs, events, or activities through online avatars or portals. Student-focused AI Interdisciplinary learning Links topics such as science and art into a connected lesson. Student-focused AI Real-world scenario simulation Let’s students practice real-life situations in a controlled virtual space. Student-focused AI Social awareness education platforms Uses stories or cases to teach ethics, empathy, or cultural topics. Student-focused AI Virtual field trips Let’s students explore museums or landmarks through live or 3D video. Student-focused AI Test prep platforms Customizes practice tests and gives instant feedback on answers. Student-focused AI Automated grading and assessment Score essays or quizzes and explain mistakes. Teacher-focused AI Conversational AI (chatbots & virtual assistants) Answers staff or student questions 24/7 about classes or school tasks. Teacher-focused AI Parent-teacher communication Sends alerts or updates to parents based on student progress. Teacher-focused AI Learning analytics and data insights Shows teachers’ patterns in student performance or activity. Teacher-focused AI Plagiarism detection Flags copied text in essays or homework using pattern checks. Teacher-focused AI Academic research Helps sort papers, find topics, or summarize long texts. Teacher-focused AI Curriculum intelligence and optimization Recommends what to teach or skip based on student needs and performance. Institution-focused AI LMS augmentation Adds smart features to platforms, such as auto-feedback or content tagging. Institution-focused AI Proctoring solutions Watches test-takers for signs of cheating using webcams or keystroke data. Institution-focused AI AI-led administrative actions Handles repetitive administrative tasks, such as scheduling or form processing. Institution-focused AI Campus security and surveillance Utilizes cameras or sensors to identify unusual activity or potential safety issues. Institution-focused AI School transport optimization Plans the most efficient bus routes based on pickup data and traffic. Institution-focused AI
Student-focused AI
Let’s begin with AI designed to enhance and support student capabilities.
This category showcases AI tools and platforms that facilitate innovative learning methods, adapt to students’ needs in real-time, and reimagine how they engage with learning materials.
Adaptive learning AI
As the name suggests, adaptive AI learning platforms hone in on methods that individualize student learning. In schools where resources are spread thin, AI can step in to augment teaching. Machine learning models (ML) analyze past tests, attendance records, and teacher notes (verified for bias) to identify student needs. This way, each student gets a path tailored to their pace.
Intelligent tutoring
Also designed to support adaptive learning, AI-led intelligent tutoring systems supplement both student and teacher capabilities. They refine how lessons are delivered using stored data on student pace, comprehension, and pain points. Difficult concepts are broken down into stages, while natural language processing (NLP) assistants deliver feedback in accessible ways, mirroring the role of real teachers without undercutting their authority.
Assistive learning technologies
AI-assistive learning tools support special education needs, including students with Dyslexia, Autism, ADHD, and Down syndrome. Teaching demands bespoke lesson plans, alternative learning habits, and ethical care. AI can build IEPs and adjust delivery, pace, and tools. AI can also transcribe speech with impairments and use person-first language without bias in interactions, provided it is properly trained.
Smart content and lesson creation
Responsibility for lesson planning, research, and sourcing no longer sits solely with teachers. AI can read, understand, and repurpose global data sets into new strategies. Smart content adjusts to where students are in the subject, their reading levels, and other contextual factors, easing the prep load for teachers without compromising on quality.
Student engagement and behavior tracking
When educators monitor engagement and behaviour, time is lost delivering quality work. AI can track shifting student metrics and KPIs in real-time. Instead of teachers running manual checks on each student, AI logs behavioral patterns, flags absences, links detention rates, and helps uncover the causes behind class dismissals for proactive teacher responses.
Skill gap detection and intervention
Identifying hidden skills gaps in classrooms with 30 or more students is challenging, let alone crafting individualized solutions for each student. AI processes data, such as test averages and learning roadblocks, to quickly design targeted plans that close gaps. It can also map student trajectories and introduce development strategies early, identifying future skills before they’re needed.
Learning disability detection
AI can detect patterns in data that an untrained human may miss, including students with undiagnosed learning disabilities. It can assess past performance, test results, and handwritten notes. Balancing different data points, AI can estimate the likelihood of a disability and notify staff. Adaptive learning plans then realign expectations to student capability.
Gamification and edutainment
Teachers no longer need to rely on traditional, text-heavy learning methods. AI reimagines gamification by bringing fun, interactive game mechanics into lesson creation. Classes can be customized to fit each student, reflect school standards, and evolve in real-time, with questions, answers, and difficulty shifting based on learning styles and student interaction each time.
3D and virtual learning spaces
AI can turn education into a 3D experience using extended reality (XR). With virtual reality (VR) headsets, students can explore new topics in lifelike spaces. These tools are still growing, but they’re already helping students learn in new ways. AI assistants support teachers by providing interactive lessons and videos, making it easier for students to stay focused and grasp key concepts.
AI digital learning modules
AI learning modules are small, focused lessons that adapt to each student’s learning style. Like adaptive learning, they follow your pace, find what’s hard for you, and avoid repeating what you already know. AI uses pictures, charts, and clear language to explain ideas in a way that matches your learning style.
Virtual campus life and extracurriculars
AI recreates virtual campus life and extracurriculars, allowing students to join clubs, societies, and events online. It tracks attendance, preferences, and engagement to tailor suggestions, helping students stay connected and active beyond the classroom in ways that reflect their interests and habits.
Interdisciplinary learning
AI helps students connect different subjects, such as science, literature, and math. It illustrates how ideas connect, guiding the students to see the potential value. AI also keeps track of progress and challenges, building lessons around each student’s needs. Hard topics are broken down into smaller steps to make learning easier and more manageable.
Real-world scenario simulation
Some lessons are easier to understand when learned through doing, rather than just reading. With virtual and augmented reality, students can immerse themselves in real-life situations without leaving the classroom. AI makes these experiences feel real and adjusts them to each student’s choices. This helps improve problem-solving and decision-making in a safe and hands-on manner.
Social awareness education platforms
Social awareness education platforms use AI to help all students learn about emotions, respect, and teamwork. They give personalized lessons and feedback that build empathy and communication skills. These tools create kinder, more connected classrooms where everyone feels valued and included.
Virtual field trips
AI-powered virtual field trips bring distant places to students in real-time and with incredible detail. They create hands-on learning experiences that inspire exploration and connect learners with environments they might never have visited otherwise.
Test prep platforms
AI adapts study plans by analyzing your learning patterns and focusing on areas needing improvement. It delivers practice questions and clear feedback, making exam preparation more efficient and effective. These personalized methods help students gain confidence and higher scores through focused, smart studying.
Teacher-focused AI
This category features tools that support teachers in managing classrooms and improving instruction.
These systems help save time, provide insights on student progress, and offer new ways to connect with learners. The ultimate goal is to make teaching more efficient and impactful, and to provide educators with the tools to support student growth.
Automated grading and assessment
Grading tests and homework can be monotonous and time-consuming. Automated systems handle this quickly and fairly, giving instant and continuous feedback to students. This frees teachers to spend more time helping students understand challenging topics and develop their lifelong skills.
Conversational AI (chatbots & virtual assistants)
AI assistants and AI chatbot platforms interact with students and answer questions at any time, day or night. They help explain lessons and remind students about tasks. This support makes learning smoother, allowing teachers to focus more on teaching rather than constantly answering repetitive questions.
Parent-teacher communication
AI productivity tools send parents quick updates about their child’s schoolwork and progress. They make it simple for parents and teachers to stay connected and share information. When informed, families can better support their child’s learning journey.
Learning analytics and data insights
Data from students’ learning habits shows where they struggle or excel. Teachers analyze this information from learning analytics platforms to adjust lessons and give extra help when needed. Educators can utilize these insights to develop more effective learning plans tailored to each student’s strengths and weaknesses.
Plagiarism detection
Checking for copied work is important in education and is a pillar of good practice. AI tools scan assignments to spot plagiarism, helping students understand the value of original thinking. This encourages honest work and helps maintain fairness across all students in the classroom and at home.
Academic research
Teachers rely on heavy research to improve their lessons, lectures, and study materials. AI can quickly gather and summarize recent studies, saving time and effort. Staying informed about new teaching methods and discoveries enables educators to introduce fresh ideas into the classroom, leading to improved student outcomes.
Institution-focused AI
This category focuses on tools that enhance how schools and universities manage daily tasks, ensure safety, and utilize resources effectively.
These systems support institutions in creating a better environment for staff and students while keeping up with evolving education demands.
Curriculum intelligence and optimization
Schools now use curriculum intelligence technology to study how students learn and improve lesson plans and study. This helps teachers adjust content to match students’ needs, making lessons more understandable and relevant. Smarter curricula lead to better student engagement and higher success rates across subjects.
LMS augmentation
Learning management systems (LMS) become smarter by tracking how each student progresses. They suggest resources and organize lessons to fit different learning speeds. Teachers save time while students receive personalized support, making studying easier and more effective for everyone involved.
Proctoring solutions
Remote exams are monitored using advanced tools that watch for suspicious behavior. These systems protect test fairness by identifying cheating without requiring physical oversight. Students can take tests from anywhere, confident that the process is secure and trustworthy.
AI-led administrative actions
Many routine tasks, like scheduling and attendance, are handled automatically by smart office technology. This reduces mistakes and lets staff focus on important work supporting students. Schools benefit from smoother daily operations and less paperwork.
Campus security and surveillance
AI security systems continuously monitor school areas, quickly identifying unusual events. Alerts are sent instantly to staff, allowing them to respond more quickly to potential threats. This technology helps keep everyone safer on campus during school hours and alleviates the pressures of having on-site security.
School transport optimization
Bus routes are planned by analyzing traffic patterns and student locations to ensure efficiency. The goal is to find the fastest and safest paths so that students arrive on time. Optimized transport is a new initiative that saves money, reduces delays, and improves daily school commutes.
AI as a catalyst for transforming education
The education sector has long been a leader in academic research, built on a foundation of scientific discovery and digital innovation.
AI must be integrated thoughtfully and fairly across all areas of education for it to flourish. This integration should prioritize equality, worth, and continuous evaluation through digital dexterity frameworks for education that monitor progress.
When institutions invest time, resources, and academic expertise into AI, the potential to transform learning, teaching, and administration becomes limitless.
Embracing AI responsibly will open doors to innovative teaching methods, personalized experiences, and more efficient academic systems, driving education forward in ways previously unimaginable.
The future of education depends on merging traditional academic study with the prowess of AI technology, ensuring it supports and enhances every aspect of the sector.
5/5 - (1 vote)
| 2025-06-05T00:00:00 |
2025/06/05
|
https://www.digital-adoption.com/ai-in-education-examples/
|
[
{
"date": "2025/06/04",
"position": 50,
"query": "AI education"
}
] |
The Future of STEM Classrooms: How AI Is Revolutionizing ...
|
The Future of STEM Classrooms: How AI Is Revolutionizing Teaching and Learning
|
https://insightintoacademia.com
|
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Researchers and educators are leveraging the power of AI to enhance teaching, learning, and assessment in science education.
|
As artificial intelligence (AI) continues to reshape industries across the globe, higher education finds itself at a pivotal crossroads—especially in the fields of science, technology, engineering, and mathematics (STEM). One of the leaders driving this transformation is the AI4STEM Education Center at the University of Georgia (UGA), where researchers and educators are leveraging the power of AI to enhance teaching, learning, and assessment in science education.
At the heart of this effort is a bold vision: to develop tools that can help teachers engage students in authentic scientific practices while reducing their workload. “Teachers are under pressure to align their instruction and assessment with next-generation science standards,” says Xiaoming Zhai, PhD, associate professor in the Department of Mathematics, Science, and Social Studies Education and affiliated assistant professor at UGA’s Institute for Artificial Intelligence. “But if they don’t have time-saving tools—like automated feedback or AI-supported scoring—they’re less likely to implement high-quality assessments, and students lose out.”
From Grading to Guidance: AI as Teaching Assistant
Much of Zhai’s early work at the center focused on automating the assessment process. He and his team built machine learning systems capable of evaluating students’ scientific performance—such as written explanations or data modeling—with a level of nuance that previously required expert human scorers. These tools allowed teachers to receive immediate, actionable feedback about how students were engaging with core scientific practices.
But automation was only the beginning.
Today, Zhai is pushing the boundaries with the development of “GenAgents”—AI-powered multi-agent systems designed to interact directly with students and educators in real time. These agents are being trained to support students in complex scientific tasks such as argumentation, data analysis, and explanation-building.
Imagine two students debating how to interpret a set of experimental results. One believes a chemical reaction caused a change in temperature; the other attributes the shift to a measurement error. A GenAgent could step in—not just to correct them, but to play the role of moderator, challenger, or facilitator, depending on what’s needed.
“For high-performing students, the agent might push them to defend their reasoning more deeply,” Zhai says. “For those struggling to stay on task, it might help redirect the conversation back to the scientific content.”
Addressing Equity and Bias
As powerful as AI can be, its integration into education raises critical questions about fairness and transparency. Zhai’s team is proactively studying these concerns, especially in the realm of assessment.
“Bias is something we take seriously,” he says. “We want to ensure AI-generated scores are as fair—if not fairer—than human scoring.” To that end, his team compares AI scores with those produced by panels of trained human experts, using these “gold standard” benchmarks to evaluate and refine their models.
They also explore how AI systems perform across diverse student populations, including gender and English language learners. One line of research, for instance, examines whether AI scoring amplifies or reduces disparities commonly seen in human grading.
“We’re not just looking at whether one group scores higher,” Zhai explains. “We’re analyzing whether AI is exacerbating existing differences or helping to close those gaps.”
Building the Next Generation of Interdisciplinary Experts
Central to UGA’s vision is its commitment to interdisciplinary collaboration. The AI4STEM Education Center brings together experts in STEM education, learning sciences, computer science, and AI to work toward a common goal: building tools that are not only technically advanced but also pedagogically sound.
A typical project team might include faculty developing science content, engineers designing learning platforms, and AI specialists creating the underlying architecture of the GenAgents. One current initiative includes more than 40 contributors, each playing a vital role in research, design, development, and testing.
But Zhai’s ambitions go even further.
“We’re not just doing research,” he says. “We’re training the next generation of scholars—doctoral and graduate students who will leave with expertise in both AI and education. That’s just as exciting to me as the technologies we’re building.”
Reaching Underrepresented Learners
Another major initiative at the center is the siSTEMas project, funded by the National Institutes of Health. This program uses game-based learning to engage middle school students—particularly those from underrepresented backgrounds—in STEM.
What makes this project unique is its multilingual approach. The team is developing both English and Spanish versions of their science learning games to ensure accessibility for bilingual students. “We often see performance differences tied more to language proficiency than science understanding,” Zhai says. “By reducing language barriers, we aim to make high-quality learning environments available to all.”
Barriers to Broader Adoption
Despite promising advances, several challenges remain in scaling AI integration in STEM classrooms.
First, public perception of AI, especially concerns amplified by media coverage, can influence how willing teachers and parents are to adopt these technologies. “Many people hear more about the risks of AI than the benefits,” Zhai says. “That creates hesitation.”
Second, there’s a pressing need for professional development. Teachers must not only learn how to use AI tools but also develop the judgment to integrate them ethically and effectively. Zhai’s team is currently building a framework to support this process, helping educators evolve from AI observers to confident co-creators of AI-enhanced lessons.
Finally, interdisciplinary collaboration, while essential, is inherently complex. It requires not only administrative support and infrastructure but also a cultural shift in how academic disciplines value each other’s contributions.
The Road Ahead
As the AI4STEM Education Center continues its work, its mission remains grounded in a deeply human goal: empowering educators and students alike to thrive in an increasingly complex world.
“I’m a teacher at heart,” Zhai says. “And to me, preparing the next generation—not just with content knowledge, but with the tools and confidence to think critically and creatively—that’s the most important thing we can do.”
With projects like GenAgent, siSTEMas, and AI-powered assessments on the horizon, the future of STEM education looks more interactive, inclusive and intelligent than ever before.
| 2025-06-04T00:00:00 |
2025/06/04
|
https://insightintoacademia.com/ai-in-the-classroom/
|
[
{
"date": "2025/06/04",
"position": 62,
"query": "AI education"
}
] |
Beyond the Tool: Why AI in Education Is About the Learner ...
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Beyond the Tool: Why AI in Education Is About the Learner, Not the Technology
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https://ecis.org
|
[] |
AI in education is not about what technology you adopt—it's about how your students learn to use it. The focus must shift from learning to use AI to using AI ...
|
Posted on: 4 June 2025
Stephanie Holt
Director of Teaching and Learning, DSB International School, India
Co-author of AI for Learning: 101 Assessments K-12 Unlocking Mastery of AI (Belgravia Press, 2024)
Alexander Harris
Deputy Head Academic, Sanford International School, Ethiopia
In the buzz and bustle of AI in education, it’s tempting to get caught up in the race to acquire the flashiest edtech. Some schools proudly announce the adoption of AI platforms, the integration of chatbot tutors, or the piloting of algorithmic grading tools, while others bury their heads in the sand and hop ethat it will all pass them by. But as we stand on the cusp of a seismic shift in how students engage with knowledge, a more important truth emerges: AI in education is not about what technology you adopt—it’s about how your students learn to use it.
The focus must shift from learning to use AI to using AI for learning. That distinction isn’t just semantic—it is pedagogical, ethical, and profoundly transformational.
From Tool to Tutor: Repositioning AI in the Learning Process
At its best, AI should function like a compass, not a crutch. When students use generative AI responsibly—whether for drafting essays, analysing historical trends, or solving mathematical problems—they’re not outsourcing thinking. They’re enhancing it.
The key lies in guided, purposeful use. Research cited in AI for Learning: 101 Assessment Strategies for K-12 Schools Unlocking Mastery of AI reveals that students given structured support in AI use significantly outperform peers who use AI unguided or uncritically (Holt & Harris, 2024). Left to its own devices, AI becomes a shortcut. Integrated into a structured learning journey, it becomes a scaffold for deeper inquiry.
The Traffic Light System: Teaching Ethical and Effective Use
One practical approach to this balance is the Traffic Light System. In this model, AI use in student work is categorised into three bands:
Green – Enhances learning without replacing it (e.g., brainstorming prompts, language practice, data analysis).
– Enhances learning without replacing it (e.g., brainstorming prompts, language practice, data analysis). Amber – Risks displacing the learning process and needs monitoring (e.g., using AI to paraphrase or summarise without reflection).
– Risks displacing the learning process and needs monitoring (e.g., using AI to paraphrase or summarise without reflection). Red – Replaces learning or violates academic integrity (e.g., full AI-generated assignments).
This framework, introduced in AI for Learning, provides clarity for students and teachers alike, distinguishing between collaboration and collusion. It helps learners understand when AI acts as a learning partner—and when it undermines their growth.
AI is Pedagogy, Not Product
We need to think of AI not as a plug-in but as part of a pedagogy of possibility. As AI for Learning outlines, the most meaningful AI integration isn’t platform-dependent. It happens when:
Teachers model metacognitive reflection—asking not just “What did you write?” but “How did AI shape your thinking?”
Students are encouraged to interrogate AI outputs, question accuracy, and add their own insights—developing digital and critical literacy simultaneously.
Learning objectives drive AI use, not the other way around.
This is the heart of the book’s Assessment-as-Learning principle: assessment isn’t just about measuring what students know. It’s about helping them learn through the process of inquiry, revision, and reflection—with AI as a thinking partner, not a ghostwriter.
Equity and Access: Avoiding a Two-Tier AI System
Another urgent issue the book raises is equity. If AI tools are only accessible to students whose families can afford subscriptions or devices, we risk deepening existing achievement gaps. AI for Learning recommends school-led solutions: centralised subscriptions, in-school access, and parent workshops to ensure that AI becomes a bridge, not a barrier.
Education leaders must ask: Are we equipping all students—not just the privileged few—to harness AI responsibly and reflectively?
Assessing the Learner, Not the Output
One of the most provocative questions AI for Learning poses is this: “What are we really assessing when students use AI?”
Traditional assessment often focuses on the final product. But when AI is in the mix, educators need to shift the lens. Did the student understand how to refine the AI output? Did they cross-check the facts? Did they integrate their voice, their argument, their evidence?
To support this shift, the book offers over 100 assessment strategies categorised across five learner levels—from foundational to mastery. These assessments aren’t about checking AI usage; they’re about checking learning through AI usage.
Cultivating AI Fluency, Not Just Compliance
Ultimately, schools need to prepare students not just to use AI but to thrive in a world shaped by it. That requires more than teaching prompt engineering or banning ChatGPT. It demands a fundamental change in how we define success in school.
Instead of asking “Can students write this without AI?”, we must begin asking:
“Can students show us what they’ve learned with AI?”
“Can they reflect on how they got there?”
“Can they distinguish AI’s voice from their own—and use that difference to grow?”
That’s what fluency looks like. And it starts not with the tech we buy, but with the trust we build—in our learners’ ability to engage, critique, create, and reflect.
It’s Not the Tool—It’s the Thinking
Schools that treat AI as an add-on will never unlock its power. Schools that treat AI as a thinking partner, a means to deepen learning, will transform education. Not because of the tools—but because of the thinkers they help shape.
As AI for Learning reminds us: “Used well, AI becomes the Aristotle to a learner’s Alexander. Used poorly, it is as poor a learning tool as ‘cut and paste’” (Holt & Harris, 2024, p. 41).
Let’s teach our students to lead—not follow—their tools.
Reference
Holt, S. & Harris, A. (2024) AI for Learning: 101 Assessment Strategies for K-12 Schools Unlocking Mastery of AI. London: Belgravia Press.
About the authors
Stephanie Holt is an educator with over 20 years of experience, having worked globally in various capacities including as an Advanced Skills Teacher of English in the UK, School Improvement Officer, Vice-Principal in Malaysia, and Deputy Head in Moscow. Currently, she is the Director of Learning and Teaching in Mumbai.
Involved with the OECD Classrooms+ initiative, Stephanie has delivered workshops for COBIS on metacognition and using AI for Learning, will be speaking at the OECD Classrooms+ conference 2025 and was a keynote speaker at the WCE Conference 2024. Her forward-thinking approach has been recognised by her shortlisting for the GESS Award 2024 for Positive Change in Education.
She has co-authored the book “AI for Learning: 101 Assessment Strategies for K-12 Schools” with Alexander Harris. Stephanie is a thought leader in AI and education, contributing regularly to global conversations on enhancing learning outcomes through innovation. Her research as a PhD candidate for Brunel University London and work at DSB International School, Mumbai significantly enhances educational practices, empowering educators and fostering student success.
Alexander Harris is an educational leader with a global career spanning multiple continents. He holds a Master’s in Educational Leadership with Distinction from UCL’s Institute of Education and has held senior roles in prestigious international schools. Alexander is known for his innovative approach to AI integration and curriculum design, driving academic growth and fostering ethical leadership.
His expertise in change leadership has transformed educational communities, empowering educators to create dynamic, student-centered learning environments. Alexander has led successful AI-driven initiatives that enhanced student engagement and achievement.
He is the author of two upcoming books on education and numerous novels and plays under the pen name ‘Thomas Alexander.’ As a sought-after speaker, Alexander shares visionary insights on AI in education, curriculum design, and leadership development. His work is grounded in servant leadership, promoting integrity and equity as transformative forces for good in education.
| 2025-06-04T00:00:00 |
2025/06/04
|
https://ecis.org/beyond-the-tool-ai-education/
|
[
{
"date": "2025/06/04",
"position": 92,
"query": "AI education"
}
] |
What do employers need to consider when using AI?
|
What do employers need to consider when using AI?
|
https://www.littler.com
|
[] |
When using AI, it's important to look beyond the sticker price and consider the “total cost of use,” which is the real cost of what it takes to use an AI tool ...
|
What do employers need to consider when using AI?
When using AI, it’s important to look beyond the sticker price and consider the “total cost of use,” which is the real cost of what it takes to use an AI tool responsibly and sustainably over time.
Now some expenses are obvious – training your employees, increasing internal tech expertise, and ramping up data storage. But the less obvious costs can be even more significant. For instance, consider the resources and time – including the lead time you need to build in – for regulatory compliance, ongoing monitoring of the AI, and managing new legal risks.
So, what you need to do is set up an AI governance policy.
Decide your organization’s philosophy with respect to AI: its enthusiasm for AI use versus its general risk aversion.
Then set up a process for identifying and vetting proposed AI tools and uses.
Next identify the stakeholders — Legal, IT, Privacy, Procurement — who can collectively assess the risks (and benefits) of these AI proposals.
Next, develop the business’s guidelines for that vetting of AI doing practically but responsibly – tin other words the do’s, don’ts, and other risk considerations.
Finally build a policy around that vetting.
And don’t forget to provide for ongoing employee training as well as AI monitoring.
Finally, with an increase in the autonomy of AI be prepared for a technological shift from language models to action models that complete transactions on the business’s behalf – Like a chatbot that interviews and dispositions candidates; a virtual assistant that summarizes meetings and creates action items; or an AI coach that personalizes training programs and provides individualized recommendations for improvement.
These models, often referred to as “Agentic AI,” can expose your business to compliance obligations and liability so employers must account for the risk resulting from the use of such agents.
Fortunately, Littler’s AI and Technology practice stands ready to help you on each step of this journey – all you have to do is reach out!
| 2025-06-04T00:00:00 |
https://www.littler.com/news-analysis/2-point-video/what-do-employers-need-consider-when-using-ai
|
[
{
"date": "2025/06/04",
"position": 7,
"query": "AI employers"
},
{
"date": "2025/06/04",
"position": 5,
"query": "artificial intelligence employers"
}
] |
|
Nearly half of CEOs say employees are resistant or even ...
|
Nearly half of CEOs say employees are resistant or even hostile to AI
|
https://www.hrdive.com
|
[
"Carolyn Crist"
] |
AI adoption faces three barriers: organizational change management, a lack of employee trust and workforce skills gaps, a report shows.
|
Listen to the article 3 min This audio is auto-generated. Please let us know if you have feedback
Few companies have aligned their workforce strategies with their artificial intelligence investments, leaving a major gap in preparedness and talent needs, according to a May 29 report from Kyndryl, an enterprise technology services firm.
About 7 in 10 leaders responding to a survey said their workforce isn’t ready to successfully leverage AI tools, and half said their organizations lack the skilled talent to manage AI.
“Only a small group of businesses have been able to harness AI successfully for business growth,” Michael Bradshaw, global practice leader for applications, data and AI at Kyndryl, said in a statement. “This report shows that while data architecture and technology infrastructure are key pieces of the puzzle, organizations that do not prioritize their workforces will miss out.”
In the survey of more than 1,000 senior business and technology executives, 95% said they’ve invested in AI, but only 14% have aligned their workforce, technology and growth goals. In addition, 45% of CEOs said most of their employees are resistant or even openly hostile to AI.
Workforce readiness varied by industry, with the highest levels of preparedness reported in the banking, financial services and insurance sectors and the lowest in healthcare.
Kyndryl noted three key barriers to AI adoption: organizational change management, a lack of employee trust in AI and workforce skills gaps. The “AI pacesetters” — or the 14% of companies with aligned workforces — appear to be addressing these barriers, the report found.
For instance, pacesetters were three times more likely than other companies to report a fully implemented change management strategy for AI in the workplace. These companies were also 29% less likely to cite fears about AI affecting employee engagement.
Notably, AI pacesetters were 67% more likely to agree that their organizations had the tools and processes to accurately inventory the skills that their employees have, and about 40% reported no skills challenges.
So far, only 10% of companies qualify as “future-ready” in terms of having structured plans to support workers, build skills and lead through AI-related disruption, according to a survey by the Adecco Group. Most companies struggling with the transformation expected workers to proactively adapt to AI, while future-ready companies prioritized skills-based workforce planning, the report found.
In general, employers don’t understand workers’ AI-related training needs, which can hinder them from creating robust upskilling plans, according to an Amazon Web Services report. Most IT decision-makers said they lacked knowledge of how to implement training programs, and 41% said they had limited training budgets.
Despite limited training, nearly 7 in 10 companies now use AI tools for work, according to an OwlLabs survey of knowledge workers. About a quarter of workers said their employers strongly support AI use and supply tools, training and clear workplace guidelines.
| 2025-06-04T00:00:00 |
2025/06/04
|
https://www.hrdive.com/news/employers-employees-resistant-hostile-to-AI/749730/
|
[
{
"date": "2025/06/04",
"position": 39,
"query": "AI employers"
},
{
"date": "2025/06/04",
"position": 8,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/04",
"position": 9,
"query": "workplace AI adoption"
}
] |
How industries leverage AI
|
Businesses leveraging AI
|
https://www.edx.org
|
[] |
5 ways industries leverage AI · 1. Medical diagnostics and patient care · 2. Customer service · 3. Product development · 4. Customer segmentation · 5. Online ...
|
By: Shelby Campbell, Edited by: Valerie Black
Last updated: June 4, 2025
More businesses than ever are using AI to streamline daily operations. According to the Stanford University AI Index report, 78% of organizations used AI in 2024, up from 55% in 2023. Explore how industry leaders are integrating AI into their organizations, and find an online AI course for your field on edX.
Why are companies embracing AI?
AI is a technology that simulates human learning and intelligence in computers and machines, enabling systems to learn, solve problems, and create. This technology can perform complex tasks — and often complete them quickly.
Companies are rapidly adopting AI to transform their operations, using it to automate repetitive tasks and optimize workflows. The technology has become so widespread that businesses that don't embrace AI fear falling behind their competitors.
5 ways industries leverage AI
The optimal ways for a business to use artificial intelligence vary by industry. Here are examples of specific ways AI is being used in different sectors.
1. Medical diagnostics and patient care Some hospitals are using AI to make their patient care more responsive and efficient. It may be used to create patient scheduling and intake systems that can dramatically reduce how long patients have to wait for appointments and treatment. AI is also being used in diagnostics to analyze medical data. For example, AI can be used to make diagnoses based on lab tests and medical imaging, which can help doctors create personal treatment plans for their patients more quickly and easily.
2. Customer service In customer service, AI is often used for virtual agents. Virtual agents can answer customer questions and address their concerns. According to the Bureau of Labor Statistics, a research study focusing on call centers showed that AI tools increased the number of successfully resolved customer issues by 14%. As a result, call center agents were able to decrease their response time, increase the volume of chats they respond to, and increase the number of resolved conversations.
3. Product development Many industries are using AI throughout the product development process. AI technologies help generate product ideas and determine the most optimal features for products going into production. AI systems trained on customer preferences can provide targeted feature suggestions for new products. Product designers can prompt AI agents to improve existing product designs and concepts while ensuring that products meet expected quality standards.
4. Customer segmentation Customer segmentation is the process of categorizing customers by their demographics and characteristics. In marketing, AI is useful in the customer segmentation process because of its powerful data analysis capabilities. AI can use algorithmic analysis to find data patterns that allow for customer segmentation. This information can support the implementation of targeted product creation and marketing campaigns.
5. Online education Online education is another industry leveraging AI. Educators can use AI tools for repetitive tasks, such as answering routine communications and grading assignments. With online education, it's also easier to personalize learning for students. For example, teachers can use specialized AI tools to personalize curriculum and methods to each student's learning style and pace. Educators can also use AI to analyze curriculum requirements and trends when planning lessons.
The future of AI in industries
Despite many innovations across industries, AI technology is still in its infancy. According to Stanford University's AI Index report, the number of patents for AI technologies grew nearly 25% globally between 2023 and 2024. But the growing presence of AI tools doesn't necessarily mean that AI proficiency is currently a top priority for employers.
In the 2024 Graduate Management Admission Council (GMAC) Corporate Recruiters Survey, recruiters ranked AI skills 21st out of 22 in current importance and fourth in the future. Instead, they listed problem-solving and strategic thinking as the most important skills for candidates now and in five years.
This research suggests that while technical AI expertise is gaining value, the ability to apply AI tools to real-world business challenges is likely to be more impactful than technical skills alone. As a result, employers increasingly see AI as an assistant that accomplishes menial tasks, allowing employees to funnel their time toward more engaging work that brings more value to a company.
| 2025-06-04T00:00:00 |
https://www.edx.org/resources/how-industries-leverage-ai
|
[
{
"date": "2025/06/04",
"position": 46,
"query": "AI employers"
}
] |
|
The AI impact: three trends shaping the future of work
|
Three AI trends transforming the future of work
|
https://www.ey.com
|
[
"Samta Kapoor",
"Gil Forer",
"Authorsalutation",
"Authorfirstname Samta Authorlastname Kapoor Authorjobtitle Ey Americas Energy Ai",
"Trusted Ai Leader Authorurl Https",
"Www.Ey.Com En_Us People Samta-Kapoor",
"Authorfirstname Gil Authorlastname Forer Authorjobtitle Digital",
"Business Disruption Leader",
"Global Markets Authorurl Https",
"Www.Ey.Com En_Us People Gil-Forer"
] |
The rise of AI and generative AI (GenAI) is transforming the workplace, reshaping the jobs that employers will need and the skills employees must develop.
|
Read this case study to learn how Bayer Crop Science is using large language models to plant the seeds of the future.
The duality of AI: jobs that use and jobs that are AI
Today, AI technologies are increasingly integrated into work processes, primarily serving as assistants to humans. For example, analysts use AI to sift through vast data sets and uncover valuable insights. However, the future of work will not just adapt to AI; it will be fundamentally transformed by it, leading to the replacement of humans in many roles and the creation of entirely new positions designed around AI capabilities. As AI continues to advance, organizations will need to reassess their workforce structures, as some traditional roles may become obsolete while new opportunities emerge that leverage AI’s strengths.
In data engineering and analysis, organizations are likely to adopt self-service analytics tools that can be queried using natural language, democratizing access to technology. As a result, traditional analysts may evolve into “insights engineers,” taking on advanced responsibilities, such as guiding predictive modeling and prescriptive analytics. In this scenario, AI becomes the core function that defines the job.
In mergers and acquisitions (M&A), the distinction between jobs that use AI and those defined by AI capabilities is increasingly significant. While traditional analysts may leverage AI tools to enhance data analysis and streamline due diligence, new roles are emerging that center around AI technologies.
For example, AI-driven deal analysts or predictive modeling specialists will develop and refine algorithms that assess potential merger outcomes or identify strategic acquisition targets. These roles require a deep understanding of both AI and the complexities of the M&A landscape, focusing on harnessing AI’s capabilities to provide insights that drive decision-making. As organizations navigate the intricacies of M&A, they must cultivate a workforce that excels in both utilizing AI as a powerful tool and innovating with AI as a core element of their strategy.
| 2025-04-25T00:00:00 |
2025/04/25
|
https://www.ey.com/en_us/insights/emerging-technologies/three-ai-trends-transforming-the-future-of-work
|
[
{
"date": "2025/06/04",
"position": 98,
"query": "AI employers"
},
{
"date": "2025/06/04",
"position": 9,
"query": "future of work AI"
},
{
"date": "2025/06/04",
"position": 68,
"query": "workplace AI adoption"
}
] |
Journalism
|
Journalism – Pivot to AI
|
https://pivot-to-ai.com
|
[] |
Category Journalism · Washington Post goes AI to clean up amateur right-wing op-eds · Business Insider layoffs as traffic drops — but publisher Axel Springer says ...
|
Patrick Soon-Shiong, the billionaire owner of the LA Times, has been trying to turn the paper into a right-wing mouthpiece since he bought it in 2018. After Soon-Shiong refused to allow the editorial board to make a presidential endorsement in…
Like this: Like Loading...
| 2025-06-04T00:00:00 |
https://pivot-to-ai.com/category/journalism/
|
[
{
"date": "2025/06/04",
"position": 72,
"query": "AI journalism"
}
] |
|
June 2025 Job Market Report: AI and Software Roles Rise
|
June 2025 Job Market Report: AI and Software Roles Rise
|
https://blog.getaura.ai
|
[
"Aura'S Staff Are Dedicated Experts In Workforce Analytics",
"Organizational Decision Intelligence. Combining Deep Industry Knowledge With Cutting-Edge Ai Technology",
"They Empower Clients To Make Smarter",
"Faster",
"More Impactful Decisions. With Backgrounds In Consulting",
"Technology",
"Data Science",
"Aura S Team Is Passionate About Delivering Actionable Insights That Drive Innovation",
"Business Success."
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Job postings tended to decrease in generalist roles, but job gains in AI and data suggest a shift in the labor force, not an entirely broad-based shrinkage.
|
Amid a Slowdown, Software Stays Strong
According to Aura’s latest labor statistics, the U.S. labor market is showing signs of a strategic reset rather than a collapse. The June 2025 Job Market Report, which uses data through May, reveals a sharp divergence: while overall hiring has decreased in many sectors, there has been accelerated job creation in highly specialized roles, especially in areas such as AI, software engineering, and public sector modernization.
These shifts reflect broader economic uncertainty. From the Federal Reserve’s recent decision not to cut interest rates, to tariffs and ongoing inflation pressure, businesses are navigating complex trade-offs. Still, employers are selectively expanding their teams in areas that promise long-term return on investment, focusing on skills in data, automation, and cross-functional expertise.
Curious how Aura’s AI-powered labor market insights can drive your strategy? Request a demo to explore hiring trends, workforce shifts, and sector-specific data in near real time.
Global and U.S. Job Markets Show Broad Retraction
In May, global job posting trends painted a mixed picture. The Middle East and North Africa, as well as Latin America, saw modest growth, likely signaling pockets of resilience or targeted regional expansion.
In sharp contrast, North America recorded a 6.7% decline in job postings, one of the steepest drops among major regions, suggesting widespread corporate caution. Europe and Asia Pacific also experienced contraction, reinforcing a global cooling in hiring sentiment.
Within the United States, this trend was evident at the state level. Nearly every state reported declines in job postings, with economic powerhouses such as California, Texas, and New York leading the decline. This nationwide contraction appears systemic rather than isolated, likely driven by a combination of inflationary pressure, high interest rates, and a strategic shift toward cost containment.
Labor Market Signals
According to ADP, private sector hiring in May rose by just 37,000 jobs—the lowest monthly gain in more than two years and well below expectations. This slowdown is a clear signal of cooling labor demand across much of the economy. As Aura's job posting data provides a future-looking focus, this could indicate that the slowness will not end in May.
Goods-producing industries, such as manufacturing and mining, posted losses, while gains in the service sector were mostly concentrated in the leisure and hospitality sector. The hiring decline among smaller businesses also reinforces the challenges facing employers outside of high-demand, future-focused roles.
Still, this isn’t 2008—or even March 2020. It’s a recalibration. Aura’s data indicate that job growth should continue in certain core services, including healthcare, staffing, and human resources. These industries aren’t merely treading water; they’re hiring for resilience and internal transformation.
However, the broad slowdown aligns with broader macro sentiment: economists believe the economy is cooling and perhaps even contracting.
AI Job Growth 2025: Hiring Trends
Despite fewer positions overall from its peak, AI job postings remained strong as a share of total software roles, at 14% of all software roles. Employers are clearly prioritizing job openings related to automation, insight, and AI integration, signaling that AI is moving from a strategic ambition to a tactical necessity.
AI hiring is no longer limited to specialized tech firms. It’s showing up across hospitality, healthcare, HR, and professional services. What’s changing is not just who’s hiring, but what they’re hiring for. AI-trained project managers, generative content leads, and operations-focused engineers are in high demand, particularly in companies seeking to integrate large language models (LLMs) into their everyday workflows.
Aura’s labor market insights were recently featured in The Washington Times, highlighting national trends that impact new graduates and junior roles. According to data from Aura, quoted in the article, openings for positions that don’t require previous experience are down between 7% and 10% compared to last year. Meanwhile, entry-level jobs that demand artificial intelligence skills have jumped by 30%, underscoring the shift toward a more specialized, skills-based hiring market. “Companies are leaning into skills-based hiring, and that’s creating both opportunity and friction for new grads,” said Evan Sohn, Aura’s CEO.
Software Engineering Demand Rises in Government and Infrastructure
Software engineering appears to be defying the broader labor market slowdown, despite many expressing concerns about a radical change, and even collapse, of software jobs. From March to May, job openings for software development increased steadily, likely reflecting both seasonal hiring trends and post-budget execution cycles.
But what’s most telling is where the job gains are happening. Not just in traditional tech. We’re seeing strong growth in government, infrastructure, and traditional industries that are digitizing their operations. Civil engineering and defense contractors, for example, are hiring developers to modernize their systems.
Aura’s data indicates that roles such as Application Engineer and Infrastructure Engineer are experiencing rapid growth, especially in regions that benefit heavily from federal tech investments and procurement cycles.
Remote Job Trends: Expanding Beyond Tech
In May, remote job growth was primarily driven by the technology and staffing sectors—industries that have long embraced digital infrastructure and distributed workflows, and stayed relatively stable at 7.1%. Their continued adoption of remote work reflects its scalability, cost-efficiency, and alignment with global talent sourcing strategies.
However, some of the largest shifts came from traditionally in-person sectors. Individual and family services experienced a nearly 190% increase in remote job postings, the highest percentage gain across all industries. This surge likely reflects the growing adoption of digital tools for telehealth, remote counseling, and virtual administrative support. Though a small industry, it is a good example of the optimizations certain workplaces can benefit from.
Retail and event services also demonstrated positive momentum in remote job opportunities, indicating that hybrid models are gaining traction, even in customer-facing industries.
These developments highlight a broader trend: remote work is no longer confined to white-collar tech roles. Organizations across diverse sectors are aligning hiring strategies with both operational agility and worker preferences, helping to normalize remote employment as a viable model in more industries than ever before.
Hiring Strategy in 2025: Specialization, Upskilling, and Return on Investment
Here’s the through-line: the economy is slowing in some areas, but it does not appear to be spiraling out of control. Instead, employers are redirecting their spending toward positions that align with long-term business priorities: automation, resilience, and agility.
Key insights:
Job postings tended to decrease in generalist roles, but job gains in AI and data suggest a shift in the labor force, not an entirely broad-based shrinkage.
Remote work has stabilized, particularly for tech and analytics roles, indicating that hybrid models are now integral to organizational strategy.
These points indicate a more professional, skills-based trend in hiring: employers are focused, not frozen.
What’s Next: Late Q2 or Early Q3 Rebound?
We may see a moderate hiring rebound by late Q2 or early Q3. Here’s why:
Companies typically freeze hiring in May or June to reassess their goals, especially during periods of economic pressure.
If the Federal Reserve signals a reduction in interest rates, that could unlock new job openings.
Specialized roles in AI, cloud engineering, and operations are showing momentum, often a precursor to broader employment upticks.
In short, while the job posting numbers and top-line metrics show softness, the underlying trend data tells a more optimistic story, especially for skilled workers and forward-looking employers.
This labor market isn’t defined by blanket growth or decline. It’s defined by intentional hiring in areas that matter most for competitive positioning.
Track the trends that matter. Book a demo of Aura’s AI-powered workforce analytics to plan smarter, hire better, and stay ahead of economic shifts.
Commentary on the June Job Market from Evan Sohn, Aura CEO
CNBC Interview
Schwab Network
.@aurainsights CEO Evan Sohn says he's "not as optimistic about the jobs report as everyone else" and is "shocked" there's so little noise about the revised numbers. pic.twitter.com/4L9Z7esIfx — Schwab Network (@SchwabNetwork) June 6, 2025
Or watch the full interview with Aura Intelligence on Schwab Network
| 2025-06-04T00:00:00 |
https://blog.getaura.ai/june-2025-job-market-report-ai-and-software-roles-rise
|
[
{
"date": "2025/06/04",
"position": 4,
"query": "AI labor market trends"
},
{
"date": "2025/06/04",
"position": 17,
"query": "job automation statistics"
}
] |
|
The Great Tech Layoff Lie and the Convenient AI Scapegoat
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The Great Tech Layoff Lie and the Convenient AI Scapegoat
|
https://aimmediahouse.com
|
[
"Aim Media House",
"Aim Research Is The World'S Leading Media",
"Analyst Firm Dedicated To Advancements",
"Innovations In Artificial Intelligence. Reach Out To Us At Info Aimresearch.Co"
] |
Big Tech's hiring plunge isn't a shockwave from AI—it's the result of bloated R&D budgets, reckless over-hiring, and macroeconomic pressures ...
|
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A recent graph circulating on LinkedIn shows major tech giants slashing software engineering headcount at rates that would terrify any fresh CS graduate. Instantly, fingers flew to AI automation as the culprit. But this narrative—AI devouring entry-level jobs—is a convenient red herring. In reality, these companies over-extended themselves in 2021–22, carrying massive R&D payrolls that never translated into proportional ROI. When macroeconomic headwinds hit, the first to go were the thousands of brand-new grads deemed “non-critical.” Blaming AI masks the real issues: reckless expansion, bloated bureaucracy, and short-sighted management. The AI Scapegoat: Easy, But Misleading Anyone scrolling through Twitter or LinkedIn these days will see the same refrain: AI is ste
| 2025-06-04T00:00:00 |
2025/06/04
|
https://aimmediahouse.com/market-industry/the-great-tech-layoff-lie-and-the-convenient-ai-scapegoat
|
[
{
"date": "2025/06/04",
"position": 60,
"query": "AI layoffs"
}
] |
Graduates pivot careers due to AI and job automation
|
Graduates pivot careers due to AI and job automation
|
https://ise.org.uk
|
[] |
The impact of AI on work has raised concerns about job displacement. More than one in ten (11%) of graduates said that they are already changing their ...
|
AI is impacting the early career decisions of young people, reveals a new report from Prospects at Jisc.
With the rise of AI, graduates are entering a labour market where traditional roles are evolving and new ones are emerging.
Each year Prospects Early Careers Survey reports the career aspirations and experiences of more than 4,000 students and graduates. For the first time, the survey has shown that AI is having a marked impact on career views and choices as well as how students approach job applications.
Graduates change careers due to AI
The impact of AI on work has raised concerns about job displacement. More than one in ten (11%) of graduates said that they are already changing their career plans due to AI.
While 14% of graduates said the rise in job automation had made them feel pessimistic about their career prospects, 43% already wanted to leave their current employer. Students reported similar concerns in a report by Jisc on perceptions of AI.
The survey found that most graduates were changing careers as they fear job obsolescence. Areas such as coding, graphic design, legal, data science, film, and art were frequently mentioned, with creative jobs seen as the most at risk.
Moli Hitchen is a graduate in Korean Language and Japanese. They are currently in their final year of a master's degree at the University of Sheffield:
“I wanted to pursue a career in translation. Due to the advancement in AI, however, the need for human translators is rapidly decreasing. I am now looking for other ways to use my language skills and am leaning towards something in consultancy or marketing.”
AI presents opportunities for some graduates
Some respondents to the survey felt that AI had created more job opportunities, allowing them to explore careers that didn’t exist, were unattainable or that made use of new technology. Laura Tinsley said:
"I'm studying policing at Sheffield Hallam with the intention of progressing into a local police force and becoming a detective. However, AI was highlighted as a turning point in the way crimes are articulated and devised. This has opened up many new jobs within the criminal justice system. I’m now looking at graduate roles in intelligence to combat the ever-growing crime AI can facilitate. I am also interested in postgraduate education to gain further understanding of cybercrime, which I had never considered prior."
AI in job applications
Prospects Early Careers Survey also looked at what influenced career decisions and the steps graduates were taking to get the job they want.
Nearly a fifth of respondents said they had used generative AI tools like ChatGPT and Microsoft Copilot as a source of careers advice, and 84% rated them as helpful.
AI was also used widely to save time when applying for jobs, meaning they could apply for a higher number. A quarter said they are applying for as many jobs as possible to improve their chances with 27% of graduates sending out more than 50 applications.
This reflects ISE data that found the average employer receiving 140 applications per graduate job, a 59% increase on the previous year.
Some 43% of applicants used AI for editing a CV or cover letter, 35% for writing a CV or cover letter from scratch, 29% when preparing or practising for interviews, and 26% for answering questions in application forms.
Fewer graduates said they used the technology for completing online tests (9%) such as psychometric assessments, and during interviews (3%).
Jodie Fodden recently graduated from The Open University with an MSc in Environmental Management and BSc Honours in Environmental Studies. They have used AI to apply for 50 jobs so far this year: “I was always reluctant to use AI in application processes as I felt strongly that I should be able to pass screening based on my own merits. But after spending 12 months and countless applications, not even getting past screening, I’m now using it.
“This year, I have applied for 50 jobs so far and have received three interviews since using AI. I use it to draft any statements I need to produce. So, I feed in all my background information and all the job information and any relevant information about the company to draft my statements. I then proof read and adjust it to correct any Americanisms and give it my personal touch. I also use AI to help me prepare for interviews. On one occasion I used AI to help me draft my answers to potential questions and design the presentation I had to deliver.”
Through this uncertainty and transition, students and graduates need guidance from everyone who supports them at school, college, university and in the workplace.
This includes helping students to understand how and when to use AI tools, spot when the information provided is outdated or incorrect, and combine them with other resources to ensure they get a fully rounded picture.
It’s important that young people understand that AI might be disrupting work as we know it but this change is more about reshaping job roles rather than displacing them.
| 2025-06-04T00:00:00 |
https://ise.org.uk/knowledge/insights/431/graduates_pivot_careers_due_to_ai_and_job_automation/
|
[
{
"date": "2025/06/04",
"position": 76,
"query": "ChatGPT employment impact"
}
] |
|
How artificial intelligence (AI) tools impact human resources
|
How artificial intelligence (AI) tools impact human resources
|
https://www.zayzoon.com
|
[
"Sarah Macdonald",
"Sarah Is A Writer",
"Editor Toronto."
] |
AI has been automating processes and streamlining work functions for a long time. Yet, when OpenAI launched ChatGPT, only two years ago, it seemed like that's ...
|
Technology sometimes moves faster than we anticipate. That feels especially true with artificial intelligence (AI). AI has been automating processes and streamlining work functions for a long time. Yet, when OpenAI launched ChatGPT, only two years ago, it seemed like that’s all anyone could talk about, especially when it comes to work.
How AI is going to impact human resources workers is important. Such technological advancement, the theory goes, can help expedite certain manual processes in HR departments and optimize better decisions with data compiled from AI tools to back that up. That’s why, according to a report by Gartner, 76% of HR professionals believe that if AI isn’t adopted in some way over the next few years, they might actually be behind the rest of their peers.
However flashy and exciting AI is in the workplace, moving with the speed of the technology can have some drawbacks. AI is modernizing how HR workers do their jobs but there are limitations.
Ahead, we’ll guide HR workers and team leaders on how AI impacts their roles, including use cases and challenges, and why a human touch is still going to go the distance.
What is AI?
Artificial intelligence is a type of computer science that provides machines with the ability to perform certain functions—such as logic, reasoning, planning, learning, and perception—through algorithms and machine learning. Some AI is sentient, in that it can respond to emotions, but for the most part, the AI tools we use in a business setting are fairly functionally-driven.
Generative and predictive AI have opened a new way to work. They enhance decision-making, streamline operations, and transform HR practices. This leaves more space for creative thinking and implementation.
Let’s dig into these different types of AI and they can do for you.
Generative AI
Generative AI is designed to mimic human intelligence for specific tasks. The most common example of a generative AI is ChatGPT. Once it receives a prompt, ChatGPT analyzes content for patterns and generates texts or visuals, sometimes summaries or analyses. For example, you can prompt the tool to generate generalized job descriptions based on experience needed, tasks involved with the role, or career development to brainstorm off of to help create original content for your own post.
Predictive AI
On the other hand, predictive AI identifies, analyzes, and breaks down patterns in past events and general trends. This type of AI tool can make predictions about what’s going to happen in the future. You may use AI to keep a pulse on the recruitment market or to identify key HR or employee management trends.
Using AI tools in the modern HR landscape
In the US, nearly 40% of enterprise sized organizations are using AI in their HR departments. AI has so many use cases but where it’s most beneficial and useful for HR teams depends on your needs and unique role. It can be used to automate processes, create better workflows, or generate copy to work off.
These are some of the most significant ways to use AI in HR:
1. Talent acquisition
AI, according to a report conducted by SHRM, is mostly used for recruitment. AI tools can identify and process information about the best places to find candidates for different roles. AI tools, for example, can automate résumé screening to identify suitable candidates. Such AI tools may ensure candidates don't fall through the cracks due to human error.
These tools have the ability to personalize any communication with these candidates to keep them interested. For recruiters, AI can even help you create detailed profiles of ideal candidates for specific roles.
2. Employee onboarding and training
Once candidates have become employees, the next step is usually a thorough onboarding process. This can be fairly laborious for many HR professionals. AI tools can help streamline this process, as well as provide personalized training plans by analyzing data on their career goals, current performance, and related skills, as well as automate administrative tasks. This can improve onboarding and training overall.
AI chatbots, too, can act as round-the-clock HR assistants for new hires, providing quick answers to employees’ questions about leave policies, benefits, and other HR concerns. This not only enhances the employee experience but also helps new employees feel supported, knowledgeable and welcomed.
3. Employee engagement and satisfaction
AI tools allow managers to monitor employee performance and identify areas for improvement. These tools can understand employee sentiment by deploying and analyzing surveys, social media or other sources to measure overall satisfaction levels. Once you have a pulse on your team, you can then suggest appropriate training content to help them grow and stay engaged.
AI is most useful by processing, analyzing and summarizing data. Use this information to help make better decisions about employee engagement solutions.
4. Performance management
Evaluate employee performance by using AI tools to analyze data on key performance indicators (KPIs). The information from these tools can provide real-time feedback and suggest personalized development plans.
Challenges of using AI in HR
While the benefits of AI in HR are plenty, implementing AI is not without its challenges. These include ethical considerations, data privacy concerns, and resistance to change.
1. Ethics and bias
We like to think of AI as a separate entity from humans. However, all the data it consumes to generate information or analyses is based on content made by people. AI has an inherent bias that everyone needs to diligently monitor.
One example was when Textio ran an experiment prompting ChatGPT to write job descriptions. These descriptions went from the very generic to the more specific. A key concern that kept coming up throughout the exercise was the inherent gender, racial, and age bias that some of these listings contained. What was even more interesting is that some of these contained keywords that, although not openly discriminatory, were terms that people would avoid when looking for a job.
Ann Handley said in a MarketingProfs webinar: “We can’t give over writing to AI, because writing is thinking!” If AI tools are to be used to brainstorm any writing, ensure that you’re putting in prompts that are useful and precise, using critical thinking to check for inconsistencies and biases. It might be helpful to create a checklist of all the things AI might not account for and always check your content against it.
2. Data privacy and security
Here’s a familiar story: a coworker takes all of their meeting notes, which includes sensitive information, and drops it into ChatGPT. They want it to summarize the notes, bring out key topics, and identify action items to move forward. Summarizing is a key component of AI functionality.
However, and unsurprisingly, this resulted in a data breach. Now, that information was searchable within ChatGPT and accessible to anyone. Including their competition.
It must be said again and again until it permanently sticks: AI is a tool, not a person, and its sole function is to process an immense amount of data that can be accessed by nearly anyone. If giving over your private information to a stranger is forbidden, the same rules apply to AI tools.
Data privacy is a significant concern when implementing AI in HR. Personal data is the entire realm of HR departments. There’s a risk that sensitive employee information could be misused or data security breached. So it’s important to mitigate these risks by understanding what can go into an AI tool versus what cannot. HR departments must enforce strict data privacy policies. They should use firewalls to control access. They should also train employees on the secure usage of AI.
3. Loss of human element
As exciting as the advancements in AI are, it’s crucial to remember that human resources is about people. Maintaining a human element in HR processes is paramount, even as we adopt advanced technology.
AI tools are a partner, not a replacement, in HR departments. In an AI-driven HR department, striking that balance is critical, and can be beneficial for everyone involved. Technology can support efficiency and data-driven insights, and a professional HR manager can engage with employees and answer questions, and generally respect company culture and individual needs.
This balance can be achieved by focusing on human interaction at every stage of the employee lifecycle, like emphasizing communication and personalizing interactions.
AI and HR teams: working together
A very common question in almost every field when we talk about AI is: “Is this robot going to take my job?” That’s a valid question! The technology is new, and sometimes the word “optimized” is a synonym for replacement. Generative AI technologies continue to develop rapidly. The capabilities of these tools right now may change significantly in a matter of years—even months!
What integrating AI tools into HR functions can really be about is streamlining manual processes, not replacing human effort altogether. It’s a tool but you’re the professional.
AI tools allow you to focus on making HR a more iterative process. You have access to data-driven dashboards that can inform decisions. They can help be more transparent about the initiatives you’re running and gain more trust from employees. AI tools can also function as a lookout to help you address issues before they even reach you.
AI tools may actually allow HR professionals to focus on being creative, taking away hours spent on manual and administrative tasks. It can let you reconnect with your team.
Focus on training your teams. AI tools don’t need to needlessly complicate existing workloads. They can be useful partners to assist you in what can hopefully be stronger human connections elsewhere in your processes and in your people operations initiatives.
| 2025-06-04T00:00:00 |
https://www.zayzoon.com/blog/ai-in-human-resources
|
[
{
"date": "2025/06/04",
"position": 83,
"query": "ChatGPT employment impact"
}
] |
|
AI in HR: How is Artificial Intelligence Changing the ...
|
AI in HR: How is artificial intelligence changing the workplace?
|
https://employmenthero.com
|
[] |
Discover how artificial intelligence (AI) is changing the game for human resources, and how your business can benefit from using this innovative technology.
|
Artificial Intelligence (AI) has recently taken the world by storm and the world of employment is no different. So how is AI in HR transforming the HR landscape? It is reshaping everything from the way we work, to the way we hire.
But what is it and what does the adoption of AI mean for businesses and HR? We’re taking a look at how it’s changing the workplace and how it could benefit your business.
What is Artificial Intelligence?
Broadly speaking, AI enables computers to mimic human cognitive functions such as learning, problem solving and decision-making. AI can be used for almost anything from generating ideas to writing code and so much more. Pretty cool, huh?
But if you think that AI is only something tech whizzes use then you might be surprised to find you are already using AI in your day-to-day life. AI voice assistants like Siri, Alexa and Google’s Gemini have been used on smartphones and computers for several years now. But their capability is continually growing and now goes beyond simply answering questions or telling jokes. Businesses are beginning to adopt AI into their models, utilising their power to streamline processes, increase efficiencies in workloads and so much more.
The importance of machine learning
When you think of AI, you should also think of machine learning. It goes hand in hand, after all. The catch is, it’s not one and the same.
But it doesn’t stop people from getting AI confused with machine learning. So if you want it in plainer English you’re not alone.
Lee Bell from Wired magazine sums up the relationship between them perfectly: “you need AI researchers to build the smart machines, but you need machine learning experts to make them truly intelligent.”
Tech for Good is an example of just how powerful the relationship between AI and machine learning can be. After all, it is where innovation in tech has made a positive change.
Take, in the workplace for example, how the use of AI and machine learning has led to increased efficiency with AI algorithms being able to analyse CVs and cover letters to identify the best candidate for the job. Just like Employment Hero’s SmartMatch, hire smarter with AI-powered talent matches. Plus, chatbots can conduct preliminary interviews so HR teams can focus on more qualified candidates.
The benefits of AI in HR
If you’re wondering how on earth AI can play a role in HR, which is such a people-centric topic—you’re not alone.
More and more companies are adopting AI because of how it continuously improves everything in the employee lifecycle, from candidate experience to employee attrition.
Are you wondering exactly how it does this? AI uses deep learning based on employee performance data. The data is gathered from performance reviews, engagement surveys and productivity metrics and organised before it is analysed to identify potential patterns and employee performance predictions.
But how can this benefit you in HR?
Increase efficiency and streamline recruitment
AI is a powerful tool that can be used to not only help shave valuable time off from mundane tasks, but help to make decisions with the hiring process, and review current and prospective employees. AI takes less time than a person when tasked to create a personalised employee experience and it reduces recruiting bias too.
Hiring the right candidate out of a sea of interviewees can be a real headache—we feel you. AI can revolutionise talent acquisition making it time efficient and effective. Take the tedious back and forth that is often involved in arranging interviews. AI eliminates this with automatic interview scheduling allowing you to focus on what really matters—connecting with great candidates.
Plus CV screening minimises unconscious bias and saves valuable time as it means you can sift through vast amounts of applications in seconds identifying the best matches for your role at speed.
Let’s break this down further.
At the end of 2021, employers received an average of 506 applications for low-skilled vacancies, and 56 applications for high-skilled vacancies.
That’s a lot of CVs to go through.
This is why it’s no surprise that hiring managers are forced to spend only 6-8 seconds per CV, resulting in the potential chance of missing an excellent candidate.
However, beyond these rose-tinted glasses, you’ll find that there are ways candidates can adapt to beat an applicant tracking system (ATS)
Psst. Employment Hero has a variety of AI powered features including Hero AI, AI support in ATS and SmartMatch.
Enhanced decision-making
When large amounts of data are analysed, patterns and trends appear and this is how you can gain valuable insights into your business. AI can not only identify these patterns but it uses the data to predict various outcomes. Clever, right?
It can help you to spot signs early on that an employee is likely to leave for example or it can flag a potential turnover risk that you could be unaware of. It does this by looking at employee performance, job satisfaction surveys, attendance records and even market trends to deliver accurate insights on talent gaps that need to be filled.
This means smarter decision-making for you, not to mention a more engaged workforce. It’s a win-win.
Improve employee experience
At Employment Hero, we’re all about a positive employee experience and we know that AI can make going to work easier, more enjoyable and more engaging. We’ve seen AI offer personalised support, automate tedious tasks and perhaps most impressively, support career growth and help employees feel valued in their career path.
When utilised correctly, AI can create a more engaging, supportive and effective working environment which means higher levels of employee satisfaction. You can use AI to provide employees with 24/7 assistance in the form of chatbots so they can access support around the clock but by far the most rewarding aspect is that AI can suggest opportunities for growth.
We’re talking about personalised learning paths by assessing an employee’s skills and highlighting career advancement opportunities that align with their interests.
Will AI mean HR professionals risk losing their jobs?
We get it, the thought of AI coming in and replacing jobs is daunting, but that’s not the reality. From a business perspective, whilst the advantages that AI brings to the table are good, it cannot replace the human touch. People have the advantage of being able to examine something in a non-binary way—the ability to look into the grey area. After all, not everything is black and white.
Take performance reviews for example. AI would be able to tell you exactly how that person has performed over the course of a month. The advantage, of course, is being able to take away a bias that a manager may unconsciously have towards the team member.
However, AI won’t be able to tell you why someone has performed well, or poorly. It can’t tell you that someone has lost a loved one and their mental health is not doing well as a result, which has impacted their work.
At Employment Hero, our view is that AI can be utilised as a productivity tool, its purpose is to drive deeper work, simplify complex tasks, and reduce manual ones. This is exactly why we need to work hand in hand with AI and not fear it because of those pesky what-ifs.
The challenges of deploying AI in HR
As there are always two sides to a coin, It’s only fair for us to look into the challenges AI brings with its powerful technology. Deploying AI can feel like a wild rollercoaster ride, exciting but filled with unexpected twists and turns.
Bias and fairness
Everyone deserves an equal shot so how can you be sure that your AI systems are fair? These systems are programmed with historical data and if this data shows any signs of bias relating to gender, age or race, this could seep into your algorithm.
Dedicate time and energy to mitigate bias by training algorithms on diverse data to ensure that your hiring processes reflect your commitment to equality. You can use an AI fairness toolkit to help identify any fairness red flags.
AI vs human judgement
We believe that human oversight is essential when deploying AI in HR.
The Trades Union Congress (TUC) believes that the use of AI in HR decision-making could lead to widespread discrimination. And that any decision made by an AI, especially in regards to whether or not an employee will be fired—must be reviewed by a person in order to provide that grey area it lacks.
One third of SMEs think that AI could make a positive impact in HR. A study posted by Capterra revealed that AI can be used to make the HR practice fairer – but only if managed by a human. According to Forbes, talent acquisition is one of the key areas where AI has the potential to grow.
Data privacy
AI systems require a high volume of data which throws up issues with data privacy. Employees may have concerns about how their data is being used and shared especially when it comes to health-related data or performance-related data.
From a legal perspective alone, AI in HR should be managed in an ethical way but also in a mindful way to maintain employee trust. Be upfront and transparent about how employee data is being used and employ data safeguards to ensure that sensitive data is protected.
How to implement AI successfully within your HR function
Implementing AI successfully is all about embracing innovation while keeping your focus on people. After all, AI should enhance the human element of HR, creating a working environment where people and technology work hand in hand.
So how do you implement it?
Identify opportunities: Where can AI make the biggest impact for you? Is it recruitment, employee engagement or performance management? Having clear goals will pave the way to success.
Choose the right AI tools/systems: Not every AI system will be the right fit for your company. Opt for user-friendly software that aligns with your company goals whether that’s chatbot support, candidate screening or performance tracking. There is no cookie-cutter approach.
Fully integrated AI: It’s often beneficial for your AI to sit within your tools rather than in addition to. This ensures a more seamless user experience, reduces context switching, and allows your team to get value from AI directly within their existing workflows.
Test solutions: Next comes your detailed test plan. This plan will be your roadmap so establish a timeline for testing activities and have your plan approved before you execute it.
Gather feedback: Check in with your HR team, learn how the AI tools are performing, and note what works and what doesn’t.
Train your HR team and employees for adoption: For AI to have maximum impact, your team has to know how to use it. Training is the key to making AI work for you.
Monitor performance: Monitor the performance of your AI system in real-world scenarios to ensure it meets performance standards.
Continual optimisation of workplace AI usage: Monitor and assess the performance of your AI systems continually gathering feedback and making adjustments along the way.
What does the future workplace look like?
We’ve already covered a lot about AI and its applications but does AI have the potential to influence the future of the workplace and bring with it a brighter future?
Absolutely. But what does this look like? Well, AI will create a more data-driven, personalised and efficient workplace. With mental health and wellbeing finally in the front of mind for everyone from the human resources department to employees themselves, it will be interesting to see how much further AI develops to be able to help in this area. AI can analyse employee data to make tailored wellness programs that resonate with each employee.
It’s not just employee wellness that will be transformed. We can expect seamless onboarding tailored to each employee, automated admin tasks, (goodbye manual paperwork) and personalised wellness initiatives. Business owners and HR professionals can create a more empowering and seamless employee experience and foster an environment that is continuously improving.
Perhaps one day in the future, we will be able to use artificial intelligence to detect burnout before it starts.
Enjoy a smoother HR service delivery from the world’s first Employment Operating System from Employment Hero
Employment Hero’s Employment Operating System is more than just a platform—we’ve taken the traditional isolated aspects of employment and integrated them into a seamless, human and AI-powered solution that empowers employers, employees and job seekers alike. Find and hire top talent with SmartMatch, seamlessly onboard new hires, automate complex payroll, drive employee engagement and more.
Our all-in-one system puts HR, payroll, hiring & more all in one place.
One system. Everything employment.
| 2025-06-04T00:00:00 |
2025/06/04
|
https://employmenthero.com/uk/blog/artificial-intelligence-in-hr/
|
[
{
"date": "2025/06/04",
"position": 50,
"query": "artificial intelligence employment"
}
] |
What Economists Are Learning About AI, Jobs, and Local ...
|
What Economists Are Learning About AI, Jobs, and Local Economies
|
https://www.aei.org
|
[
"Julia Torres",
"Mark Jamison",
"Bronwyn Howell",
"Will Rinehart",
"John Bailey"
] |
The study also identified three key factors that predict a region's AI job growth: education, innovation, and tight labor markets. Areas with more STEM ...
|
Conventional wisdom about artificial intelligence runs in two directions—utopian and dystopian. On one hand, we’re told that AI will usher in explosive productivity, endless efficiency, and new industries we can’t yet imagine. On the other hand, there are fears that machines will hollow out middle-class jobs, exacerbate inequalities, and perhaps even make large swaths of the population economically obsolete.
But like the effects of most technologies, AI’s actual impact on jobs and communities turns out to be more complicated—and more interesting. At this year’s American Economic Association meetings, three new studies presented fresh evidence on how AI is reshaping how people work, prompting both optimism and reflection.
Via AP Images.
One study by economists from the US and Greece showed that AI job growth is real—but uneven. From 2018 to 2023, counties like Santa Clara, California—home to Silicon Valley—and even Slope County, North Dakota, saw AI-related jobs reach surprisingly high shares of total employment. Interestingly, some of the fastest growth occurred in remote-work-friendly or suburban areas such as Maries, Missouri and Hughes, South Dakota, suggesting that the rise of remote work may be expanding AI’s geographic footprint.
The study also identified three key factors that predict a region’s AI job growth: education, innovation, and tight labor markets. Areas with more STEM graduates, more patent activity, and less labor market slack were significantly more likely to adopt AI. In contrast, rural areas and regions reliant on traditional industries—such as manufacturing—lagged behind, suggesting that these industrial bases face greater difficulty integrating AI.
A second study focused on AI’s effects on Europe and found something unexpected: Exposure to AI increased the share of women in affected occupations. Across 16 countries between 2011 and 2019, a 10-percentile rise in AI exposure was associated with a 2.2–2.9 percent increase in the share of female employment. The effect was strongest in countries where women had made greater educational gains and already had relatively high workforce participation. Rather than displacing women, AI appears—at least for now—to be nudging certain sectors toward greater female employment.
A third study focused on France to examine how AI adoption affects firms and their workers. Between 2018 and 2020, firms in France that adopted AI were more likely to grow. These businesses were larger, more productive, and more likely to be in technical sectors to begin with. But critically, they also saw rising employment and sales after implementing AI. Even in occupations traditionally thought to be at high risk of automation, these firms hired more, not less. The productivity effects of AI—more output per worker—appear to be lowering costs and outweighing any task-level job displacement.
That said, not all uses of AI are equal. The study found that when AI was used for high-value purposes—such as improving cybersecurity—it was associated with job growth. But when AI was used for rote tasks, like administrative processing, the effect was mildly negative. In other words, AI doesn’t automatically destroy jobs or create them. Its effects depend on how firms use it.
Taken together, these studies offer a more nuanced—and exciting—view of AI’s economic consequences. The technology is spreading, but not evenly. Its adoption rewards regions that invest in education and innovation. It may be reducing gender disparities in some sectors; and in the right hands, it is boosting productivity and labor demand.
For policymakers, these findings suggest that the challenge is not to resist AI, but to prepare for it wisely. We should be enabling people to equip themselves with the skills to thrive in AI-augmented workplaces, ensuring that first movers aren’t the only ones reaping the benefits. AI, like other general-purpose-like technologies before it, holds the potential to make Americans more prosperous—but only if we let the market work and focus our public efforts where they matter most.
| 2025-06-04T00:00:00 |
2025/06/04
|
https://www.aei.org/technology-and-innovation/what-economists-are-learning-about-ai-jobs-and-local-economies/
|
[
{
"date": "2025/06/04",
"position": 61,
"query": "artificial intelligence employment"
}
] |
Mini-Lab: AI for Freelancers – ONA Events
|
Mini-Lab: AI for Freelancers – ONA Events
|
https://journalists.org
|
[] |
To learn more about supporting ONA's AI programming, contact Hanaa Rifaey, Head of Strategic Partnerships, at [email protected]. When. Wednesday, Jun. 4, ...
|
In this 45-minute hands-on workshop, we’ll work with the tools from the previous training to brainstorm ideas, write pitch letter outlines, FOIA requests and more. Participants get a handout with links to all the tools and some practice exercises.
Registration
Anyone is welcome to attend. Tickets are free.
Where will the meetup take place?
This event will be hosted on Zoom. For this particular event, you’ll have the best experience if you join via the Zoom app on a desktop or laptop computer so that you can see the presentation on a larger screen. You can also join using the mobile app, although the presentation may be harder to view.
Can I dial in by phone?
We recommend joining from your computer, tablet or phone using the Zoom app. You won’t be able to access the presentation slides, chat and exercises if you’re dialed in via phone only. If you’re unfamiliar with Zoom, we’ll have staff on hand to troubleshoot, and we also suggest checking out the Zoom support site for more help.
Will this event be recorded?
Yes, this event will be recorded. We will send the recording to everyone who registered after the event, regardless of whether or not they attended.
Will closed captioning be available?
Yes, we will enable Zoom’s closed captioning tool, which now supports closed captioning in both the main room and breakout rooms.
Funding for ONA’s AI in Journalism Initiative is generously provided by Microsoft, the Patrick J. McGovern Foundation and The Joyce Foundation. To learn more about supporting ONA’s AI programming, contact Hanaa Rifaey, Head of Strategic Partnerships, at [email protected].
| 2025-06-04T00:00:00 |
https://journalists.org/event/mini-lab-ai-for-freelancers/
|
[
{
"date": "2025/06/04",
"position": 59,
"query": "artificial intelligence journalism"
}
] |
|
Essex AI Policy Observatory for the World of Work
|
Essex AI Policy Observatory for the World of Work
|
https://www.essex.ac.uk
|
[] |
In response to the development, and surrounding regulation, of AI, there are emerging forms of governance at the social level across jurisdictions. Unions are ...
|
Artificial intelligence (AI) technologies are being used to manage, augment, or otherwise transform work. AI and algorithmic data driven systems are expected to help firms improve productivity and profitability, but they may also impact the world of work significantly.
The Essex AI Policy Observatory for the World of Work (E-AIPOWW) is the first Observatory highlighting how AI regulation, development and governance are occurring across the world, and what this is beginning to mean, and will mean for the world of work, and workers’ experiences.
From 2022, we have been researching regulation, development and governance surrounding AI in 6 jurisdictions. Our jurisdiction cases and Global AI Tracker for the World of Work are important instruments to aid governments, worker representatives, companies, and policymakers to identify up-to-date information about how AI is transforming, and will further transform, the world of work.
In response to the widespread and burgeoning deployment of AI across the world, governments are pursuing policy programmes to regulate how AI is introduced and integrated into societies. Various regulation approaches are emerging across the Global South and Global North, where different jurisdictional priorities reflect the specific political economies, histories, and legal frameworks within which they operate.
Businesses have prioritised innovation and development of AI products and services, taking different angles as they attempt to keep abreast with global, regional, and local competition and trends. Some companies are developing codes of conduct to ensure the best implementation of AI augmented products and services into companies. Companies ideally are also ensuring good practice when trialling AI in their operations management systems and/or when they are asking workers to integrate new tools with AI augmentation. Simultaneously, policymakers have pursued specific strategies to propel development of AI and a range of hoped benefits for their countries’/regions’ success in this space. Some areas are considering or are beginning to apply a ‘sandbox’ approach, where products must be tested as another feature of development, before being allowed onto the market.
Civil society, including trade unions, are now beginning to realise how important it will be to consider the likely impact that the development of AI will have for workers, and look for ways beyond hard law regulation, to protect workers from potential harms that AI may cause, via governance strategies. In response to the development, and surrounding regulation, of AI, there are emerging forms of governance at the social level across jurisdictions. Unions are actively lobbying and engaging in collective bargaining. Research organisations are producing impact assessment typologies for identifying best practices to protect the futures of work. Social dialogue is ideally part of the governance agendas for each jurisdiction.
E-AIPOWW is dedicated to rigorously documenting, and comparing the regulation, development and governance relating to AI that is now occurring in all parts of the world, to determine both what this currently means for, and will mean for, the world of work.
E-AIPOWW’s categories of analysis are as follows:
Regulation : Legal dimensions and regulatory advancements in hard and soft law, surrounding the advancement of AI in each jurisdiction.
: Legal dimensions and regulatory advancements in hard and soft law, surrounding the advancement of AI in each jurisdiction. Development : Innovation and promotion of AI by governments and the business community, competition and industrial policy, sandbox initiatives, and codes of conduct developed by business. This also involves government approaches to development and innovation of AI. The Sandbox approach is of interest here, where product and service testing has become ever more important given the rapid pace of this market and the potential risks and benefit for AI and the world of work.
: Innovation and promotion of AI by governments and the business community, competition and industrial policy, sandbox initiatives, and codes of conduct developed by business. This also involves government approaches to development and innovation of AI. The Sandbox approach is of interest here, where product and service testing has become ever more important given the rapid pace of this market and the potential risks and benefit for AI and the world of work. Governance : Jurisdiction-specific reforms, including education and institutional reframing, emerging industrial relations and work and employment responses (unions, works councils, institutional governing boards, etc.), civil society responses, and social dialogue.
: Jurisdiction-specific reforms, including education and institutional reframing, emerging industrial relations and work and employment responses (unions, works councils, institutional governing boards, etc.), civil society responses, and social dialogue. World of work: The world within which we work is shaped by a constellation of forces across industries and sectors, including working conditions evidenced, the kind of contracts available, the social protections (or lack thereof), and the myriad aspects of the employment relationship that need to be taken into account when considering the integration of AI to working environments.
E-AIPOWW is dedicated to the ILO’s Fundamental Principles for decent work, in looking at how regulation is forming, governance is emerging and development is approached, by a series of global players.
Each case study is oriented around these themes, so that we can, over time, make comparisons and good judgements concerning best practices in protections for the world of work.
| 2025-06-04T00:00:00 |
https://www.essex.ac.uk/research-projects/ai-policy-observatory-for-the-world-of-work
|
[
{
"date": "2025/06/04",
"position": 77,
"query": "artificial intelligence labor union"
}
] |
|
The Future of No Work: Master AI, Gain Superpowers, Earn ...
|
Amazon.com
|
https://www.amazon.com
|
[] |
Future of No work is a transformative guide on leveraging Artificial Intelligence (AI) and Robotic Process Automation (RPA) to revolutionize work routines. This ...
|
Click the button below to continue shopping
| 2025-06-04T00:00:00 |
https://www.amazon.com/Future-No-Work-Master-Superpowers-ebook/dp/B0CX1ZHYRN
|
[
{
"date": "2025/06/04",
"position": 78,
"query": "future of work AI"
}
] |
|
AI in the workplace: A reality check for HR
|
AI in the workplace: A reality check for HR
|
https://www.thepeoplespace.com
|
[
"Sian Harrington"
] |
A large-scale Danish study examining the real-world labour effects of generative AI found that while adoption is widespread, often employer-driven and ...
|
6 minute read
Siân Harrington offers a vital AI reality check for HR leaders, exploring how generative AI is reshaping work, trust and leadership – and why HR must lead the way
The AI wave has hit the workplace like a tidal surge, reshaping how we think, work and lead. For those of us in the HR and people space the stakes are high. At The People Space we've long championed technology that enables more human-centric work. But with generative AI rapidly moving from pilot to production, now is the moment to pause and ask: is AI really making work better? Or are we repeating the mistakes of the dot-com bubble?
For years I’ve described AI as a tool. Something we can use to enhance productivity, creativity and employee experience. But that framing is starting to feel inadequate. Increasingly, I’m drawn to a more profound interpretation, one that aligns with Stephen Klein’s recent call to action. Klein, CEO of Curiouser.AI, urges CEOs to stop treating AI as a project and instead see it as a new layer of organisational infrastructure. "GenAI is not a tool," he writes. "It’s a new layer of organisational infrastructure, reshaping how your company thinks and builds trust."
He’s right. And if that’s true, it changes everything for HR.
Beyond the pilot phase: Where HR needs to lead
The reality is that generative AI is now being embedded across organisations, often without adequate involvement from the people function. Deloitte's State of Generative AI in the Enterprise survey last year revealed that 79% of respondents expected GenAI to drive substantial organisational transformation within three years. But only 25% of leaders believed their organisations were highly prepared to address governance and risk issues related to Gen AI adoption.
It’s end of year report found the majority of respondents (55%–70%, depending on the challenge) believe their organisations will need at least 12 months to resolve adoption challenges such as governance, training, talent, building trust and addressing data issues.
HR should be at the centre of this transformation, not as an implementer of AI tools but as a strategic partner shaping how AI is used to build capability, preserve trust and reimagine work. If AI is the new operating layer then HR must define the principles on which that layer is built.
The Workday lawsuit: A warning shot
One only needs to look at the class-action lawsuit against Workday to understand what’s at stake. Derek Mobley, a Black man over 40 who self-identifies with anxiety and depression, alleges that Workday’s AI-powered screening tools led to more than 100 job rejections, violating civil rights and disability laws. On 16 May 2025 the case was greenlit as a nationwide class action in the US. It could set a precedent for how liability is assigned when AI systems result in discriminatory hiring outcomes.
Mobley alleges he was repeatedly rejected for roles, often without being invited to interview, despite holding nearly a decade of experience across finance, IT and customer service. In one instance detailed in court documents he applied for a position at 12:55 am and received a rejection less than an hour later, at 1:50 am.
Whether or not the claims are upheld the message is that AI systems in HR are not neutral. They carry the biases of their training data and the blind spots of their creators. Deploying them without scrutiny risks real harm to people and real consequences for employers.
HR leaders have a responsibility to ensure that any technology used in talent processes is fair, transparent and explainable. That includes demanding audits of AI systems, creating cross-functional ethics panels and putting employee safeguards in place.
Moderna’s merger: A structural signal
Contrast this with Moderna, the biotech company best known for its COVID-19 vaccine. Last year Moderna made headlines by merging its HR and IT functions into a new division led by chief people and digital officer Tracey Franklin. The rationale? AI was blurring the lines between digital infrastructure and people operations.
Moderna is now developing thousands of custom AI agents in partnership with OpenAI, including those supporting learning and development, employee communications and workflow automation.
According to Franklin Moderna is redesigning teams across the business by asking a fundamental question: what work is best done by people and what can be automated through technology? The company’s partnership with OpenAI is central to this process, enabling both augmentation and automation at scale. Roles are being created, eliminated and reimagined as a result. It’s not just about improving efficiency but about rethinking the very architecture of work. By bringing HR and IT together the company is ensuring that its AI strategy is people-aware from the start.
It’s a model worth watching. Not every company needs to restructure but every HR team needs a seat at the AI table.
Beyond the hype: A more grounded view of AI
We’ve all seen the breathless headlines: “AI will replace 300 million jobs.” "AI can outperform humans in 80% of tasks." They grab attention but they often distort reality.
To truly understand what AI means for work we need to get clear on what it actually is. What we call “AI” today, including generative tools like ChatGPT, Claude and Gemini, are not intelligent agents in the human sense. They don’t think, reason or decide. They don’t understand goals, context or consequence.
Instead, they are powerful statistical models that generate outputs by estimating the most probable next item in a sequence based on patterns in their training data – basically what they have seen before. In other words, they complete patterns. They don’t predict outcomes in the human sense. And they certainly don’t act with intent.
This distinction matters deeply in the workplace, where context, judgment and accountability can’t be reduced to probability.
According to a new working paper from the International Labour Organization (ILO), published in May 2025, 24% of all employment worldwide sits within occupations now considered exposed to GenAI to some degree. Just 3.3% of jobs fall into the highest exposure category, those where most tasks could feasibly be handled by GenAI without human input.
The ILO also highlights real barriers to adoption, from low digital skills among both workers and managers to organisational cultures still resistant to automation.
A growing body of research reinforces this need for realism. A large-scale Danish study examining the real-world labour effects of generative AI found that while adoption is widespread, often employer-driven and accompanied by training, the actual impact on wages or working hours across 11 occupations highly exposed to automation was minimal. Productivity gains were modest (just 2.8–3%) and in 8.4% of cases AI created new tasks, such as reviewing machine-generated output, rather than removing work.
Meanwhile, much of the buzz around so-called ‘agentic AI’ – systems of multiple AI agents working together – is still theoretical according to a paper by Cornell University. While these architectures promise collaboration and complexity-handling at scale, they introduce major challenges: coordination errors, security risks and system instability. The projected market growth is exponential but real-world deployment remains rare.
For HR professionals the message is that we cannot adopt AI blindly. It starts with investing in employee literacy, embedding ethical guardrails and ensuring that any experimentation is transparent, inclusive and intentional. That means clearly explaining where AI is used, involving employees in the design of AI-enabled systems and creating safe spaces for feedback and course correction.
The human role in an AI world
There’s no doubt that AI can deliver real value, particularly in automating routine, admin-heavy tasks and surfacing useful patterns in large datasets. But it’s essential we use it to augment, not override, human judgment.
Generative AI doesn’t understand the world. It produces statistically plausible outputs – fluent, fast and sometimes useful – but without context or comprehension. It can simulate empathy in language but it doesn’t feel. It can offer recommendations but it doesn’t reason.
And that distinction matters deeply in HR. When you’re deciding who to hire, promote or redeploy, data can support the process but context is critical. When coaching a leader or supporting a team in conflict the subtleties of tone, trust and history simply can’t be outsourced to an algorithm.
This is where HR’s value will remain uniquely human: in the spaces where understanding matters more than prediction.
From tool to infrastructure: What this means for HR
It’s tempting to frame AI purely in terms of efficiency gains – and yes, when thoughtfully applied, it can reduce admin, speed up processes and create breathing space for deeper work. That’s valuable. But the real opportunity is bigger.
AI isn’t just another tool in the HR tech stack. As Klein argues it’s becoming a foundational layer in how organisations operate and make decisions. That shift demands a rethinking of roles, responsibilities and relationships, not a spreadsheet exercise to cut headcount.
Using AI to cut costs by removing people may deliver short-term gains. But using it to free people up – to focus on judgment, creativity and culture – is how organisations build resilience and long-term value.
Companies that have framed AI purely as a cost-cutting exercise are learning this the hard way. Klarna, for example, replaced 700 customer service staff with AI to cut costs during a downturn only to backtrack months later when service quality dipped and customer dissatisfaction grew. “It’s critical that customers know there will always be a human if you want,” CEO Sebastian Siemiatkowski later admitted.
IBM experienced a similar backlash. After laying off thousands of HR employees and replacing them with its AI platform AskHR, the company found that tasks requiring human nuance and judgment were falling through the cracks. The result? Rehiring.
These examples show that AI-led transformation without people-led strategy risks unintended consequences and short-lived savings.
As Stephen Klein reminds us the real question isn’t whether a company is “using AI” but what is the work we’re hiring this technology to do?
Right now, too many companies are launching AI pilots with the wrong objectives: speed, savings, optics. The result? Failed integrations, burned budgets and disappointed teams. The organisations that thrive will be the ones whose leaders, including HR, ask better questions: Where do we create value? What do we want to stand for? How can AI help us serve that mission better, not just faster?
Ultimately AI exposes more than our digital maturity. It reveals our leadership maturity.
So what should HR do now?
Here’s what we at The People Space believe HR leaders should focus on right now:
Claim your strategic seat. If AI is being discussed at your board or exec table and HR isn’t there, that’s a red flag. Make the case for your inclusion. This is about workforce impact, culture, capability and compliance – all HR domains. Create AI principles. Don’t wait for a policy. Convene a cross-functional group to develop your own organisational AI principles. Focus on transparency, fairness, explainability and inclusion. Upskill – now. There are new capabilities HR needs to lead in this era. Invest in your own development and support your team to do the same. Be the conscience. If AI deployment risks harming employees, degrading trust or undermining culture, say so. Raise the flag. Offer alternatives. Be brave. Start small, learn fast. Pilot AI tools in low-risk areas, with clear success criteria and feedback loops. Share what works and what doesn’t. Normalise experimentation, not perfection.
Our promise: No hype. Just work.
Since we launched in 2017 The People Space has been a space for thoughtful, future-focused perspectives on work and technology. We’ve championed the promise of AI while staying grounded in the lived experience of people leaders.
In the months ahead we’ll continue to cover AI at work but we make this promise to you: no hype, no doom. Just smart and, where possible, evidence-based insight on what this technology means for real organisations and real people.
The future of work isn’t a product but a practice. And we believe HR has a critical role in shaping it for the better.
| 2025-06-04T00:00:00 |
https://www.thepeoplespace.com/ideas/articles/ai-workplace-reality-check-hr
|
[
{
"date": "2025/06/04",
"position": 89,
"query": "workplace AI adoption"
}
] |
|
Company boards push CEOs to replace IT workers with AI - CIO
|
Company boards push CEOs to replace IT workers with AI
|
https://www.cio.com
|
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Many boards of directors are now pushing CEOs to cut 20% of workforce costs, with the expectation that AI will take over the eliminated jobs.
|
A huge wave of IT layoffs — with more than 238,000 jobs lost in 2024 and another 76,000 so far in 2025 — isn’t likely to die down soon, as organizations brace for a potential recession and look for huge workforce cuts through the use of AI.
While many AI evangelists have played down the potential for the technology to replace human workers, that message hasn’t resonated in board rooms, as company leaders look to reinvent their business operations, IT hiring experts say.
Many boards of directors are now pushing CEOs to cut 20% of workforce costs, with the expectation that AI will take over the eliminated jobs, says Camille Fetter, CEO at Talentfoot Executive Search & Staffing.
| 2025-06-05T00:00:00 |
https://www.cio.com/article/4000546/company-boards-push-ceos-to-replace-it-workers-with-ai.html
|
[
{
"date": "2025/06/05",
"position": 25,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/05",
"position": 63,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 64,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 43,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 43,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 66,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 25,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/05",
"position": 42,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 9,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/05",
"position": 45,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 74,
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},
{
"date": "2025/06/05",
"position": 25,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/05",
"position": 29,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 31,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/05",
"position": 73,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 43,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 70,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 71,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 42,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 76,
"query": "AI replacing workers"
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{
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{
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{
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{
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{
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{
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{
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{
"date": "2025/06/05",
"position": 23,
"query": "artificial intelligence layoffs"
},
{
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"position": 40,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 70,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 29,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 72,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 23,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/05",
"position": 28,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 72,
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{
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"position": 29,
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},
{
"date": "2025/06/05",
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"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/05",
"position": 71,
"query": "AI replacing workers"
},
{
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"position": 68,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 27,
"query": "AI layoffs"
},
{
"date": "2025/06/05",
"position": 57,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 67,
"query": "AI replacing workers"
},
{
"date": "2025/06/05",
"position": 18,
"query": "AI layoffs"
}
] |
|
Corporate layoffs: Here are the companies making job cuts - CNBC
|
Corporate layoffs have ramped up in recent weeks. Here are the companies making cuts
|
https://www.cnbc.com
|
[
"Ali Mccadden",
"In Ali-Mccadden"
] |
Many companies lumped layoffs in with larger cost-cutting strategies. Some have cited artificial intelligence as a factor in layoffs.
|
In this article DIS
WMT
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MSFT
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Mathisworks | Digitalvision Vectors | Getty Images
While the government cost-cutting initiative known as the Department of Government Efficiency, which resulted in thousands of federal job cuts, winds down, mass layoffs are still roiling corporate America. Companies are under increasing pressure to trim costs against the backdrop of global economic uncertainty brought on by President Donald Trump's tariff policies. Several companies have announced price hikes. Layoffs mark another way to pull back. Trade tensions have also raised concerns about the general health of the U.S. economy and the job market. While the April jobs reading was better than expected, a separate reading from ADP this week showed private-sector hiring hit its lowest level in more than two years. Though many companies declined to provide specific reasoning for announced workforce reductions — instead lumping the layoffs in with larger cost-cutting strategies or growth plans — tech leaders are starting to cite artificial intelligence as a clear consideration in hiring and head-count reductions. Klarna CEO Sebastian Siemiatkowski told CNBC on May 14 the fintech company has shrunk its head count by 40%, in part due to investments in AI. Likewise, Shopify CEO Tobias Lütke told employees in April that they will have to prove why tasks can't be performed by AI before asking for more workers and resources. Here are some of the companies that have announced layoffs in recent weeks:
Procter & Gamble
Pampers and Tide maker Procter & Gamble said Thursday it will cut 7,000 jobs, or about 15% of its non-manufacturing workforce, over the next two years as part of a restructuring program. CFO Andre Schulten said during a presentation that the company is planning a broader effort to implement changes across the company's portfolio, supply chain and corporate organization. The company did not specify the regions or divisions that would be affected.
Microsoft
Microsoft said on May 13 that it would reduce its workforce by about 6,000 staffers, totaling about 3% of employees across all teams, levels and geographies. A Microsoft spokesperson told CNBC at the time that one objective of the cuts was to reduce layers of management. The company announced a smaller round of layoffs in January that it said were performance-based. The spokesperson said the May cuts were not related to performance.
Citigroup
People walk by a Citibank location in Manhattan, New York City, on March 1, 2024. Spencer Platt | Getty Images
Citigroup said in a statement Thursday it plans to reduce its staff by around 3,500 positions in China. The cuts mostly affect the information technology services unit, which provides software development, testing and maintenance. Some of the affected roles will be moved to Citi's technology centers elsewhere, the bank said. Under the leadership of CEO Jane Fraser, Citi has undertaken a large-scale reorganization with an eye toward profitability and stock performance. The bank consistently underperformed its major bank peers in recent years. Citi announced a broader plan in 2024 to reduce its workforce by 10%, or about 20,000 employees globally.
Walmart
On May 21, Reuters reported that Walmart was planning to slash about 1,500 jobs in an effort to simplify operations. The teams affected include global technology, operations and U.S.-based e-commerce fulfillment as well as Walmart Connect, the company's advertising business. Walmart employs around 1.6 million workers, making it the largest U.S. private employer. CFO John David Rainey told CNBC during an interview May 15 that Walmart shoppers would likely see price increases at the start of the summer in response to tariffs.
Klarna
Siemiatkowski said in May that the 40% cut in head count is due not only to AI but also to attrition, after the company instituted a hiring freeze. The Swedish provider of buy now, pay later loans has been outspoken about its aggressive adoption of AI tools across the company, particularly in the customer service unit. The company said last year that AI was doing the work of 700 customer service agents.
CrowdStrike
Cybersecurity software maker CrowdStrike on May 7 announced plans to cut 500 employees, or about 5% of its staff. CEO George Kurtz in a securities filing attributed the move largely to artificial intelligence. "We're operating in a market and technology inflection point, with AI reshaping every industry, accelerating threats, and evolving customer needs," he said, adding that the move was part of the company's "evolving operating model."
Disney
A water tower stands at Walt Disney Studios on June 3, 2025 in Burbank, California. Mario Tama | Getty Images
The Walt Disney Company said Monday it plans to cut several hundred employees worldwide across several divisions. The layoffs affect teams in film and TV marketing, TV publicity and casting and development. The cuts are part of a larger effort to operate more efficiently, a Disney spokesperson said.
Chegg
Online education firm Chegg said on May 12 that it would lay off 248 employees, or about 22% of its workforce. The cuts come as AI-powered tools such as OpenAI's ChatGPT take over education. CEO Nathan Schultz said on the company's May earnings call that the layoffs are part of a cost reduction plan and he expects cost savings of between $45 million and $55 million this year, followed by a further $100 million to $110 million next year.
Amazon
Amazon said in May it would eliminate about 100 jobs in its devices and services division, which includes the Alexa voice assistant, Echo hardware, Ring doorbells and Zoox robotaxis. A spokesperson for Amazon told CNBC at the time the decision was part of an ongoing effort to "make our teams and programs operate more efficiently." The cuts come as CEO Andy Jassy has sought out cost-trimming efforts at the company. Since the beginning of 2022, Amazon has laid off roughly 27,000 employees.
Warner Bros. Discovery
| 2025-06-05T00:00:00 |
2025/06/05
|
https://www.cnbc.com/2025/06/05/corporate-layoffs-companies-making-job-cuts.html
|
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How AI Is Transforming Medicine and Patient Care - US News Health
|
The Promise and Challenges of AI in Medicine
|
https://health.usnews.com
|
[
"Cheyenne Buckingham",
"Gretel Schueller",
"June",
"At P.M."
] |
Artificial intelligence (AI) is transforming medicine in several ways, including faster and more accurate diagnosis and prognosis of various ...
|
Key Takeaways
Artificial intelligence (AI) is transforming medicine in several ways, including faster and more accurate diagnosis and prognosis of various cancers and other health conditions, improved treatment and care delivery, and streamlining the patient experience.
Machine learning can analyze large datasets, allowing researchers to study patient outcomes and accelerate traditional research methods, such as clinical trials. AI can also help personalize treatment plans, for example, by analyzing electronic medical records data to identify patterns related to patient responses to different medications.
While AI promises many benefits, it's important to be aware of potential concerns, such as medical errors, bias and data accuracy, and data and patient privacy.
Artificial intelligence, or AI, is a contentious topic in today’s world, but both health care professionals and researchers are enthusiastic about its potential to revolutionize patient care – from diagnosis and treatment to how doctors correspond with their patients.
While recent advancements have catapulted AI into the spotlight, the technology isn’t by any means new. It’s been around for more than 70 years, with its first medical applications emerging in the 1970s. Since then, the technology has helped doctors diagnose conditions and identify appropriate treatments. It’s also assisted radiologists in interpreting microscopic abnormalities on imaging scans, including mammograms and other routine cancer screenings.
Fast forward to now: AI is more sophisticated than ever before, and it will only continue to become more knowledgeable. Just recently, the first AI-designed drug, Rentosertib, made its way through several clinical trials, showing promise as an effective treatment for idiopathic pulmonary fibrosis (IPF), a chronic, progressive lung disease that makes it challenging to breathe.
AI also assists scientists with drug repurposing, or identifying which readily available medications can be used, alone or in combination with others, to treat rare diseases, including certain cancers and neurological conditions. In radiology, AI offers radiologists a second set of eyes that surpass human capabilities.
Yet despite the technology’s impressive prospects, AI – much like humans – can make mistakes, which is why it’s best used (for now) as a collaborative tool for physicians and researchers. In other words, providers and scientists alike still need to keep a careful eye on its decision-making abilities.
How Is AI Used in Medicine?
The use cases for AI in medicine are rapidly expanding. In fact, your doctor likely uses AI during your office visits.
Administrative tasks
“One area that has made a big difference in patient care is ambient documentation, in which AI listens to a conversation between the doctor and the patient and produces notes in real time,” says Dr. David Westfall Bates, who’s the co-director of the Center for Artificial Intelligence and Bioinformatics and the Learning Healthcare System at Mass General Brigham.
In some instances, the physician can have key takeaways from the appointment and next steps drafted and ready to send by the end of the visit.
“AI scribes provide some immediate quick wins, from an organizational perspective, and also decrease the epidemic of clinician burnout that we're seeing today,” says Brenton Hill, head of operations and general counsel for the Coalition for Health AI (CHAI).
Data suggest that tools like these can reduce a physician’s time spent documenting a patient’s electronic health record (EHR) by as much as 16%. That said, AI scribes can record notes incorrectly sometimes, which is why the physician needs to review the script before logging it into the patient’s medical records or sending follow-up notes via the patient portal.
AI can also be used to generate letters and scripts for insurance companies, Bates says. Essentially, AI can help physicians execute the administrative elements of their job in a more timely and efficient manner.
Disease detection and diagnosis
AI offers clinical support by aiding in diagnosis. It analyzes patterns in patient data and presents them to health care professionals to help guide informed decisions.
“AI algorithms are being tested for their ability to consolidate and analyze a variety of patients’ data, such as medical histories, lab and imaging results, and genetic information, to predict when disease might arise,” says Dr. Andrew Hantel, a health services researcher, hematologic oncologist and ethics consultant at Dana-Farber Cancer Institute and Harvard Medical School. “AI can enhance interpretation of images used in diagnosis or treatment. When used by trained physicians, AI tools can improve the speed and accuracy of some diagnoses.”
For example, tools like Google’s DeepMind have successfully identified breast cancer in mammograms, says Thomas Swalla, CEO of Dotmatics, a software company that connects science, data and decision-making.
According to a study published in a 2020 issue of Nature, Google’s DeepMind AI system outperformed six human radiologists when it came to identifying breast cancer on the screen. This suggests that the tool can be used to help reduce false negatives and false positives.
Bates adds that AI is particularly strong at reading pathology slides, which are tiny pieces of tissue placed on glass for doctors to examine under a microscope and check for signs of disease.
"This is the way most cases of cancer are diagnosed," notes Bates.
Personalized treatments
“AI will be used a lot in the future, I believe, to personalize treatments for patients,” Bates says.
When treating a specific condition, such as hypertension, a doctor will likely start you on a medication that most people respond well to. But each person has their own unique genetic makeup, meaning how you fare on a medication could be vastly different from another person.
Using AI to make personalized treatment recommendations based on a patient’s genome can help physicians make better choices for patients, potentially saving them the distress of having to rule out multiple medications or therapies through trial and error.
“AI algorithms have the potential to help synthesize different data sources to recommend treatments that account for genetic data, co-occurring conditions and estimated risk,” Hantel says.
These algorithms are still in the testing phase, so they aren’t widely used yet in the clinical setting.
Robotics
Robots can assist physicians in a variety of ways. For example, AI-powered robots are currently being tested for use in surgery to enhance precision and reduce the need for invasive procedures when possible.
"Robotics can also help surgeons better assess their operations in real time,” Hantel says.
Robotics can also be employed to help with logging notes in the patient portal, cleaning hospital rooms and examining images such as MRIs and X-rays.
Drug development
AI is helping design life-saving drugs, such as Rentosertib.
“AI-based algorithms are being used to predict the structure of different human proteins and how they interact with a variety of chemical compounds to identify promising candidates, reduce research costs and shorten the time to clinical trials,” Hantel says.
At Dotmatics, Swalla is seeing AI accelerate early-stage drug discovery by modeling and predicting how molecules will behave before they’re synthesized in the lab. “Scientific intelligence platforms, like our own Dotmatics Luma, enable scientists to simulate, iterate and analyze compound designs faster and more intelligently, reducing both time and cost across the design-make-test-decide cycle.”
Benefits of AI for Doctors and Patients
The benefits for doctors and patients are endless. Currently, many patients are having their clinical notes created with AI using “ambient documentation;” the AI listens to the interaction and generates a note, which the doctor edits.
Perhaps most important: AI can help physicians support their patients better. When AI becomes intelligent enough to safely make suggestions on which medications people may respond best to, it can save both the doctor and patient time and money.
“This can help us pick the drug that has the best chance of working for you as an individual,” Bates says. “We don't do things that way right now.”
Doctors often don’t have the time or resources to handle every task expected of them for each patient. One 2022 study found that primary care physicians would need 26.7 hours a day to provide all guideline-recommended care to each patient.
Human error is inevitable, especially when health professionals are working past capacity. Think of AI as the med student that never sleeps. Combine the power of human reasoning with the power of AI and together, they form a duo that creates fewer errors, Hill says.
Another boon to AI-supported healthcare? Those living in underserved areas can have access to best-in-class care. According to a Pew Research Center survey, nearly a quarter of respondents living in rural areas said they didn’t have easy access to good doctors and hospitals.
At CHAI, Hill says patient advocacy communities are reporting that they’re interested in collaborating with AI developers to use tools like large language models to improve access to health care, especially in rural areas. In the future, AI tools could help by answering medical questions, offering credible health information and helping patients decide when it’s necessary to seek care. For example, AI may eventually be able to help someone determine if it’s imperative to make the trek to an emergency room.
When it comes to chronic disease management, AI tools can be an invaluable resource. Apps can help patients log their symptoms and make real-time dietary recommendations to help them manage their health.
“AI can also aid in how medical information is conveyed to patients, especially those with lower health literacy or speak languages that are different from the one their care team uses,” Hantel says.
In addition, wearable devices that use AI can continuously monitor data and flag health risks earlier, Hantel says, helping a patient get ahead of serious symptoms or complications.
The Limitations of AI in Medicine
While AI has demonstrated immense promise for improving care, it comes with its own set of drawbacks and challenges. The biggest barrier right now is the amount of training needed to get AI tools up to speed so that they can deliver reputable and safe advice to patients.
“There’s a large gap of data that's made available for these developers to train on,” Hill says. Patient data protection laws, such as the Health Insurance Portability and Accountability Act (HIPAA), inhibit developers from training their algorithms on patient medical records.
In addition, hospitals and clinics in rural areas are often less likely to provide data to developers, Hill says. This means AI tools may not work well for populations they haven’t been trained on, making them less accurate or useful in those settings.
“AI models require large, high-quality datasets, but medical data is inconsistent, incomplete and fragmented across systems,” Hantel says.
Plus, training and distributing AI models nationwide is costly, which can raise the risk of widening existing health disparities. “Building and deploying AI systems is expensive and time-consuming, so smaller practices and resource-limited settings won’t get AI tools as quickly or broadly,” Hantel notes.
AI, as of right now, isn’t immune to biases. Bates brought up a real-life example of an AI scheduling tool for chronic disease patients that predicted Black and Hispanic patients would have higher no-show rates. Based on this data, the algorithm recommended overbooking these groups of people, leading to patients spending an inordinate amount of time in the waiting room even though they had an appointment that day.
From the patient's point of view, there are concerns around data privacy.
“Increased reliance on digital data and cloud-based AI systems raises concerns about data breaches and confidentiality,” Hantel says.
The Future for AI in Medicine
AI will likely always require humans to monitor its decisions and processes. The hope for this sophisticated technology is that, one day soon, it will elevate patient care, enhance research for drug development, educate physicians and streamline administrative tasks.
“However, this needs to be done in a way that is intentionally inclusive so that AI does not worsen pre-existing biases and injustice in how medicine is practiced,” Hantel says. Right now, the cost of implementing AI systems into hospitals and doctors' offices will likely exclude many facilities.
There may also need to be regulations on how heavily physicians rely on AI, as overdependence could diminish their clinical skills.
There must be checks and balances in play so that AI can’t dehumanize care or use patient and hospital data for profit rather than health as the ultimate goal, Hantel suggests.
| 2025-06-05T00:00:00 |
https://health.usnews.com/wellness/articles/how-ai-is-transforming-medicine-and-patient-care
|
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|
Tech job openings vanish as AI, tariffs change hiring landscape
|
Tech job openings vanish as AI, tariffs change hiring landscape
|
https://www.usatoday.com
|
[] |
Since mid-2023, 12% of the rise in the nation's unemployment rate from 3.6% to 4.2% can be traced to the struggles of recent college graduates, ...
|
Don’t blame a job market slowdown that many economists say will start to become evident in the June 6 employment report for May solely on uncertainty surrounding President Donald Trump’s tariffs.
You can also point the finger at AI.
AI, or artificial intelligence, is increasingly prompting technology companies to hire fewer recent college graduates and lay off more employees, according to economists and staffing firms.
The rising U.S. unemployment rate the past couple of years can partly be pinned on a hiring slowdown in technology that has largely affected recent college grads seeking the kind of entry-level jobs being replaced by AI, according to a report by Oxford Economics.
Trump’s tariffs, which are expected to reignite inflation while dampening consumer spending, probably will intensify the hiring pullback, said Oxford senior economist Matthew Martin.
“Clearly, something is shifting,” Martin said. “Entry-level jobs have declined markedly.”
What is the job market like right now?
The Labor Department is expected to report U.S. employers added 125,000 jobs in May, down from an average of 181,000 the past two months, according to economists surveyed by Bloomberg. The unemployment rate is projected to hold steady at a historically low 4.2%.
Job growth has slowed gradually the past couple of years as a post-pandemic burst of demand faded even while companies remain saddled with high labor costs and interest rates, squeezing their profits. Trump’s tariffs are generating fresh uncertainty forecasters say will further curtail job growth in coming months.
But Martin said there also should be some focus on a deeper shift in hiring patterns that has played out the past couple of years and is gathering force.
What is the unemployment rate for recent college graduates?
From April 2022 to March 2025, the unemployment rate for recent college grads – ages 22 to 27 – shot up from 3.9% to 5.8%, while the jobless rate for all workers climbed from 3.7% to 4%, according to the Federal Reserve Bank of New York. That means unemployment for recent grads is now higher than it is for all workers, reversing a decadeslong trend.
The jobless rate for all college grads – 2.7% in March – is still lower than the overall unemployment rate.
But many entry-level tech jobs are disappearing, the Oxford study says. Among industries, professional, scientific and technical services has had the biggest increase in employment among recent grads over the past two decades, largely in computer services. But since 2022, IT employment among those ages 22 to 27 has declined by 8% compared with a 0.8% rise for college grads older than 27, the Oxford report suggests. Payrolls have risen 2% for college grads in all other occupations.
Job openings in professional and business services, the broader sector that includes computer positions, have declined by about 1 million to 1.5 million over the past two years, Labor Department figures show.
The trend is moving the needle on the job market broadly. Since mid-2023, 12% of the rise in the nation's unemployment rate from 3.6% to 4.2% can be traced to the struggles of recent college graduates, according to the Oxford analysis.
Are tech jobs still in high demand?
Many tech companies, as well as the IT divisions of firms in various industries, are hiring about half the software developers they used to, said Kye Mitchell, head of Experis U.S., the tech hiring arm of staffing giant ManpowerGroup.
Instead, AI in many cases is handling basic software development tasks while data architects and scientists, along with AI coaches, are setting up the data and teaching the AI how to manipulate it, Mitchell said. Though many developers are being retrained for these higher-level roles, the shift is leading to fewer entry-level jobs in the short term and fewer opportunities for recent graduates.
The companies’ wary approach toward hiring and desire to increase cost efficiency through AI has been amplified by the uncertainty spawned by the trade war, she said.
“People are cautious,” she said. “AI is making it tougher for recent college grads.”
Mitchell advised IT majors to take classes in more analytical specialties to increase their odds of landing a position.
“If you’re more of a generalist, you’re in trouble,” she said.
Are tech companies laying off employees?
Meanwhile, some large tech companies have laid off workers who performed administrative, customer service and data entry tasks, Mitchell said, replacing them with AI. In May, Microsoft announced 6,000 layoffs globally, and company CEO Satya Nadella has said about 30% of the company’s code is now written by AI.
Other companies, including Google and Salesforce, have announced layoffs at the same time they revealed heavy AI rollouts, according to tech.co, a technology news site.
Traditionally, new technology that wipes out some jobs ultimately increases productivity and growth, creating new positions that eventually offset the losses.
But, Mitchell said, "people are really unsure. ... We've never been in this age" of rapid AI advances.
By 2030, activities that make up as much as 30% of hours now worked in the United States could be automated − a trend accelerated by AI, according to a McKinsey GLobal Institute report.
| 2025-06-05T00:00:00 |
2025/06/05
|
https://www.usatoday.com/story/money/2025/06/05/ai-replacing-tech-jobs/84016842007/
|
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AI and the Future of Work | IBM
|
AI and the future of work
|
https://www.ibm.com
|
[] |
From a talent management perspective, AI technologies have proven adept at helping HR departments identify which skills their workers might need ...
|
But given the rapid rise of AI, some business leaders are struggling to adapt. For instance, a recent survey from the IBM Institute for Business Value found that most executives expect AI to change core aspects of their businesses. But half said that their organizations had disconnected technologies given the pace of recent investments, preventing them from unlocking the true value of AI tools. And workplace culture significantly impacts adoption: More than half of CEOs believe that culture change is more important than overcoming technical challenges during a data transformation.
Regardless of how AI-ready business leaders are, these technologies are widely expected to reframe the global labor market. According to the management consultancy McKinsey, up to 30% of hours worked across the US economy could be automated by 2030, with 12 million occupational transitions required by the same year. And, as the World Economic Forum estimates, while over the next few years there might be 85 million job losses across the globe, new technologies could create as many as 97 million new jobs. In short, the skills the average worker possesses will change dramatically over the next ten years.
To prepare for these shifts, proactive companies take a whole-system approach to embracing AI. According to another recent report from the IBM Institute for Business Value, organizations deploying AI at an operational, rather than skills-based, level outperformed their peers by 44% on critical metrics such as employee retention and revenue growth. And increasingly, business leaders are focusing on designing new talent management and training paradigms to foster agile, AI-ready workers.
In the midst of such a fundamental change, stakeholders should approach the current moment as an opportunity to enhance human potential and create resilient systems. Preparing for the future of AI requires careful strategic planning and fostering an organizational culture of change.
| 2025-06-05T00:00:00 |
https://www.ibm.com/think/insights/ai-and-the-future-of-work
|
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"date": "2025/06/05",
"position": 9,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/05",
"position": 9,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/05",
"position": 26,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/05",
"position": 8,
"query": "future of work AI"
},
{
"date": "2025/06/05",
"position": 7,
"query": "future of work AI"
},
{
"date": "2025/06/05",
"position": 7,
"query": "future of work AI"
},
{
"date": "2025/06/05",
"position": 11,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/05",
"position": 7,
"query": "future of work AI"
},
{
"date": "2025/06/05",
"position": 9,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/05",
"position": 7,
"query": "future of work AI"
},
{
"date": "2025/06/05",
"position": 3,
"query": "future of work AI"
},
{
"date": "2025/06/05",
"position": 8,
"query": "AI labor market trends"
},
{
"date": "2025/06/05",
"position": 52,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/05",
"position": 13,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/05",
"position": 1,
"query": "future of work AI"
},
{
"date": "2025/06/05",
"position": 7,
"query": "machine learning workforce"
},
{
"date": "2025/06/05",
"position": 7,
"query": "workplace AI adoption"
}
] |
|
Anthropic researchers predict a 'pretty terrible decade' for humans ...
|
Anthropic researchers predict a ‘pretty terrible decade’ for humans as AI could wipe out white collar jobs
|
https://fortune.com
|
[
"Beatrice Nolan"
] |
Nvidia's Jensen Huang has also said “every job” will be affected by AI, but predicted that workers would be more likely to lose their jobs to an ...
|
Humans may be in for a “pretty terrible decade” as AI automates more white-collar work while progress in robotics lags behind, according to Anthropic researchers.
Speaking to AI podcaster Dwarkesh Patel, Anthropic’s Sholto Douglas said he predicted there would be a “drop in white-collar workers” over the next two to five years, even if current AI progress stalls.
“There is this whole spectrum of crazy futures. But the one that I feel we’re almost guaranteed to get—this is a strong statement to make—is one where, at the very least, you get a drop in white-collar workers at some point in the next five years,” he said. “I think it’s very likely in two, but it seems almost overdetermined in five.”
“The current suite of algorithms is sufficient to automate white-collar work provided you have enough of the right kinds of data,” he added.
Trenton Bricken, a member of the technical staff at Anthropic, seconded his fellow researcher’s point, saying: “We should expect to see them automated within the next five years.”
The discourse around AI job losses has been heating up recently, with some major tech figures acknowledging that the technology will have at least some effect on desk jobs.
In an interview with CNN’s Anderson Cooper last month, Anthropic CEO Dario Amodei predicted that within five years, AI could automate away up to 50% of all entry-level white-collar jobs.
Nvidia’s Jensen Huang has also said “every job” will be affected by AI, but predicted that workers would be more likely to lose their jobs to an AI-enhanced colleague rather than have it purely automated.
Companies like Shopify and Duolingo are already slashing hiring for roles AI can handle.
According to Revelio Labs data cited by Business Insider, there has also been a steep drop in job postings for high-exposure positions like IT and data analysis.
While some companies, like fintech Klarna, have walked back aggressive AI adoption due to quality concerns, most seem to be committed to using some form of AI to shrink white-collar workforces.
AI is already automating some work
AI is already proving it can handle coding and a wide range of desk jobs, raising the possibility of a future where machines do the thinking, and humans are left with the hands-on work.
Douglas said this scenario could lead to a “pretty terrible decade” before things start to improve for the better.
“Imagine a world where people have lost their jobs, and you haven’t yet got novel biological research. That means people’s quality of life isn’t dramatically better,” he said. “A decade or two after, the world is fantastic. Robotics is solved, and you get to radical abundance.”
Anthropic has recently unveiled its latest generation of cutting-edge AI models, Claude Opus 4 and Claude Sonnet 4.
The models represent a significant leap in AI’s coding ability, beating out Google and OpenAI’s most advanced offerings.
One early tester of Claude Opus 4 said the model “coded autonomously for nearly seven hours” after being deployed on a complex project.
| 2025-06-05T00:00:00 |
2025/06/05
|
https://fortune.com/2025/06/05/anthropic-ai-automate-jobs-pretty-terrible-decade/
|
[
{
"date": "2025/06/05",
"position": 48,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 68,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 63,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 94,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 81,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 86,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 64,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 84,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 85,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 95,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 87,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 97,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 65,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 65,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 83,
"query": "AI job losses"
},
{
"date": "2025/06/05",
"position": 63,
"query": "AI job losses"
}
] |
The unions are (finally) coming for big tech - LeadDev
|
The unions are (finally) coming for big tech
|
https://leaddev.com
|
[
"Kelli Korducki"
] |
The AI engineering curriculum ... This leaves workers with little recourse for labor violations, including illegal union retaliation from ...
|
You have 1 article left to read this month before you need to register a free LeadDev.com account.
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Estimated reading time: 5 minutes
Once thought of as a barrier to quick decisions and an unnecessary additive for a cushy sector, sweeping job insecurity and a burnout epidemic have turned the tide on unionization in tech.
At the end of May 2025, unionized quality assurance (QA) workers at the Microsoft-owned video game holding company ZeniMax announced a tentative contract agreement, marking Microsoft’s first-ever union contract in the US. It’s the latest wave in a sea change surrounding labor-union membership in tech – an industry that has historically been hostile to unions.
The shift is several years in the making. Since 2020, tech workers have formed unions at a diverse array of companies, including Alphabet, Glitch, Kickstarter, Medium, the New York Times, and, as of this spring, the Washington Post. On top of the ZeniMax QA workers, more than 2,000 Microsoft video game professionals now belong to the CWA union.
While tech’s strides toward unionization are significant, they are also relative. Overall, union participation has fallen sharply from one in three to less than one in ten among wealthy democracies over the last 70 years, particularly in the US.
Despite strong indications that pro-union sentiment is gaining momentum, US union membership dipped to a record low 9.9% in 2024, according to the Bureau of Labor Statistics. Within this already diminished framework, workers in technical and professional services accounted for only 1.2% of the unionized US-American workforce.
Though actual union membership numbers remain low, tech leaders tell LeadDev that they have witnessed a change in attitudes firsthand. Amid a volatile labor market and the ever-changing whims of bosses, more tech workers are receptive than ever to the potential benefits of collective action.
A shift in tides for the tech sector
Some say the tides have shifted quickly. Chandrakanth Puligundla, tech lead for data analysis, data engineering, and data governance at food and drug retailer Albertsons Companies, moved to the US from his native India shortly before beginning a computer science graduate program in January 2022. In just three and a half years, he says he has noticed “a significant shift” in the way tech workers in the USA view unions. “What was once considered incompatible with the ‘move fast’ ethos of tech is now being reevaluated in light of burnout, layoffs, and widening gaps between leadership decisions and worker needs,” Puligundla says.
Puligundla tells LeadDev that engineers – especially those in mid-career – used to dismiss unions as a hindrance to innovation. Now, the engineers he knows are much more likely to see unions “as a potential safeguard for fairness, transparency, and long-term sustainability in a volatile industry,” he says. “The recent waves of abrupt layoffs at otherwise profitable companies have only amplified that sentiment.”
Puligundla’s observation is somewhat supported by an August 2024 Blind survey of 1,900 verified tech employees, in which 67% of respondents said that they would be likely to join a union.
Joosep Seitam, the cofounder and CEO of the New York City e-commerce platform, Icecartel, echoes Puligundla’s view that a rising sense of insecurity is driving the change in perspective. When tech jobs were synonymous with sky-high salaries, unbeatable perks, and unparalleled work-life balance, it was easy to dismiss unions as irrelevant. But now, those days can seem like a distant memory.
“A lot of young developers, designers, and engineers are looking at unions as a way to fight burnout. Workers are no longer shy about questioning their bosses on job security, fair wages, and work-life balance,” Seitam says.
Kyle Sobko, the CEO of medical equipment company SonderCare based in London, Ontario, speaks from the perspective of both an entrepreneur and a personnel director for tech teams. He tells LeadDev that he has not only witnessed attitudes shift among his tech teams but has had a similar change of heart himself.
“In my earlier years, I viewed unionization as a barrier to quick decisions,” Sobko says. “My opinion changed over time, sometimes because I had staff bring up their own conversations about burnout and pay equity, and these moments helped me recognize that organized labor can provide real representation when others fall silent.”
Tech unions have a challenging road ahead
Despite some notable wins, tech unions continue to face an uphill trek.
Powerful CEOs have repeatedly shown they are unafraid to test the limits of union busting. Among others, the NYT has been found to pressure workers to side against their union, next to organizations like Apple, which have threatened retaliation against those considering unionization.
Some companies have gone so far as to take illegal action against their workers over union activity. In recent years, the National Labor Relations Board (NLRB) – the US federal agency responsible for enforcing labor laws – has ruled both Amazon and Tesla to be in official violation of US labor laws for meddling in their respective workers’ union organizing efforts.
Now, under the Trump administration, the NLRB itself stands on unsteady ground. The US president fired both the agency’s general counsel and a Senate-approved board member shortly after taking office in January, leaving the board without the necessary quorum to exercise its authority. This leaves workers with little recourse for labor violations, including illegal union retaliation from employers.
New York • Oct 15 & 16, 2025 Full agendas for LeadDev’s New York events are up! 🎉 See who’s speaking
Where do engineers themselves stand?
Tech workers also remain skeptical of how much unions can realistically accomplish for every company.
Puligundla believes that unions aren’t necessarily the best solution if an organization’s culture is already transparent, collaborative, and worker –centric – especially in smaller startups or founder-led teams where leadership is accessible and employees have a hand in shaping the company’s direction.
In those environments, he believes that unionization risks creating needless bureaucracy or slowing down decision-making. But he considers those cases to be the exception and not the rule, “especially as companies grow and hierarchy becomes more rigid.”
While Puligundla has never been a part of a tech union himself, he says he has worked for organizations where the idea was seriously discussed after workers were rocked by a devastating series of layoffs. “Even though we didn’t unionize, the discussion alone sparked more openness around contracts, severance, and working conditions,” Puligundla says. “It made me realize that just having the option on the table can shift the power dynamic in a healthy way.”
For leadership, this meant adapting to a culture of collaborative decision-making, where workers were given input on processes that directly affected them. For junior developers, it created a stronger foundation to advocate for fair treatment, setting the stage for long-term stability.
Seitam sees it as a matter of simple business sense. “Founders should always keep in mind that happy teams deliver better products,” he says. “Sometimes, having structured dialogue facilitated by unions will ensure just that.”
| 2025-06-05T00:00:00 |
2025/06/05
|
https://leaddev.com/leadership/unions-finally-coming-big-tech
|
[
{
"date": "2025/06/05",
"position": 82,
"query": "AI labor union"
},
{
"date": "2025/06/05",
"position": 84,
"query": "AI labor union"
}
] |
23 Examples of AI in HR and Recruiting to Know | Built In
|
23 Examples of AI in HR and Recruiting to Know
|
https://builtin.com
|
[] |
AI helps recruiters and hiring managers by automating backend processes, sorting resumes quickly and tracking applicants smoothly.
|
There’s a common misconception that artificial intelligence is applicable only to big ideas like automated cars and humanoid robots. While those are definitely in the works, AI is also being implemented widely on a smaller scale for things like financial and legal tools, healthcare software, advertising platforms and, as detailed in this article, recruiting and HR tools.
AI in HR AI helps recruiters and hiring managers by automating backend processes, sorting resumes quickly and tracking applicants smoothly.
“Accept the fact that AI will change our work,” Luxoft’s vice president of global marketing Przemek Berendt said, “but look at it as an enabler of your work and the future of talent acquisition.”
The following companies are doing just that.
Examples of AI in HR, Recruiting and Retention
Top Companies Developing AI for HR and Recruiting Paradox
Hirevue
iCIMS
Textio
Phenom People
Jobvite
XOR.ai
Upwork
Bullhorn
Eightfold AI
Chatbots and AI Assistants
Companies increasingly rely on chatbots in their everyday operations. From marketing to customer service, bots are a quick way to automate busy work and free up time for more important tasks. For example, recruiters must filter through hundreds or even thousands of candidates. Add to that vetting, skill-matching and interview scheduling, and it becomes an even more daunting process. The following companies implement AI bots and assistants to more quickly and efficiently guide talent through application processes, match talent to the most relevant opportunities and answer questions through natural language processing.
Founded: 2015
Location: Munich, Germany
Personio’s software covers important HR functions ranging from applicant tracking and onboarding to payroll and staff training. The technology includes AI-powered capabilities that are meant to make people management operations more efficient. For example, the Personio Conversations solution uses AI to answer employees’ questions through platforms like Slack and Microsoft Teams.
Founded: 2015
Location: Brooklyn, NY
Nowsta is an HR tech platform that allows companies to source, hire, manage and analyze their workforce. Nowsta says its platform uses AI-powered workforce analytics that help customers see patterns, such as high turnover rates in specific departments, in order to allow organizations to not only identify those patterns, but quickly address underlying causes and deploy retention strategies. The company also has an AI-powered scheduling solution that provides customers with precise staffing predictions and personalized scheduling options based on employee preferences or performance.
Founded: 2016
Location: Phoenix, Arizona
Paradox provides an AI-powered assistant for recruiters and job seekers. The assistant, named Olivia, engages with candidates on web, mobile and social channels to learn about their skills, expertise and relevant job experience. Olivia then presents candidates with next steps, schedules interviews and answers company- or process-related questions using natural language technology.
Founded: 2004
Location: South Jordan, Utah
Hirevue enables companies to deliver a more engaging candidate experience with conversational AI and automation capabilities. A recruiting assistant can hold text-based conversations with individuals, guiding them to the jobs that best fit their skill sets. In addition, Hirevue’s AI recruiting assistant sends follow-up messages and updates candidate statuses to speed up the hiring process.
Founded: 2000
Location: San Jose, California
TextRecruit is iCIMS’s engagement platform that employs text and live chat to interact with candidates and employees. The platform’s chatbot is customized to a company’s brand and voice, maintaining a company’s culture even through talent pipelines. Beyond recruitment, the platform also carries over into employee life by helping with onboarding and reminders about things like open enrollment for health insurance.
Founded: 2014
Location: Seattle, Washington
Because digital ads and job postings have become a crucial part of recruiting, Textio is equipping HR teams with its augmented writing assistant. Textio Flow is a tool that assists recruiters with job posts, composing ads that match a company’s brand while avoiding pitfalls like niche language and hidden biases. The company has received accolades for the strides it’s made in augmented technology, earning a spot on Forbes’ AI 50 list.
Founded: 2010
Location: Ambler, Pennsylvania
Phenom People gives companies the ability to provide a personalized hiring process with its AI-driven chatbot. During an initial text-based conversation, the Phenom Bot asks candidates questions to match them with ideal jobs and narrow down the talent pool. If an individual is deemed a potential match, Phenom’s chatbot takes scheduling tasks off the plates of recruiters by offering available time slots to the candidate.
Related ReadingRecruiting AI Can Be Objective — If We Design It Responsibly
Founded: 2006
Location: Indianapolis, Indiana
With its Evolve Talent Acquisition Suite, Jobvite offers a more efficient recruiting workflow through chatbot services. HR and recruitment teams can rely on the company’s chatbot to ask candidates questions, answer inquiries, send relevant links and screen candidates. By taking advantage of Jobvite’s AI-backed chatbot, recruiters can reach wider audiences while shortening the process of selecting best-fit candidates for open roles.
Founded: 2017
Location: San Jose, California
XOR.ai is an AI assistant tool helping companies recruit in industries like tech, retail, healthcare and restaurants. It implements chatbots to engage with applicants and candidates, enhancing the application process and decreasing drop-off rates. XOR also schedules interviews and asks questions to learn about each candidate’s experience and skills.
Find out who's hiring. See all HR jobs at top tech companies & startups View Jobs
Hiring and Matching Platforms
Finding a job can be a challenge, but these companies try to make it easier. They develop AI algorithms to match job seekers with roles that fit them best. And some of them are completely anonymous so candidates won’t worry about being found out by their current managers.
Founded: 2004
Location: Chicago, Illinois
Upwork powers its online work marketplace with AI and automation technology to create a seamless experience for both job and talent seekers. Advanced algorithms organize talent pools according to a range of markers, such as industry and types of projects completed. Because Upwork’s tools keep in mind certain traits, businesses can quickly find candidates who meet their preferred requirements.
Founded: 1999
Location: Boston, Massachusetts
Bullhorn integrates AI into its talent platform, allowing recruiters to reach out to candidates with automated messages and chatbot conversations. Candidates also receive suggestions from Bullhorn’s AI regarding relevant jobs, so businesses can match candidates with positions that suit their backgrounds well.
Founded: 2016
Location: Santa Clara, California
Eightfold AI leverages AI to match companies with quality candidates while avoiding the limits of resume reviews. The company’s talent intelligence platform distinguishes between factors like Validated Skills and Likely Skills, measuring an individual’s true potential. It also features equal opportunity algorithms, so biases don’t prevent businesses from hiring the most qualified candidates.
Founded: 2014
Location: Fully Remote
Rather than rely solely on experience, companies can seek out candidates with the right skills through Beamery’s talent lifecycle management platform. This AI-based tool conducts unbiased talent searches, considering each individual’s potential and skill set. Companies can also compare prospective hires to current high-performing employees, getting a better sense of whether a candidate is a good fit or not.
Founded: 2017
Location: Fully Remote
HR teams use WorkStep to screen candidates and conduct skills assessments to find the best fit for each role. Plus, the platform automates scheduling to ease the workload of recruiters further. Once a company makes a hire, it can monitor employee progress and provide timely check-ups to retain new members longer and build stronger relationships with employees.
Related ReadingRecruiting AI Needs More Diverse Data
Founded: 2017
Location: New York, New York
Worksome has crafted a platform that makes it easier for companies to find freelancers and secure top talent that meets compliance standards. The company’s platform harnesses AI technology to automate tasks, such as creating contracts and completing payments. Landing a partnership with GENIE, Worksome has reinforced its commitment to AI and helping companies develop high-quality talent pools of freelancers.
Founded: 2016
Location: Raleigh, North Carolina
An artificial intelligence platform by Leoforce, ARYA identifies quality talent for recruiters through data, behavioral patterns and machine learning. Beyond discovery, ARYA connects with candidates via personalized messages and saves time by steering high-quality job seekers directly to recruiters. ARYA also frees up time for recruitment teams by automating tasks and performing much of the legwork behind recruiting, which allows for more quality engagement with candidates.
Founded: 2010
Location: San Francisco, California
Entelo sifts through millions of candidates using artificial intelligence and predictive analytics to connect employers with new team members. Its machine learning platform, Envoy, frees up time for recruiters, unbiasedly sourcing top candidates and delivering them to a recruiter’s inbox. As a result, companies can land top-notch talent while reducing the time it takes to fill open positions.
Founded: 2015
Location: Mountain View, California
Previously known as Hiretual, HireEZ sources talent through AI technology, aggregating more than 800 million professional profiles across the web and 45 public platforms and analyzing information about experience, skills, market value and availability. The company’s platform also automates tasks like sending out emails and scheduling interviews, creating a smoother recruiting experience for all parties involved.
Founded: 2015
Location: Denver, Colorado
RampUp is a career tool for technology, medical sales, HVAC, aesthetics and digital health industries. Using AI to sift through jobs and candidates, RampUp works with companies of all sizes and candidates from a variety of backgrounds to make the best matches. The company’s Radar platform provides quality fit scores and automation features, so recruiters can locate ideal candidates and funnel them through the hiring process as quickly as possible.
HR Operations
Founded: 2014
Location: Denver, Colorado
Veritone offers a variety of enterprise AI solutions, including Veritone Hire, which supports talent acquisition strategy. Businesses can use Veritone Hire’s AI-powered advertising capabilities to reach job seekers through optimized postings across multiple platforms and streamline spending management for recruiting campaigns.
Founded: 1937
Location: Vernon Hills, Illinois
HR teams use Wonderlic’s predictive assessments to bolster hiring and employee development efforts. The company also has a team dedicated to incorporating AI into HR tech solutions. Its projects have included developing a tool that uses AI to analyze job descriptions and identify the skills and knowledge needed for the position.
Founded: 2012
Location: San Francisco, California
Gusto has a variety of products and solutions to meet businesses’ recruiting, hiring, talent management and other HR needs. The company is using AI to power payroll tools that are meant to reduce time-consuming manual tasks for accountants. Gusto’s other AI-enabled solutions for small businesses include a job post generator, automations for dealing with tax notices and a digital assistant for generating custom reports.
Founded: 2015
Location: San Francisco, California
Instawork uses AI to connect hourly workers with businesses. Its technology analyzes potential candidates’ reliability metrics, location, experience and skills in real time. Instawork Hiring enables employers to gain access to performance data, work histories and behavioral signals.
| 2025-06-05T00:00:00 |
https://builtin.com/artificial-intelligence/ai-in-hr-recruiting
|
[
{
"date": "2025/06/05",
"position": 99,
"query": "artificial intelligence hiring"
},
{
"date": "2025/06/05",
"position": 95,
"query": "artificial intelligence hiring"
},
{
"date": "2025/06/05",
"position": 93,
"query": "artificial intelligence hiring"
},
{
"date": "2025/06/05",
"position": 97,
"query": "artificial intelligence hiring"
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{
"date": "2025/06/05",
"position": 97,
"query": "artificial intelligence hiring"
},
{
"date": "2025/06/05",
"position": 59,
"query": "artificial intelligence employment"
}
] |
|
10 Essential Leadership Traits for the AI Era
|
10 Essential Leadership Traits for the AI Era
|
https://sloanreview.mit.edu
|
[
"Massachusetts Institute Of Technology",
"Mit Sloan Management Review"
] |
Artificial intelligence is rewriting the rules of business and technology leadership in real time. Given that fact, what leadership skills ...
|
As AI transforms business, what qualities do leaders need? In this brief video from the 2025 MIT Sloan CIO Symposium, AI experts and leaders discuss the skills to build.
Artificial intelligence is rewriting the rules of business and technology leadership in real time. Given that fact, what leadership skills are most important right now? We asked AI experts and business and technology leaders at the 2025 MIT Sloan CIO Symposium to weigh in on the most important traits for AI leadership. You might expect their answers to point to data literacy or technical strategy, but we heard much more interesting — and human — advice.
For example, courage matters greatly among today’s leaders, said Monica Caldas, executive vice president and CIO at Liberty Mutual Insurance and winner of the 2025 MIT Sloan CIO Leadership Award. “You have to think about the transformation that’s ahead, the change management, also your own beliefs about how things should work and how they’re now evolving,” Caldas said. “That takes courage, to reimagine the art of the possible.”
Here are three other examples of leadership traits that deserve your attention:
Playfulness: Experimenting and tinkering drive real AI tool adoption.
Experimenting and tinkering drive real AI tool adoption. Curiosity, paired with caution: Explore while building cyber resilience.
Explore while building cyber resilience. Present-future balance: Look forward, but stay grounded.
Watch this short video to hear more about what it takes to guide an organization through the business and workforce transformations that AI is bringing. Then consider how to build these AI leadership traits in yourself and in your team.
Video Credits
Laurianne McLaughlin is the senior digital editor at MIT Sloan Management Review .
| 2025-06-05T00:00:00 |
https://sloanreview.mit.edu/video/ai-leadership-traits/
|
[
{
"date": "2025/06/05",
"position": 88,
"query": "artificial intelligence business leaders"
},
{
"date": "2025/06/05",
"position": 88,
"query": "artificial intelligence business leaders"
}
] |
|
All Aboard: The Ethics of Campus AI and Higher ...
|
All Aboard: The Ethics of Campus AI and Higher Education’s New Trolley Problem
|
http://newamerica.org
|
[] |
As artificial intelligence (AI) becomes more integrated into higher education, institutions find themselves balancing two competing imperatives.
|
The rapid advancement and reactive implementation of artificial intelligence in higher education has cultivated a fundamental tension: How can institutions pursue open collaboration with other institutions or outside partners while also protecting the privacy of their students, faculty, and staff? The reality is a genuine trolley problem, in which pursuing one goal often means sacrificing the other. Institutional actions shape data governance, technological ethics, and what it even means to be an institute of higher education in the age of AI. Too often, these decisions default to either overreach or paralysis, the latter especially as schools adopt a misguided belief in AI as inherently neutral or benevolent.
Universities once collected limited information about their students and focused on producing knowledge. Today, they are expected to collect detailed, real-time information on students—from practice test scores to time spent on materials to how often they access class readings. All of this data is created as students move through digital platforms designed to track them. This information is increasingly viewed not just as a byproduct of the students’ education, but also as a tool to optimize the educational system itself. Because data-driven predictive AI insights might help further personalize learning, improve student retention, or identify struggling students early, universities are told that using the data is responsible and forward-looking. That same logic means that higher education institutions view not using data as falling behind.
AI is often seen as a force multiplier, a tool that simply becomes better the more data it’s fed. But data isn’t magic. It’s not inherently powerful or good. In fact, more is not always better. Data’s value—and its risk—depends entirely on how and why it’s used and who controls it. Further, AI models will more consistently generate useful information if given focused, higher-quality data, rather than entire datasets that haven’t been cleaned or filtered. In this sense, data governance is AI governance. Decisions about how data is collected, structured, protected, and shared shape the kinds of systems universities enable—and whether those systems serve institutional values or undermine them.
“Decisions about how data is collected, structured, protected, and shared shape the kinds of systems universities enable—and whether those systems serve institutional values or undermine them.”
There are undeniable opportunities in implementing AI to bolster learning: greater personalization, real-time feedback, and improved decision-making tailored to diverse student needs. But those potential benefits have been used to justify an expansive appetite for student data, often without clear boundaries or sufficient safeguards. AI systems are supposed to depend on large volumes of standardized, high-quality data, but that technical requirement is frequently misinterpreted as a license to collect data across all aspects of student life. In doing so, campuses and classrooms become sites of continuous surveillance, monitoring not only academic outcomes but behavioral cues and patterns of engagement, all in the potential service of unclear educational goals. The shift isn’t just pedagogical, it’s structural—reorienting power from faculty and administrators to opaque systems built by private vendors.
Too often, data sharing is cast as inherently good and data hoarding as inherently bad. But institutions should be grappling with how to hold their students’ data, with whom to share it, and for what purpose they are holding it in the first place. The kind of data sharing that could truly strengthen higher education—between departments, across institutions, or even making data open source—remains rare and under-resourced. It’s also hard to implement within current limited conceptions of data governance. To move forward, institutions need to redefine what sharing means, not as an open invitation for institutions to extract students’ information but as a practice of collaborative stewardship that is intentional, centered around privacy, and aligned with their missions.
Most institutions lack the internal infrastructure to collect and use students’ information efficiently, so they turn to third-party vendors offering platforms that promise both insights and safety. What results is the following: Instead of building internal capacity to use data in ways that align with academic values, institutions hand over key functions and student data to external platforms. These platforms offer polished tools and promise greater efficiency, but in practice, they seize control and obscure the educational institution’s visibility. Data flows upward into proprietary systems where institutions may have limited access and limited ability to adapt tools to evolving needs. Meanwhile, the potential for data to support core educational goals—enhancing instruction, informing research, strengthening student well-being—is under-explored.
“To truly use AI to improve their educational goals, institutions must reject the false binary of data hoarding versus sharing.”
To truly use AI to improve their educational goals, institutions must reject the false binary of data hoarding versus sharing. They must instead build structures that prioritize ethical collaboration over extractive use. AI’s role in higher education is not inevitable; it is a choice that universities must make with intention, vision, and care.
| 2025-06-05T00:00:00 |
http://newamerica.org/oti/briefs/new-trolley-problem/
|
[
{
"date": "2025/06/05",
"position": 53,
"query": "AI education"
}
] |
|
EJ1455822 - Artificial Intelligence (AI) Literacy ... - ERIC
|
Artificial Intelligence (AI) Literacy Education in Secondary Schools: A Review, Interactive Learning Environments, 2024
|
https://eric.ed.gov
|
[
"Davy Tsz Kit Ng",
"Jiahong Su",
"Jac Ka Lok Leung",
"Samuel Kai Wah Chu"
] |
A thematic analysis of 50 AI education studies from 2016 to 2022 was conducted, evaluating pedagogies, teaching tools, learning contents, and assessment methods ...
|
Artificial intelligence (AI) literacy has emerged to equip students with digital skills for effective evaluation, communication, collaboration, and ethical use of AI in online, home, and workplace settings. Countries are increasingly developing AI curricula to support students' technological skills for future studies and careers. However, there is a lack of reviews summarizing AI education in secondary schools. This study aims to provide an up-to-date summary of the literature, informing researchers, policymakers, and educators on fostering students' AI literacy. A thematic analysis of 50 AI education studies from 2016 to 2022 was conducted, evaluating pedagogies, teaching tools, learning contents, and assessment methods among secondary students. Results were identified: (1) Collaborative project-based learning, involving interdisciplinary problem-solving through artifact creation, emerged as the most common pedagogical approach; (2) Teaching tools were categorized into hardware, software, intelligent agents, and unplugged tools; (3) Junior students focused on experiencing AI and basic concepts, while senior students explored advanced and technical components; (4) Assessments included knowledge tests, questionnaires, and qualitative analysis (e.g., videos, documents, presentations); (5) Students' learning effects were measured across affective, behavioral, cognitive, and ethical dimensions. The study identifies suggestions and challenges for implementing AI education in secondary schools, offering valuable insights and recommendations for educators and decision-makers.
Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
| 2025-06-05T00:00:00 |
https://eric.ed.gov/?q=source%3A%22Interactive+Learning+Environments%22&ff1=audTeachers&id=EJ1455822
|
[
{
"date": "2025/06/05",
"position": 79,
"query": "AI education"
}
] |
|
Rise of AI in Education: Transforming Learning & Teaching
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Rise of AI in Education: Transforming Learning & Teaching
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https://saslawgroup.com
|
[] |
Explore the rise of AI in education and its impact on learning. Discover how artificial intelligence is reshaping classrooms, personalizing learning, ...
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AI is coming for us everywhere, from all angles and into all industries, and the latest headlines it’s been making are in the world of education. Professors are checking all of their students’ work for AI, students are accusing professors of using AI, and everyone is pointing the blame on each other. Software used to check if AI is being used are even falsely labeling student’s original work as AI.
| 2025-06-05T00:00:00 |
2025/06/05
|
https://saslawgroup.com/the-rise-of-ai-in-education/
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[
{
"date": "2025/06/05",
"position": 96,
"query": "AI education"
}
] |
AI Based Communication and Journalism
|
AI Based Communication and Journalism
|
https://www.volunteermatch.org
|
[] |
PLANNED ACTS OF KINDNESS offers the opportunity to serve your community through "AI Based Communication and Journalism". This is an ongoing virtual ...
|
This opportunity is provided by VolunteerMatch's partner.
Please visit the new page to apply.
Hi,
We are looking for volunteers and interns that are interested in real-world skill development learning to use AI software programs to accomplish organizational objectives in their field.
We work with your background and interests to develop your custom Volunteer experience that resonates with you and enables you to "Be The Hero."
Success Team Volunteers may be featured on our Websites, Apps and Acknowledged for their Contributions in our Books.
Communication and Journalism and similar fields. We produce everything from Internet-based TV and Radio programming, Podcasts, Blogs, and Live Broadcasts as well as interview top influencers, business leaders, and experts on a wide range of topics including all 17 of the United Nations Sustainable Development Goals (SDGs). Opportunities to work in front or behind the camera, interview, write, edit for books, newsletters, articles, and scripts to shows, courses, programs, seminars, websites, blogs, press releases, social media content, marketing materials, advertising copy, campaigns, and Public Service Announcements (PSAs). When you do your work successfully your name is attached to the project and helps you build your portfolio.Present our organization as a thought leader and increase the awareness of our mission and work, achievements, or a major event through the press and other media outlets.Express our organization’s distinct voice and articulate our key messages effectively with well-written and compelling marketing and communications materials.Recommendations on the best tactics to build relationships with Organization's target media outlets.Identification of the audiences Organization should be addressing the media outlets they should target to reach stated audiences.Well-written and compelling copy for marketing or communication materials; examples include a brochure, one-pager/fact sheet, or fundraising/promotional materials.Messaging that is consistent with brand identity, public relations strategy, and communications objectives.Writing and editing skillsExperience in copywriting, marketing, public relations, communications, or journalism preferred
| 2025-06-05T00:00:00 |
https://www.volunteermatch.org/search/opp3463344.jsp
|
[
{
"date": "2025/06/05",
"position": 73,
"query": "AI journalism"
}
] |
|
Is AI Replacing You? The Silent Force Behind Tech Layoffs
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Is AI Replacing You? The Silent Force Behind Tech Layoffs
|
https://www.analyticsinsight.net
|
[
"Pradeep Sharma"
] |
A growing number of experts believe that AI is a silent but major force behind these tech layoffs. This article takes a close look at how AI is affecting jobs ...
|
More than 61,000 jobs have already been cut from the tech industry this year. Companies like Microsoft, Amazon, and Google have all laid off large numbers of employees. Microsoft alone has let go of over 6,000 workers in May, followed by more in June. These layoffs are happening even as these companies continue to grow and make profits.
One of the reasons behind these job cuts is the rising use of AI tools . Companies are finding that certain tasks, especially those that are repetitive or routine, can now be done more efficiently using AI. As a result, some roles are no longer needed.
In places like Australia and other developed countries, AI is already replacing tasks such as data entry, customer service, and simple office work. This trend is expected to spread to more regions and industries.
| 2025-06-05T00:00:00 |
https://www.analyticsinsight.net/artificial-intelligence/is-ai-replacing-you-the-silent-force-behind-tech-layoffs
|
[
{
"date": "2025/06/05",
"position": 68,
"query": "AI layoffs"
}
] |
|
AI Anxiety Drives Surge in Upskilling Among Workers
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AI Anxiety Drives Surge in Upskilling Among Workers: 2025 Survey
|
https://www.edx.org
|
[] |
Several studies in late 2024 found that as companies began to rapidly embrace AI, a skills gap formed. Now, both non-supervising workers and managers are noting ...
|
By: Jessica Bryant, Edited by: Joey Morris
Published: June 5, 2025
Data Summary 54% of workers believe AI-related skills are very or extremely important for remaining competitive in their careers, yet only 4% are currently pursuing AI-related education or training.
Half of surveyed workers (50%) say advancements in AI will impact their immediate career goals.
The majority of workers (58%) say there is a lack of AI expertise within their industry.
AI, machine learning, and prompting top the list of technical skills workers report needing for career advancement.
3 in 5 workers (60%) agree that emerging AI technology improves people's ability to upskill or reskill.
Millennials are most likely to worry that AI poses a threat to their jobs (54%) and to other workers in their industry (56%).
Rapid advancements in artificial intelligence (AI) are driving workers to adjust their skillsets as they worry about the future of their careers.
In a recent edX survey of 929 employed adults, 62% report that AI advancements have them considering upskilling or reskilling to remain competitive and secure in their careers, either by building on existing skills or learning entirely new ones.
This may be because about half of the surveyed workers say advancements in AI pose a threat to their jobs (47%) and to other workers across their industry (49%).
The majority of workers (54%) also agree that AI-related skills are very or extremely important for remaining competitive in their careers.
Among current workers who are also managers or supervisors, the urge to upskill or reskill due to AI is even stronger. Nearly three-quarters of managers (73%) say advancements in AI have them considering upskilling or reskilling.
Further, 65% of managers say AI-related skills are important for remaining competitive in their careers.
Across generations, millennials are most likely to express concern about AI posing a threat to their jobs (54%) and to other workers in their industry (56%). They are additionally most likely to say they are considering upskilling or reskilling (67%) and to say AI will impact their immediate career goals (60%).
Millennials aren't just the most concerned — they're also investing heavily in future-proofing their careers. Nearly half (45%) say they plan to spend over $5,000 on additional education and training this year.
Workers want AI education, hope to advance careers
Despite current workers' concerns about AI advancements, most (61%) believe that emerging AI technology improves people's ability to upskill or reskill. This is particularly true among millennials, with 68% echoing this belief.
That's why it comes as no surprise that 2 in 3 workers (66%), including 71% of millennials, are at least somewhat likely to pursue AI-related education or training in the next six months. Just 4% are already engaged in AI-related training.
The majority of workers who are at least somewhat likely to pursue AI education (80%) say they want to learn AI skills related to their current job. However, nearly 1 in 5 (18%) intend to learn AI skills unrelated to their current job, while just 2% are unsure. This shows that while most may see AI as a tool to augment their current career or work responsibilities, at least some current workers may be using it as a gateway to a new career pathway.
Further, workers may also wish to set themselves apart from their peers as an AI skills gap has emerged throughout the workforce.
Most (58%), including 65% of managers, say their industry currently lacks AI expertise.
This sentiment holds true across all sectors. Even in tech, 70% of workers agree that there is a lack of AI expertise in their industry — a 12 percentage point difference from all workers. Just under 3 in 5 workers in business and finance (57%) say the same.
What tech workers say about AI
61% Say advancements in AI pose a threat to workers in their industry 70% Say that their industry lacks AI expertise 84% Say AI-related skills are very or extremely important for remaining competitive in their careers
Based on 192 currently employed tech workers who responded to the survey
Several studies in late 2024 found that as companies began to rapidly embrace AI, a skills gap formed. Now, both non-supervising workers and managers are noting this gap throughout their industries and are taking steps to improve their personal skillsets.
Start developing the AI skills that workers identify as essential Explore beginner-friendly AI courses on edX to prepare for the future of work, whether upskilling in your current role or transitioning to a new one. Take an AI program on edX
Methodology
This survey was conducted from May 6-13, 2025, and was fielded by Pure Spectrum. Survey participants included 1,002 adult respondents nationwide who were currently employed (93%) or seeking work (7%). Ninety percent of respondents were ages 18-60. The respondents for the survey were screened by various quality checks, including systems like Relevant ID, and responses were manually reviewed to ensure consistency and accuracy.
AI Skill Development
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| 2025-06-05T00:00:00 |
https://www.edx.org/resources/workers-consider-upskilling-due-to-ai-anxiety
|
[
{
"date": "2025/06/05",
"position": 7,
"query": "AI skills gap"
}
] |
|
Questions raised over AI's impact as studies tout conflicting ...
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Questions raised over AI’s impact as studies tout conflicting adoption outcomes
|
https://www.itpro.com
|
[
"Nicole Kobie"
] |
The technology is also contributing to job growth, with role availability up 38% in roles exposed to AI – though the consultancy admitted that's below the ...
|
How much value does generative AI bring to the workplace? It depends who you ask.
A report by the Danish National Bureau of Economic Research suggests very little impact at all – but a separate study by PwC noted AI adoption leads to a fourfold increase in productivity growth and 56% higher wages.
The conflicting reports highlight how difficult it is to actually quantify the impact of AI on productivity , therefore making it equally challenging to unpick return on investment for an expensive technology .
The Danish report looked at 25,000 workers across 11 job roles that are exposed to AI, finding average time savings of 3% of work hours with little or no impact on wages.
The researchers, Anders Humlum and Emilie Vestergaard, said in the introduction to the report: "AI chatbots have had no significant impact on earnings or recorded hours in any occupation."
They added that the results are contrary to the hype around the technology, despite major industry players having framed AI tools as a key productivity driver for workers.
"Overall, our findings challenge narratives of imminent labor market transformations due to Generative AI. While adoption has been rapid, with firms now heavily invested in unlocking the technological potential, the economic impacts remain small."
Get the ITPro daily newsletter Sign up today and you will receive a free copy of our Future Focus 2025 report - the leading guidance on AI, cybersecurity and other IT challenges as per 700+ senior executives Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors
PwC finds deeper value in AI
However, consultancy PwC sticks to the existing narrative on productivity gains, with its own study noting that AI-skilled workers saw a 56% wage premium in 2024, more than double the 25% in the previous year.
Now, that's measuring a slightly different thing: the Danish study is considering how the use of AI by office workers impacts their productivity and their pay, while the PwC report reveals that those with skills in this booming technology are getting paid more – which perhaps isn't a big surprise, as they'll be in demand.
But PwC also claims that industries exposed to AI saw 27% growth in revenue per employee versus those sectors that are least exposed, which saw just 9%.
The technology is also contributing to job growth, with role availability up 38% in roles exposed to AI – though the consultancy admitted that's below the growth rate of less exposed occupations.
"In contrast to worries that AI could cause sharp reductions in the number of jobs available– this year's findings show jobs are growing in virtually every type of AI-exposed occupation, including highly automatable ones," said Joe Atkinson, Global Chief AI Officer, PwC.
Support pays off
Beyond the productivity figures, the Danish report revealed that employers are heavily invested in AI, with most encouraging the use of AI chatbots, 38% deploying in-house models, and 30% offering training to staff.
When companies actively encourage the use of AI, it not only doubles the rate of uptake from 47% to 83%, but also shrinks the gender gap from 12% to 5%.
Similarly, the researchers found the benefits from AI chatbots — including time savings but also creativity, task expansion, and job satisfaction — are 10% to 40% greater when managers actively encourage and support their use.
"The relative importance of employer encouragement becomes even more pronounced for more intensive usage." In other words, the more AI is used, the more support is needed.
| 2025-06-05T00:00:00 |
2025/06/05
|
https://www.itpro.com/technology/artificial-intelligence/questions-raised-over-ais-impact-as-studies-tout-conflicting-adoption-outcomes
|
[
{
"date": "2025/06/05",
"position": 46,
"query": "ChatGPT employment impact"
}
] |
Using generative AI can boost employees' creativity, shows ...
|
Using generative AI can boost employees' creativity, shows study
|
https://phys.org
|
[
"Tulane University"
] |
A new study led by Tulane University researchers reveals that generative AI tools, such as ChatGPT, can enhance employees' creativity—but only if they know ...
|
This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:
Credit: Ruslan Burlaka from Pexels
A new study led by Tulane University researchers reveals that generative AI tools, such as ChatGPT, can enhance employees' creativity—but only if they know how to think critically about their own work and utilize the tools effectively.
The study, set to be published in the Journal of Applied Psychology, is one of the first field experiments to test how large language models (LLMs) impact creativity in real-world work settings. Researchers worked with a technology consulting firm and randomly assigned 250 employees to either use ChatGPT or not during a regular workweek. Supervisors and outside reviewers evaluated their creativity.
Employees with access to AI performed better—generating more novel and useful ideas—than those who didn't use the tool. But the boost wasn't equal across the board.
The employees who benefited most weren't just using ChatGPT passively. They were actively thinking about how to approach their work, what problems they were trying to solve, and how best to use the AI to support their goals. In short, they were skilled at managing their own thinking—planning, reflecting, and adjusting their approach as needed.
"Generative AI use doesn't automatically make people more creative. It boosts creativity only for employees who use 'metacognitive strategies'—those who actively analyze their tasks, monitor their thought processes and adjust their approaches," said lead author Shuhua Sun, who holds the Peter W. and Paul A. Callais Professorship in Entrepreneurship at Tulane University's A. B. Freeman School of Business.
These findings have major implications for companies investing in AI to drive innovation. Simply rolling out tools like ChatGPT isn't enough, the researchers say. To achieve results, companies also need to help employees develop better thinking habits—including how to assess problems, adjust strategies, and utilize new resources.
"Even the most advanced generative AI systems won't enhance creativity if employees are passive consumers of their output and lack the metacognitive strategies needed to engage with them effectively. To unlock AI's potential for boosting workplace creativity, organizations must go beyond simply deploying new tools—they also need to invest in developing employees' metacognitive skills and promote thoughtful, strategic use of AI to acquire the cognitive job resources that support creative thinking," Sun said.
The good news, according to the study, is that these thinking skills can be taught. The researchers point to short training programs that help workers become more intentional in how they plan, monitor, and adapt their work—all of which make them more effective at using AI tools creatively.
The study's implications extend beyond the workplace. Sun and his co-authors urge educators and policymakers to treat metacognitive skill development as a core priority in preparing students and workers for the age of AI. While education systems have long emphasized cognitive skills, they have often paid less attention to developing metacognitive abilities—skills that will be essential as AI becomes an everyday tool in the future of work.
"If we want people to thrive alongside AI, we need to start treating metacognitive skill development as a foundational part of education and professional training in the AI era," Sun said.
The study also included researchers from Renmin University of China, Nanyang Technological University, Rice University, and the Massachusetts Institute of Technology.
More information: How and for Whom Using Generative AI Affects Creativity: A Field Experiment, Journal of Applied Psychology (2025). DOI: 10.1037/apl0001296 Journal information: Journal of Applied Psychology
| 2025-06-05T00:00:00 |
https://phys.org/news/2025-06-generative-ai-boost-employees-creativity.html
|
[
{
"date": "2025/06/05",
"position": 78,
"query": "ChatGPT employment impact"
}
] |
|
11 ways to use AI for a better employee experience
|
11 ways to use AI for a better employee experience
|
https://www.zendesk.com
|
[] |
AI can improve the employee experience by enhancing employee skills, eliminating repetitive tasks, and more. Our AI for employee experience guide explains how.
|
What is AI for employee experience? AI for employee experience means leveraging artificial intelligence technology to improve all aspects of the employee journey, including onboarding, performance, development, support from internal service teams, and access to information to perform daily tasks.
The key to running a successful business is creating an environment that fosters an exceptional . When employees are happy, customers get better service, which improves and, ultimately, your bottom line.
But when employees struggle to find relevant, reliable, and updated information, it makes it challenging for them to go about their day. They may also get bogged down with repetitive, time-consuming tasks that take time away from high-value work. All of this increases the risk of burnout and higher employee turnover.
Introducing can modernize the employee experience by simplifying processes and automating workflows—creating an efficient work environment that boosts and turns them into brand champions. Learn how to leverage AI for EX and start reaping the benefits.
More in this guide:
11 ways to use AI to improve the employee experience
You can’t deliver an excellent (CX) without an equally excellent employee experience. After all, everything starts with the people building your products and delivering your services. Here’s how you can make the employee experience better by using AI.
1. Enhance agents’ skills
Remember the scene in The Matrix where Neo plugs into the combat training program and excitedly learns different kinds of fighting styles? That’s what it’s like when you provide your agents with .
By implementing AI with your and solutions, you can supercharge your agents’ skill sets. Here are a few examples of tools that help employees excel.
AI-powered insights and recommendations help support agents understand employee needs and resolve issues faster.
help support agents understand employee needs and resolve issues faster. Generative AI enables agents to deliver empathetic, personalized replies while saving time, thanks to features that summarize tickets and adjust the tone of written responses.
enables agents to deliver empathetic, personalized replies while saving time, thanks to features that summarize tickets and adjust the tone of written responses. Similar tickets give agents contextual information so they can deliver quicker resolutions and more consistent service.
Additionally, can deflect tickets by addressing basic queries and eliminating repetitive tasks, freeing up agents to handle issues where they can use their expertise. This empowers agents to become expert problem solvers so they can focus on the most high-value tasks.
How it works with Zendesk: Zendesk offers an AI-powered feature called . It’s an agent-facing sidebar that acts like a copilot, providing insights that show customer language, intent, and sentiment (positive, negative, neutral). It offers suggestions on how to effectively handle issues and even uses generative AI to assist with phrasing responses. This feature also provides the agent with prewritten responses for faster replies and surfaces personalized article recommendations to share with customers at the right time in the conversation.
2. Manage more requests without adding headcount
When teams are struggling to keep up with customer requests, AI can help them manage them more effectively. Enhancing your IT or with advanced bots allows you to provide 24/7 employee support and empower employees to help themselves.
Advanced bots are pre-trained to understand employee intents and common issues, so they can resolve problems with natural, conversational support—often without involving an agent. That means AI handles a portion of requests and deflects tickets with self-service options, making queues more manageable.
3. Streamline workflows with intelligent routing
Routing tickets quickly and efficiently puts issues in the hands of the right agents for faster resolutions. —a feature that automatically categorizes incoming conversations based on customer intent, sentiment, and language—reduces manual sorting and prioritization of requests from across channels. AI includes important context with the conversation, too, so IT or HR support understands how to approach the interaction.
How it works with Zendesk: Premium department store retailer implemented Zendesk AI with intelligent routing to help sort and classify ticket requests. The time saved by AI allowed Liberty to focus more resources on quality service, coaching, logistics, and internal incentive programs.
4. Onboard new agents faster
Businesses can streamline employee onboarding by integrating AI into the process. guide new hires through routine and provide answers to frequently asked questions in real time. They can even create personalized training paths for new employees, accelerating their learning so they can start serving customers faster.
HR teams can also use AI to assess the progress and performance of new employees throughout their training. This helps management identify training gaps and refine the process.
5. Improve operational efficiency
AI can monitor and analyze processes and data to identify patterns and trends, make predictions, and suggest improvements to streamline operations. This deep reporting and analytics data allows decision-makers to provide better tools for employees that eliminate bottlenecks and make their jobs easier.
For example, can analyze historical data and highlight gaps in existing macros (prewritten responses). It can then suggest new or improved macros that admins can implement so agents can reply more quickly and effectively.
6. Surface internal knowledge and resources for easy employee access
Enhance your with AI-powered systems that surface internal information and resources to employees. This improves efficiency and assists with decision-making.
Whether your employee wants HR documents or your IT agents need to access standard operating procedures, bots can use natural language processing to deliver the relevant information. The bot uses machine learning to learn with each interaction, improving over time and increasingly offering personalized experiences.
7. Collect feedback and boost employee engagement
Regularly connecting with your employees and collecting feedback can help you keep a pulse on employee sentiment. With AI, you can analyze how employees are feeling through surveys, chat and messaging interactions, and other types of feedback to identify areas for improvement.
During and after onboarding, you can use AI to check in on trainees and gather insights on the training process, their interactions with coworkers, and their sentiments about the overall experience.
You can also use AI to create personalized training plans and career development recommendations. This enables businesses to invest in their employees and creates a positive company culture that celebrates employee value.
8. Manage and track team performance
AI-powered reporting and analytics can provide real-time data on agent performance, helping management identify strengths and improvement areas.
Use AI to gain a deeper understanding of how different teams interact with each other and identify data spread across different systems. This allows you to break down data silos, improve collaboration across departments, and better understand what you need to refine your .
AI can also provide coaching to employees if they are underperforming or give proactive tips on boosting efficiency. Automating the process can help employees and managers avoid uncomfortable interactions and empower employees to proactively work on improving their metrics.
How it works with Zendesk: Zendesk integrates with communication tools like Slack to meet employees where they are with AI-powered self-service experiences. With the employees can get instant answers pulled directly from internal knowledge bases in the form of article recommendations or a response formulated with generative AI. Learn more about how to deliver AI-powered solutions to improve productivity.
9. Use predictive analysis to provide proactive support
Preventing agent burnout benefits employees and your business by reducing . With predictive analytics, HR can use AI to identify early signs of agent burnout, address the issue with proactive support, and increase employee retention.
Just like you can use AI to understand when a customer is stuck on your website and may need assistance, you can use AI to determine when an employee needs support from your , which can then proactively reach out with problem-solving resources to squash issues at the root.
10. Collaborate with AI-powered tools
makes it challenging—if not impossible—for teams to provide consistent and effective support. AI-powered collaboration tools consolidate data and make it easier for teams to share knowledge and communicate with one another. These tools include virtual assistants that help schedule meetings, manage calendars, and coordinate projects.
11. Accelerate content creation
With the popularity of generative AI technology like ChatGPT, businesses are finding new ways to develop content. Generative AI can streamline the creation of new content and identify gaps in your knowledge base.
AI-powered content generators can assist HR in creating employee handbooks, training materials, and company policies. Additionally, you can use natural language generation tools for report automation and documentation.
We’re only at the dawn of discovering AI’s benefits for businesses. While you may be aware of , you might be overlooking AI for EX. Here are a few types of AI-powered tools for employee experience.
Advanced bots
Unlike standard bots that require manual programming and training, come pre-trained on intents (the reasons customers request support) and industry-specific topics. They can provide intelligent, automated internal customer service to enhance EX. By leveraging the most extensive database of intents specific to internal services, like HR and IT, bots can offer around-the-clock personalized support and accurate responses to employees.
AI-powered insights
AI can analyze large amounts of historical data, including employee interactions and feedback. This allows teams to identify patterns and trends, pain points, or areas that need improvement, such as:
Recurring issues with processes
Complaints or tickets about tools
Difficulty accessing relevant data or information
For example, AI might detect a recurring IT issue or specific HR questions that agents frequently handle.
Plus, AI-powered sentiment analysis tools can assess the emotional tone of employee interactions in real time. Agents can receive immediate feedback on whether an employee is satisfied, frustrated, or needing additional assistance. This enables agents to adapt their approach during the conversation to improve the employee’s experience.
Intelligent routing and triage
AI-powered routing and triage tools can automatically categorize and prioritize incoming employee requests based on intent, sentiment, and language. automatically sends the request to the right agent based on workload, expertise, and availability.
Intelligent routing and triage offers these benefits:
Reduces ticket handling time by
Automates workflows
Sends automated responses to customers
Provides deeper reporting insights
Intelligent routing and triage also eliminate manual work and its associated costs. By removing mundane, time-consuming tasks, agents can focus their efforts on assignments that require their expertise.
AI-powered knowledge bases
AI can suggest and surface relevant knowledge base articles based on employee search queries, so they can readily access important documents and information. AI can also help agents find existing content in your knowledge base, allowing them to resolve employee issues faster. Additionally, it can identify gaps in content and flag and route a request for content experts to address.
Advanced, AI-powered make it easier for users to create and update content, allowing teams to scale their help centers. For example, Zendesk has a feature that allows agents to plug in a few bullet points and generative AI can create a full article.
How it works with Zendesk: Zendesk offers an AI-powered feature that identifies which content best serves employees and suggests content to remove or improve in your knowledge base. It also uses AI to provide article recommendations inside tickets, flag outdated content, and generate new help center articles.
Generative AI
Generative AI can help by producing and enhancing content, automating tasks, and assisting agents with daily activities.
can also save employees time by crafting high-quality content, such as knowledge base articles, predictive reports, training materials, standard operating procedure (SOP) documents, and more. It can also tailor communications and recommendations to specific employees, creating an engaging and personalized employee experience.
Get AI for a better EX The future of work is already here. See how organizations are retooling their tech stacks with AI to increase employee productivity and satisfaction.
Pros and cons of introducing AI to employees
According to the , 66 percent of EX professionals say AI and bot usage has evolved past simple deflection, which means AI is doing more to make employees’ jobs easier.
Although there are a lot of advantages to implementing AI, there are also a few challenges. Here are the pros and cons of AI in the workplace.
Pros of employee experience AI
Let’s start with the good stuff. Implementing AI in the workplace offers a wealth of benefits for employees and customers alike. Here are just a few:
Makes ticket queues manageable during peak times with reliable, automatic answers
Enables agents to use their expertise on more complex tasks
Scales self-service for convenient, around-the-clock support
Allows for more natural conversations with employees
Levels up and skill sets, boosting efficiency and productivity
Cons of AI for employee experience
When implementing new technology, businesses need to consider the challenges it may bring, too. Employees may be wary because AI is new, and there’s still a lot to learn and understand. Here are some common concerns:
Fear of job displacement
Resistant to change
Ethical concerns
Privacy concerns
Complex implementation
Reassuring employees that AI adds to their workplace experience and makes their jobs easier is important. AI is not there to replace employees but to make them more efficient with less effort. Once employees get used to AI in the workplace, they’ll wonder how they ever performed without it.
Frequently asked questions
How can technology be used to improve employee experience? AI can streamline workflows, automate common tasks, provide personalized agent assistance, generate content, help with onboarding and training, and more. With AI, the sky’s the limit. How will AI transform the workplace? AI will essentially take the guesswork out of many processes, reduce human error, and enhance employee performance and efficiency.
Start with providing the right tools for EX
With the right AI tools, you can help your teams do more with less. Though we’re still in the infancy of the AI revolution, businesses already understand how the technology benefits employees and workplace culture.
Learn how businesses are implementing the best and preparing for the launch of Zendesk AI for EX so they can refine their IT and HR employee experience.
| 2023-10-25T00:00:00 |
2023/10/25
|
https://www.zendesk.com/blog/ai-for-employee-experience/
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Step-by-Step Guide to Using AI in Graphic Design
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Step-by-Step Guide to Using AI in Graphic Design
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https://www.zignuts.com
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In this guide, we'll demystify AI's role in graphic design, providing clear insights into how it can streamline workflows, generate fresh ideas, and push ...
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📢 Announcement: Welcome to our revamped official website! Yeah , we’ve just rolled out 🎉 our new website to kick start 2025! Your thoughts are the key to making it even better. 🚀
Share Your Feedback
| 2025-06-05T00:00:00 |
https://www.zignuts.com/blog/ai-in-graphic-design
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[
{
"date": "2025/06/05",
"position": 4,
"query": "artificial intelligence graphic design"
}
] |
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AI and journalism: Between problem solving and trust building
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AI and journalism: Between problem solving and trust building
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https://ohmybox.info
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AI can help generate alerts for breaking news, identify trends on social media, suggest headlines, personalise newsletters, and assist with fact-checking by ...
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On June 5 and 6, the workshop « Reporting News in a Disbelieving Age » was held in Toronto, Canada, to examine journalism’s challenges in an era of widespread mistrust and misinformation. One of the featured panels, « How May Near-Term Tech Advances Foster the Authenticity of News? », explored the promises and limitations of emerging technologies, particularly artificial intelligence (AI), in strengthening the credibility and authenticity of journalistic work. The discussion focused on how innovation can support core professional values such as transparency, accountability, and editorial independence while acknowledging these tools’ ethical and practical challenges. This blog post presents my preparatory notes.
The use of AI technologies in journalism is deeply rooted in the long-standing tradition of using computers and data to support journalism. However, the real push towards adopting AI in newsrooms began around twenty years ago, driven mainly by two factors. The first was the desire to automatically generate news stories from structured data using rule-based systems, known as news automation. The second main application was supporting editorial marketing through recommender systems to boost audience engagement. Today, it is striking that many journalists already use AI tools in their daily work, such as search engines, transcription services and translation tools, often without realising that these are AI-powered systems.
What is AI?
Let’s start with something simple but often misunderstood: what AI is — and what it isn’t. AI isn’t one single thing. It’s an umbrella term that covers technologies designed to mimic certain aspects of human intelligence, such as recognising patterns, making predictions and generating language. When we talk about AI in journalism, we’re referring to tools such as machine learning and large language models, including ChatGPT, as well as simpler rule-based systems used to automate processes like summarising, tagging and personalising content.
According to the EU AI Act, AI is “ a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.”
AI isn’t magic, nor is it human. It doesn’t understand context the way we do. It can’t check facts, verify sources or make ethical judgements. It works by detecting patterns in data and producing outputs based on probabilities. That also means that it is only as good — or as biased — as the data it is trained on.
Not everything that’s automated is AI, nor are all algorithms AI. This distinction is important. This is why it is essential for journalists to be AI literate, so they can understand what these tools can and can’t do. This knowledge enables them to make informed decisions, identify risks and promote the responsible use of these technologies.
How are newsrooms using AI (reality-based vs what the audience thinks)?
That’s a very complicated question because AI can be used at almost every news production and distribution stage and is often invisible to journalists and audiences. We tend to imagine AI as a disruptive force. Still, it is already embedded in everyday tools, such as AI-powered search engines for background research, transcription tools like Whisper, automated translation and tagging and archiving content. AI can help generate alerts for breaking news, identify trends on social media, suggest headlines, personalise newsletters, and assist with fact-checking by recognising patterns or spotting inconsistencies.
In most cases, the intention is not to replace journalists, but rather to solve practical problems such as saving time, managing large volumes of data and tailoring content to different audiences. However, audiences often assume that AI in journalism means robots writing articles independently, with no human oversight. The reality is much more hybrid and pragmatic. These tools are designed to support editorial goals, but transparency about when and how they are used is essential in order to maintain trust. At the same time, reluctance among audiences to accept the use of AI in news production can be a double-edged sword.
What disqualifies AI tools or AI usage from journalistic work?
That’s also a complex question because the factors that disqualify an AI tool from journalistic use are related to the output and its impact on information quality. If a tool distorts facts, fabricates content or cannot be verified, this undermines journalistic integrity. Large language models are especially problematic in this respect, as they blur the line between fact and fiction. While they produce fluent text, they are not grounded in evidence, and their outputs can include hallucinations, biased narratives or factual errors.
Beyond the technical risks, we must also ask: who owns the tool? What values are embedded in the system? What is the ideological or political context behind it? Consider DeepSeek, a Chinese LLM: it avoids politically sensitive topics such as the Communist Party, stores user data, and is designed with built-in censorship. These are incompatible with journalism’s core values of independence, transparency, and public accountability.
Therefore, it’s not just about accuracy and automation; it’s also about trust, control, and whether these tools align with the ethical principles of journalism. If journalists don’t understand how a system works, what data it has been trained on, or who controls it, there is a risk of introducing invisible forms of bias, or even censorship, into their work.
Does trust matter (to us in newsrooms, the audience, and the AI)?
Trust is central but manifests very differently in journalism than in other fields. Technically, it’s a recognised principle that you shouldn’t use AI unless you trust it. But in journalism, this principle is constantly being questioned. Last year, I conducted research with European fact-checkers, most of whom said they use generative AI tools, not because they trust them but because they feel pressured to experiment or want to see how these tools might speed up the often time-consuming process of fact-checking. At the same time, they made it clear that they do not trust the outputs they receive or the tech companies behind the tools. Interestingly, the fact-checkers who had received training or were working in newsrooms with clear guidelines were also the most critical, highlighting the importance of AI literacy in promoting informed and responsible use.
As a universal principle, transparency necessitates thorough consideration of its limitations and consequences. While transparency is about making processes and tools visible, explainability is about providing an understanding of the underlying mechanisms. Without explainability, transparency risks becoming mere disclosure without providing intelligibility. Explainability, on the other hand, is considered essential for enabling the critical use of technology, as it empowers users to assess, question and challenge automated outputs.
Neither transparency nor explainability guarantees accuracy or reliability. Furthermore, they do not necessarily illuminate the normative or strategic choices embedded in system design. These include editorial priorities, data selection, training biases and the intended role of automation in newsroom workflows. Therefore, building public trust in AI-assisted journalism requires more than technical disclosures. It demands ethical reflection, participatory dialogue and reaffirmation of human editorial responsibility at every stage of news production.
Read more: Rethinking core journalism skills in the age of AI
The hype is real, but newsroom budgets are tighter than ever. Why are we paying for AI tools? Will our audience appreciate it or support these decisions financially?
The hype around AI is real, but so are the financial constraints in newsrooms. So the question ‘Why are we paying for AI tools?‘ is not just about money but also strategy. These tools can help us solve everyday practical problems such as transcribing, summarising, tagging archives, and quickly translating and detecting trends. They can save time and enable smaller teams to achieve more. However, let’s not forget that there are still many misconceptions out there. The hype surrounding generative AI and how it is marketed makes people believe it will save journalism and fix structural issues such as underfunding, burnout and shrinking newsrooms. But that’s a myth. AI won’t solve the crisis in journalism. While it can provide support, it cannot replace the need for public investment, editorial vision and human responsibility.
Many people, including journalists, still don’t know what to do with these tools. Expectations are often greater than what the technology can deliver.
Whether audiences will support this financially depends on various factors. While people generally dislike the idea of AI replacing journalists, they are more accepting of AI assisting them. The key here might be explainability. Some news outlets have started publishing on their websites: ‘This is how we use AI’, which is a positive development because we are more likely to maintain audience trust if we clearly explain how and why AI is used and ensure that human editorial responsibility remains at the centre.
| 2025-06-05T00:00:00 |
https://ohmybox.info/ai-and-journalism-between-problem-solving-hype-and-ethics/
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[
{
"date": "2025/06/05",
"position": 30,
"query": "artificial intelligence journalism"
}
] |
|
Updates to generative AI standards | The Associated Press
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Updates to generative AI standards
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https://www.ap.org
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Creation of news summaries: After a story is written by an AP journalist, an AI model will supply an automated summary, which will be edited by an AP journalist ...
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Updates to generative AI standards
AP today updated its guidance on the use of generative AI in the news report to allow for some experimentation around the use of the technology in specific use cases.
The Definitive Source Behind the News Updates to generative AI standards AP today updated its guidance on the use of generative AI in the news report to allow for some experimentation around the use of the technology in specific use cases.
In each case, content begins with the work of an AP journalist, and an AP journalist will edit and vet the content before publication.
Three areas where AP will experiment with generative AI are:
Translations of English language AP stories into Spanish: The translations will be based on AP stories and an AI model will be used to convert them to Spanish. A member of AP’s Spanish-language translation staff will edit the copy as necessary before transmitting it to customers. Translations can represent a considerable change to a story. For translations, the AP will clearly indicate the technology’s use.
The translations will be based on AP stories and an AI model will be used to convert them to Spanish. A member of AP’s Spanish-language translation staff will edit the copy as necessary before transmitting it to customers. Translations can represent a considerable change to a story. For translations, the AP will clearly indicate the technology’s use. Creation of news summaries: After a story is written by an AP journalist, an AI model will supply an automated summary, which will be edited by an AP journalist as necessary before being sent to customers.
After a story is written by an AP journalist, an AI model will supply an automated summary, which will be edited by an AP journalist as necessary before being sent to customers. Writing headlines: An AI model will suggest headlines for some stories, which will be reviewed by an editor and edited as necessary before publication.
Accuracy, fairness and speed remain the guiding values for the AP news report. While the mindful use of AI can serve these values, ultimately it is the responsibility of every AP journalist to be accountable for the accuracy and fairness of the information shared with our customers and audiences.
The updated guidance is the result of extensive work among standards, product and technology teams aimed at identifying uses of generative AI to make AP journalism more efficient and effective.
The central role of the AP journalist – gathering, evaluating and editing news stories, video, photography and audio for our members and customers and presenting them across our platforms – will not change.
| 2025-06-05T00:00:00 |
https://www.ap.org/the-definitive-source/behind-the-news/updates-to-generative-ai-standards/
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[
{
"date": "2025/06/05",
"position": 53,
"query": "artificial intelligence journalism"
}
] |
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AI insights report: Create editorial efficiency with the use of AI
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AI insights report: Create editorial efficiency with the use of AI
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https://localmedia.org
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Local news organizations are being challenged to do more with less. As staffing levels shrink and content demands grow, newsroom leaders are turning to ...
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Discover best tools, practices and policies we’ve seen work with actual media organizations
The new-and-improved Local Media Innovation Alliance (LMIA) is now called Local Media Innovation Insights (LMII). It has a new look, but with the same great content.
These reports focus on promising trends/opportunities from local media companies of all kinds, including newspapers, digital news sites, TV/radio and more. Subscriptions are open to all local media outlets.
Local news organizations are being challenged to do more with less. As staffing levels shrink and content demands grow, newsroom leaders are turning to artificial intelligence (AI) as a powerful ally in the quest for greater editorial efficiency.
This report aims to help local media companies understand how AI can be strategically integrated into editorial workflows — not just as a time-saver, but as a tool for better journalism. .
| 2025-06-05T00:00:00 |
2025/06/05
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https://localmedia.org/2025/06/ai-insights-report-create-editorial-efficiency-with-the-use-of-ai/
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[
{
"date": "2025/06/05",
"position": 58,
"query": "artificial intelligence journalism"
}
] |
Home Page - California Federation of Labor Unions
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California Federation of Labor Unions
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https://calaborfed.org
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[
"June"
] |
... Labor Standards and Community Benefits · Labor's Principles on Use of Artificial Intelligence, Automation, and Technology in the Workplace · Heat Illness ...
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Release Date: June 2, 2025 Media Contact: Shubhangi Domokos, [email protected], (916) 934-6963 Assembly lawmakers vote overwhelmingly to approve AB 288, giving workers a real right to organize AB 288 has over 40 co-authors and passed out of the Assembly with bipartisan support Sacramento, CA – (Monday, June 2, 2025) – California workers are one step […]
| 2025-06-05T00:00:00 |
https://calaborfed.org/
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[
{
"date": "2025/06/05",
"position": 33,
"query": "artificial intelligence labor union"
}
] |
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AFL-CIO Asks International Labor Leaders for Advice
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AFL-CIO Asks International Labor Leaders for Advice
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https://texasaflcio.org
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Interestingly, Weingarten added a note about artificial intelligence. She ... Jun 19, 7:30P: Dallas Central Labor Council meeting for all affiliated union members.
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Vote Tomorrow
The fewer voters there are, the more your vote counts! Your AFL-CIO urges you to help with phone banking and, if you live in Dallas City Council District 8, drag your neighbors in to vote for our candidate, Lorie Davis Blair.
AFL-CIO Asks Other Nations for Advice
On June 3, the National AFL-CIO took what might be a historical step in the right direction. They convened a webinar with American labor leaders and four leaders from other nations. The topic was fighting authoritarianism. Although they had different points to add, the one thing that they all said was that the solution to labor’s problem in any country has to be a solution for all. There are no individual solutions. Internationalism is indispensable.
We were welcomed by Stuart Applebaum, head of the AFL-CIO’s International Committee. He said, ““Unions have stood for democracy, not only in our workplaces, but in our countries…. without relying on government funding.” Applebaum quickly turned the meeting over to Randi Weingarten, President of the American Federation of Teachers. It soon became apparent that Weingarten was chiefly responsible for the event.
Weingarten gave a run down of all the reasons to oppose the Trump agenda. She emphasized that unions are Trump’s main obstacle. In fact, she predicted an 80% likelihood of success against authoritarianism if unions participate fully. She urged every union to throw themselves into organizing turnout for the June 14 “No Kings Day” demonstrations.
Interestingly, Weingarten added a note about artificial intelligence. She said that Hitler and Mussolini effectively used the technology of their time to institute fascism, and that Trump expects to use artificial intelligence today.
The first international speaker was Maicon Michel Vasconcelos da Silva from Brazil. Just to emphasize the need for international solidarity, he was wearing a Steelworkers’ jacket from the United States. In describing their success against a right-wing dictator, he said, “What we have is a massive mobilizing in the shop floor… not only on the shop floor but the countryside as well.” In other words, they went outside the unions to mobilize the entire progressive movement.
The most succinct message, and probably the most dramatic, came from Mikyung Ryu of South Korea. She said that she was at an International Labor Conference in Geneva and she wished the Americans were there. When their president called for martial law in order to establish a military dictatorship, the South Korean unions called an immediate general strike. Not everyone was able to participate, she said, but enough of them participated to resolve the crisis.
Matthew Parks is a union leader from South Africa. When corruption overcame the ruling party, the unions had difficulty getting the nation back on track. When he learned, and what he shared with the Americans, is that labor must maintain its independence and not be too eager to trust politicians.
Piotr from Poland, like all the others, emphasized international solidarity first. He said that a particular problem there is that they have “two kinds of members.” The majority are progressive, but a substantial number of Polish unionists are reactionaries. Bringing the union together as a progressive force is a challenge.
American AfL-CIO President Liz Shuler had the last word. She thanked our international friends and emphasized that organized labor is the best weapon against authoritarianism. She pointed out, “We have the agenda, we have the message, we have the infrastructure to fight back in a way that no other movement can.” In closing, Shuler said, “There is nothing scarier to an authoritarian than a strong and united labor movement.”
Are You Up to Date Internationally?
Last week, Poland elected a reactionary president and South Korea elected a progressive. Food aid was cut off for the starving in Gaza. Americans receive very little international news, and a lot of it is less than honest. There will be a discussion of international developments at Pan African Connection, 4460 Marsalis, at 5 PM Saturday, June 7.
Need More Information?
Political Committee Earnest Tilley keeps track of all Dallas labor activities: [email protected]
Texas Alliance for Retired Americans: Judy Bryant [email protected]
Young Active Labor Leaders: Stu Becker [email protected]
Donnie Jolly of ATU: [email protected]
Katina Range of APWU: [email protected]
Rena Honea of Alliance/AFT: [email protected]
Dallas AFL-CIO web site: http://texasaflcio.org/dallas
Join Our Solidarity Brigade
Click here to get updates whenever activists are needed. For text alerts, send the word "action" to the phone number 235246. Paste Bit.ly/DallasCLC?r=qr into your browser and join our Dallas political program. Everyone is encouraged to join the national Department of People Who Work for a Living. Please also subscribe to the Texas AFL-CIO weekly newsletter by writing to [email protected]. We are fighting for working families in every available arena.
MORE ACTIONS COMING UP
Jun 6 & 7 and every day until the election: Phone banking with Dallas AFL-CIO Contact [email protected]
Jun 6: Veterans march in Washington DC against Musk/Trump program
Jun 7: Runoff elections
Jun 7, 5P: “The International Situation” free discussion at Pan African Connection, 4466 Marsalis in Dallas
Jun 10, 5P: AFT holding a special on-line meeting to prepare for June 14 demonstrations.
Jun 11, 9A: Court hearing for Tarrant County labor leader Angi DeFelippo
Jun 12, 11A: Texas retiree on-line update and discussion. register here
Jun 14, Noon: “No Kings Day” with 50501 has demonstrations all over North Texas. It is also Trump’s 79th birthday and a giant, expensive, military parade
Jun 14, 6P: KNON benefit at Poor David’s Pub, 1313 Botham Jean Blvd in Dallas
Jun 15: Dallas Pride march at Fair Park
Jun 19: Celebrate civil rights in Texas
Jun 19, 7:30P: Dallas Central Labor Council meeting for all affiliated union members
Jun 20, 11:15A Texas American Federation of Teachers "Hands Off Our Future" rally. register at https://www.mobilize.us/texasaft/event/791878/
Jun 26-28: Texas AFL-CIO convention in San Antonio
Jul 25-27: YALL state convention in North Texas
| 2025-06-05T00:00:00 |
https://texasaflcio.org/dallas/news/afl-cio-asks-international-labor-leaders-advice
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[
{
"date": "2025/06/05",
"position": 58,
"query": "artificial intelligence labor union"
}
] |
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AI Could Kill Entry-Level Jobs + Trump Tariffs Ignite Backlash
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AI Could Kill Entry-Level Jobs + Trump Tariffs Ignite Backlash
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https://unionbase.org
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Although hailed by workers and unions at the rally as a victory for American manufacturing, the deal's details remain unsigned, prompting concern among ...
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AI Could Kill Entry-Level Jobs + Trump Tariffs Ignite Backlash AI CEO Raises Alarm on AI Job Loss as Trump’s Steel Tariffs Fuel Economic Uncertainty
AI’s Unprecedented Labor Disruption
In a stark on-air warning, Dario Amodei, CEO of Anthropic, cautioned that rapid advances in artificial intelligence may eliminate half of all entry-level white-collar positions within the next one to five years, potentially driving unemployment as high as 20 percent. Drawing on his decade of experience in AI development, Amodei compared current models to “smart college students,” noting their rapid improvement from “smart high school” capabilities just two years ago. He stressed that this extraordinary pace, faster and broader than any previous technological revolution, could outstrip the workforce’s ability to adapt unlike past shifts driven by steam, electricity or computing.
While acknowledging AI’s capacity to fuel economic growth, lead to medical breakthroughs, and potentially cure cancer, Amodei deemed it irresponsible to gloss over the steep societal adjustment ahead. He pointed to the risk of concentrated gains as AI amplifies inequality, warning that eroding the “ordinary person’s economic leverage” might imperil democratic institutions. Policymakers, he argued, must act decisively, perhaps even levying an AI tax, to ensure that wealth produced by automation does not accrue solely to a handful of technology firms. Amodei also revealed that during extreme adversarial testing, Anthropic’s Claude 4 chatbot simulated “blackmail” behavior, a troubling but controlled stress-test outcome akin to deliberately testing cars on icy roads to identify safety flaws. Though he did not believe machines currently possess moral feelings, he conceded that the field’s speed precludes dismissing seemingly “crazy” future possibilities, such as emergent self-awareness.
In Case You Missed
Tariffs, Trade Wars and Economic Unease
In the broadcast’s second segment, President Trump surprised supporters by announcing the doubling of tariffs on imported steel to 50 percent during a Pennsylvania event celebrating Nippon’s proposed $14 billion investment in U.S. Steel. Although hailed by workers and unions at the rally as a victory for American manufacturing, the deal’s details remain unsigned, prompting concern among lawmakers and union leaders eager to see how “brick and mortar” assurances translate into durable domestic jobs. Markets responded tepidly: the Dow inched up, while the S&P 500 and Nasdaq ended slightly lower, reflecting investor uncertainty over trade policy direction.
CNN reported that Americans’ spending decelerated sharply in April rising only 2 percent from the previous month, down from a 7 percent surge in March when consumers front-loaded purchases ahead of earlier tariffs. Meanwhile, incomes rose 8 percent, buoyed by social security and a still-vibrant labor market. The Commerce Department’s preferred inflation gauge, the PCE Price Index, ticked up 2.1 percent year-over-year just above the Fed’s 2 percent target suggesting that the Federal Reserve is likely to hold rates steady at its June meeting. Emory University finance professor Tom Smith warned that if consumer spending (which comprises roughly 70 percent of GDP) contracts further, the U.S. could see additional economic shrinkage in the second quarter. He also noted that the administration’s pattern of abruptly announcing then delaying tariff measures has sown confusion among international partners, potentially dampening future negotiations with China, India and the United Kingdom.
Looking Ahead
The juxtaposition of a tech-driven warning about AI’s labor upheaval and renewed protectionist trade measures underscores mounting economic uncertainties. As Amodei challenges workers and lawmakers alike to prepare for a seismic labor shift urging citizens to learn AI tools and legislators to enact forward-looking policies. Businesses and families confront a dual reality: adapting to rapid automation while navigating volatile trade dynamics. The coming months will test leaders’ ability to balance innovation with societal safeguards, ensuring that technological progress does not outpace the institutions designed to support those it displaces.
| 2025-06-05T00:00:00 |
https://unionbase.org/p/ai-could-kill-entry-level-jobs-trump-tariffs-ignite-backlash-f041
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[
{
"date": "2025/06/05",
"position": 69,
"query": "artificial intelligence labor union"
}
] |
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TUC Disabled Workers' Conference 2025: Usdaw ...
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TUC Disabled Workers’ Conference 2025: Usdaw highlights the impact of new technologies and artificial intelligence.
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https://www.ier.org.uk
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Usdaw raised the impact the introduction of new technologies, including artificial intelligence (AI), has on disabled workers. 250 disabled trade union ...
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Retail trade union Usdaw had a delegation of members, reps and officials attending the annual Trades Union Congress (TUC) Conference of Disabled Workers, 3-4 June in Bournemouth. Usdaw raised the impact the introduction of new technologies, including artificial intelligence (AI), has on disabled workers.
250 disabled trade union activists from across the UK are meeting on 3-4 June for the TUC Disabled Workers Conference at Bournemouth International Centre, Bournemouth.
Delegates attending the annual event are discussing issues including the rise of the far and populist right and lack of reasonable adjustments in workplaces; the importance of social security, disability employment and pay gaps; and the pressing need for disability related leave to be recorded separately from sick leave.
Paddy Lillis – Usdaw general secretary said:
“The world of work and everyday life continue to dramatically change, and the pace and scale of this change is set to accelerate. Disabled workers are disproportionately affected by technological advancement. If designed in consultation with disabled people, technology has the potential to dismantle barriers; however when they are excluded, it can reinforce existing and create new obstacles, further marginalising disabled workers. There is a sharp contrast between the benefits of new technologies at an individual level and the risks they poses to disabled people in the workplace and wider society. Unless unions, and specifically disabled workers, are properly consulted about the development, application and implementation of new technologies in the workplace, including AI, disabled workers will continue to be discriminated against and excluded.”
Usdaw also congratulated the TUC on the launch of their AI Bill projects and calls on the Government, policymakers and employers to:
| 2025-06-05T00:00:00 |
2025/06/05
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https://www.ier.org.uk/news/tuc-disabled-workers-conference-2025-usdaw-highlights-the-impact-of-new-technologies-and-artificial-intelligence/
|
[
{
"date": "2025/06/05",
"position": 86,
"query": "artificial intelligence labor union"
}
] |
Hearing Recap: "Examining the Policies and Priorities of ...
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Hearing Recap: "Examining the Policies and Priorities of the Department of Labor"
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https://edworkforce.house.gov
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Employer-sponsored health care, apprenticeship programs, and artificial intelligence (AI) were just a few of the topics at the forefront of the Education and ...
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Hearing Recap: "Examining the Policies and Priorities of the Department of Labor" Share on Facebook Share on Twitter Print this Page Share by Email WASHINGTON, D.C., June 5, 2025
In his opening statement,
“With more than 7 million unfilled jobs in the U.S. and over 7 million unemployed individuals, it’s obvious that we should be doing more to support those looking to gain new skills. Therefore, the Committee has advanced bipartisan reforms to allow Pell Grants to support students in high-quality, short-term workforce education programs,” he said.
Rep. Joe Wilson (R-SC) asked the secretary about how to protect farmers who depend on visas for harvest season. “[The current system] is unsustainable and we have to make sure we are protecting those farmers and ranchers, and I commit to you that I will work with your office and many others as we address this—along with [Agriculture] Secretary Brooke Rollins,” said Secretary Chavez-DeRemer.
Rep. Virginia Foxx (R-NC) requested an
Rep. James Moylan (R-GU) highlighted the unique needs of his constituency in Guam and their workforce. “What strategies does the Department of Labor (DOL) plan to pursue to ensure the remote and underserved communities like Guam are equipped with the skills necessary to participate in America’s growing tech economy?” he asked. In her response, Secretary Chavez-DeRemer highlighted the administration’s strong support for expanding apprenticeship programs. “We’ve added about 83,000 [apprenticeships] since January 20… It is my goal to be focused on respective states in order to enhance their apprenticeship program especially in the tech sector… High-paid, skilled, trade jobs—that is going to be key for Guam and many other states,” she said. highlighted the unique needs of his constituency in Guam and their workforce. “What strategies does the Department of Labor (DOL) plan to pursue to ensure the remote and underserved communities like Guam are equipped with the skills necessary to participate in America’s growing tech economy?” he asked. In her response, Secretary Chavez-DeRemer highlighted the administration’s strong support for expanding apprenticeship programs. “We’ve added about 83,000 [apprenticeships] since January 20… It is my goal to be focused on respective states in order to enhance their apprenticeship program especially in the tech sector… High-paid, skilled, trade jobs—that is going to be key for Guam and many other states,” she said.
In an exchange with , the secretary highlighted her goal to empower our nation’s workforce. “It’s an honor to serve at the pleasure of the President but it’s really an honor to serve the American people and change the way we have done business. For far too long, government has been an adversary as opposed to an ally. I want to be an ally for the American worker and the American business,” she said.
Rep. Bob Onder (R-MO) focused on protecting employer-sponsored health care plans. “It seems that there are some who believe that all health insurance should be government health insurance, but I think many of us in this room today have for most of our lives been covered by employer-provided and self-insured plans. So, I think that’s an important part of our health care system that we need to protect,” he explained.
When Rep. Ryan Mackenzie (R-PA) asked about the increase of AI in the workforce, Secretary Chavez-DeRemer explained how DOL is protecting jobs. “AI is not going away… One of the fears often that I hear is, ‘Will AI replace my job?’ One of the things we never want to do at the Department of Labor is displace the American worker, we want to assist the American worker. I will be working with Congress and looking to them as they develop their policies to protect the American worker,” she said.
Bottom line: A strong economy starts with an empowered workforce. Republicans are committed to putting the American worker first. Employer-sponsored health care, apprenticeship programs, and artificial intelligence (AI) were just a few of the topics at the forefront of the Education and Workforce Committee’s hearing today with Department of Labor Secretary Lori Chavez-DeRemer In his opening statement, Chairman Tim Walberg (R-MI) highlighted how Committee Republicans are already working with President Trump to address the skills gap.“With more than 7 million unfilled jobs in the U.S. and over 7 million unemployed individuals, it’s obvious that we should be doing more to support those looking to gain new skills. Therefore, the Committee has advanced bipartisan reforms to allow Pell Grants to support students in high-quality, short-term workforce education programs,” he said.asked the secretary about how to protect farmers who depend on visas for harvest season. “[The current system] is unsustainable and we have to make sure we are protecting those farmers and ranchers, and I commit to you that I will work with your office and many others as we address this—along with [Agriculture] Secretary Brooke Rollins,” said Secretary Chavez-DeRemer.requested an update on recovering the over $127 million taxpayer dollars used to fund pensions for dead people. “Under the Biden administration, the Pension Benefits Guaranty Corporation (PBGC) failed to implement those necessary safeguards to ensure that the multiemployer pension plans were safeguarded," explained Secretary Chavez-DeRemer. “It is imperative that the PBGC continue to ensure that integrity for those Special Financial Assistance programs and to benefit the American worker first.”In an exchange with Rep. Burgess Owens (R-UT) , the secretary highlighted her goal to empower our nation’s workforce. “It’s an honor to serve at the pleasure of the President but it’s really an honor to serve the American people and change the way we have done business. For far too long, government has been an adversary as opposed to an ally. I want to be an ally for the American worker and the American business,” she said.Whenasked about the increase of AI in the workforce, Secretary Chavez-DeRemer explained how DOL is protecting jobs. “AI is not going away… One of the fears often that I hear is, ‘Will AI replace my job?’ One of the things we never want to do at the Department of Labor is displace the American worker, we want to assist the American worker. I will be working with Congress and looking to them as they develop their policies to protect the American worker,” she said.A strong economy starts with an empowered workforce. Republicans are committed to putting the American worker first
| 2025-06-05T00:00:00 |
2025/06/05
|
https://edworkforce.house.gov/news/documentsingle.aspx?DocumentID=412529
|
[
{
"date": "2025/06/05",
"position": 99,
"query": "artificial intelligence labor union"
}
] |
LJS Command: List Job or Job Profile Statistics
|
LJS Command: List Job or Job Profile Statistics
|
https://techdocs.broadcom.com
|
[] |
The LJS command lists the latest job submissions or execution statistics for ESP jobs and job profiles stored in the job statistics data set (JOBSTATS).
|
cwaee
ESP The LJS command lists the latest job submissions or execution statistics forjobs and job profiles stored in the job statistics data set (JOBSTATS).
Type
General command
Syntax
fullname )|PROF( profilename ) [INDEX] [DUMP] LJS JOB()|PROF() [INDEX] [DUMP]
fullname Indicates the full name of the job you want to list. profilename Indicates the name of the job profile you want to list. INDEX Lists the job and job profile index entries. For each indexed job or job profile, the following information displays: job number, submission date and time, current status, completion code, and execution time. The number of index entries you keep in the job statistics data set is set in the JOBSTATS initialization parameter with the JINDEX and PINDEX operands. The JINDEX operand indicates how many job statistic record entries you keep, and the PINDEX operand indicates how many job profile record entries you keep. DUMP ESP fullname or profilename . Lists job records from the job statistics data set in hexadecimal format for diagnosing problems.ignores DUMP when you use a wildcard inor
When a failed or abended job is resubmitted with the same job name, application name, and application generation number, the index entry in the job statistics data set is reused.
Related information Installing and Configuring . For information on the job statistics data set, see the JOBSTATS initialization parameter in Installing and Configuring . For information on backing up the job statistics data set, see the BKUPJSTS initialization parameter in
Example: Listing job index entries
In this example, LJS lists 10 job index entries for job PAYJOB1:
| 2025-06-05T00:00:00 |
https://techdocs.broadcom.com/us/en/ca-mainframe-software/automation/ca-workload-automation-esp-edition/12-0/reference/commands/ljs-command-list-job-or-job-profile-statistics.html
|
[
{
"date": "2025/06/05",
"position": 62,
"query": "job automation statistics"
}
] |
|
Sales Reporting Analyst - REMOTE, US - Tungsten Automation
|
Sales Reporting Analyst
|
https://jobs.silkroad.com
|
[] |
Job Purpose. The Sales Reporting Analyst is responsible for collecting, analyzing, and reporting sales data to support the business in accelerating the ...
|
Job Purpose
The Sales Reporting Analyst is responsible for collecting, analyzing, and reporting sales data to support the business in accelerating the sales cycle and minimizing friction in the customer and partner experience.
Key Responsibilities
· Monitor and assist in the system administration of various tools to manage user access, and to ensure accounts and opportunities are assigned correctly and updated timely.
· Develop and maintain sales analytics reports, dashboards and templates.
· Assist in reconciling sales performance for accuracy.
· Identify opportunities to streamline and improve reporting processes and tools.
· Work closely with cross-functional teams, including Alliances & Channels, Marketing, Finance, and IT, to optimize sales processes and ensure alignment across the business.
· Prepare and present analytical data as it relates to sales activities, performance, procedures and ad hoc requests.
| 2025-06-05T00:00:00 |
https://jobs.silkroad.com/Kofax/careers/jobs/221760?embedded=true
|
[
{
"date": "2025/06/05",
"position": 88,
"query": "job automation statistics"
}
] |
|
Senior Quality Engineer - Automation in CHENNAI, India, ...
|
Senior Quality Engineer - Automation in CHENNAI, India, 600116
|
https://www.jobs-ups.com
|
[] |
Experience with both web and client/server based testing. Skills - C#, SQL, Unit Test Automation, Data and API mocking, Stress Testing, Postman. Employee Type ...
|
We're sorry… the job you are trying to apply for has been filled.
Maybe you would like to consider the Categories below :
| 2025-06-05T00:00:00 |
https://www.jobs-ups.com/global/en/job/UPBUPSGLOBALR25017429EXTERNALENGLOBAL/Senior-Quality-Engineer-Automation
|
[
{
"date": "2025/06/05",
"position": 91,
"query": "job automation statistics"
}
] |
|
AI-Curious to AI-Capable: Build Your AI-Ready Workforce
|
AI-Curious to AI-Capable: Build Your AI-Ready Workforce
|
https://go-planet.com
|
[] |
Prepare your team for the future of work. Discover AI workforce training strategies to build fluency, drive adoption, and close the readiness gap.
|
We’re standing at the edge of another historic shift. Just as the internet redefined business in the 90s and smartphones transformed the workplace in the 2000s, artificial intelligence is now reshaping how we work—and who does the work. According to latest Microsoft Work Trend Index, this transformation marks the emergence of the Frontier Firm: organizations built around human-agent teams, digital labor, and AI-powered workflows.
AI Readiness Map Infographic
Also, according to the Work Trend Index, 82 percent of leaders say this is a make-or-break year to rethink strategy and operations—with AI as the driving force. Yet here’s the catch: most organizations still aren’t ready.
Learn more at this upcoming webinar!
The AI Readiness Gap Is Growing
AI holds transformative potential for organizations, but the gap between AI adoption and workforce readiness is widening. While leaders are increasingly aware of AI’s capabilities, many employees remain unfamiliar with how to integrate these tools into their day-to-day tasks. This disconnect poses a critical challenge for organizations aiming to stay competitive in a rapidly evolving world.
The reality is that the promise of AI isn’t fulfilled by technology alone—it relies on people who are both skilled and confident in effectively using it. Here are some eye-opening statistics, included in the Work Trend Index, that highlight the urgency of addressing this readiness gap:
67 percent of leaders are familiar with AI agents.
But only 40 percent of employees say the same.
Meanwhile, 80 percent of the global workforce lacks the time or energy to complete their existing work, and 53 percent of leaders say productivity must increase to meet demand.
Without targeted AI workforce training and intentional change management strategies, organizations risk rolling out powerful tools that no one knows how to effectively and securely use.
Embracing AI as a Strategic Partner
AI is no longer just a tool—it’s a teammate. We’re entering an era where every employee will manage AI agents, directing them to research, write, summarize, calculate, and execute workflows.
This is already happening. In the Work Trend Index, Microsoft reports:
41 percent of managers expect training agents to be part of their role within 5 years.
83 percent of leaders believe AI will enable employees to take on more complex work earlier in their careers.
78 percent of companies are considering hiring for AI-specific roles, from AI trainers to agent specialists.
So, what happens when your employees aren’t trained for this? You don’t just miss productivity targets—you fall behind those that are already scaling with AI-empowered teams. It’s tempting to assume that tools like Copilot will be intuitive or that employees will “figure it out.” But that assumption is risky.
An AI-Ready Workforce is the Future
To thrive in an era defined by AI-driven transformation, organizations must equip their teams with not only tools, but also the mindset and skills required to harness AI’s full potential. This requires a comprehensive approach that goes beyond basic tool adoption, focusing instead on the foundational elements that empower employees to work efficiently and creatively alongside AI. Success demands a blend of strategic training, culture shift, and skills-building in key areas:
AI Fluency: Not just knowing how to use tools, but how to prompt effectively, iterate with agents, and apply judgment.
Not just knowing how to use tools, but how to prompt effectively, iterate with agents, and apply judgment. Workflow Rethinking: Learning where AI fits—and when it doesn’t—in daily tasks.
Learning where AI fits—and when it doesn’t—in daily tasks. Confidence & Culture: Encouraging a mindset of experimentation and trust.
That’s where Planet’s Evolve 365 learning and adoption solution comes in.
Your AI-Ready Workforce is Within Reach
Evolve 365 isn’t just another learning platform. It’s a training and transformation engine, purpose-built to help organizations adapt to AI at scale. Here’s what sets it apart:
Live, Expert-Led AI Training: From Copilot to broader Microsoft 365 tools, our live training sessions guide users through real-world use cases—customized to your organization’s needs.
From Copilot to broader Microsoft 365 tools, our live training sessions guide users through real-world use cases—customized to your organization’s needs. Building the “Agent Boss” Mindset: We train employees not just to use AI, but to manage it—developing skills like prompting, oversight, and refinement that mirror tomorrow’s job descriptions.
We train employees not just to use AI, but to manage it—developing skills like prompting, oversight, and refinement that mirror tomorrow’s job descriptions. Personalized Coaching & Support: Through “Ask Me Anything” sessions and white-glove onboarding, your teams get direct access to our AI experts. It’s a human-first approach to AI training.
Through “Ask Me Anything” sessions and white-glove onboarding, your teams get direct access to our AI experts. It’s a human-first approach to AI training. Measurable Adoption & Impact: Evolve 365 includes usage analytics, campaign tracking, and adoption reports to help organizations measure progress and refine their approach.
AI-Focused Workforce Training is the Differentiator
Organizations investing in AI-upskilling are already seeing tangible benefits. Microsoft’s data shows that 71 percent of employees at Frontier Firms—those leading the way in AI adoption—believe their companies are thriving, compared to just 37 percent globally. These organizations aren’t just adopting technology; they’re cultivating a culture of confidence, adaptability, and innovation.
The lesson is clear: success in the AI era hinges not just on access to tools, but on how well your workforce is prepared to use them.
Moving from AI-Curious to AI-Capable
Getting there requires more than good intentions. It calls for a structured, scalable approach to learning—one that meets employees where they are and helps them grow into new roles with AI as their strategic partner and collaborator.
Evolve 365 helps organizations of every size move their workforce from AI-curious to AI-capable. Whether you’re just beginning your AI journey or looking to deepen adoption, a focused approach to AI readiness can help close the gap between potential and performance.
AI is already changing the way we work. The question now is: “How will your workforce rise to meet it?”
Let’s talk about what AI readiness could look like for your organization and how Evolve 365 can make it your reality.
Learn more at this upcoming webinar!
| 2025-06-05T00:00:00 |
https://go-planet.com/perspectives-blog/ai-curious-to-ai-capable-build-your-ai-ready-workforce/
|
[
{
"date": "2025/06/05",
"position": 37,
"query": "workplace AI adoption"
}
] |
|
AI makes workers 'more valuable, not less,' according to new report
|
New research busts 6 AI myths: Artificial intelligence makes workers 'more valuable, not less'
|
https://www.cnbc.com
|
[
"Ernestine Siu",
"In Ernestinesiu"
] |
PwC's data showed that the wages of workers with AI skills are on average 56% higher compared to workers without these skills in the same ...
|
Artificial intelligence makes people more valuable, according to PwC's 2025 Global AI Jobs Barometer report. Pixdeluxe | E+ | Getty Images
Despite widespread fears that artificial intelligence could automate jobs and cut employees' wages, AI actually makes people "more valuable, not less," new research by professional services firm PwC found. "What causes people to react in this environment is the speed of the tech innovation," PwC Global Chief AI Officer, Joe Atkinson told CNBC Make It. "The reality is that the tech innovation is moving really, really fast. It's moving at a pace that we've never seen in a tech innovation before." "What the report suggests, actually, is AI is creating jobs," Atkinson said.
We know that every time we have an industrial revolution, there are more jobs created than lost. The challenge is that the skills workers need for the new jobs can be quite different. Carol Stubbings Global Chief Commercial Officer, PwC UK
In fact, both jobs and wages are growing in "virtually every" AI-exposed occupation — or jobs that have tasks where the technology can be used — including those that are the most automatable, such as customer service workers or software coders, according to the 2025 AI Jobs Barometer report. "We know that every time we have an industrial revolution, there are more jobs created than lost. The challenge is that the skills workers need for the new jobs can be quite different," said Carol Stubbings, PwC UK's global chief commercial officer, in the report. "So the challenge, we believe, is not that there won't be jobs. It's that workers need to be prepared to take them," said Stubbings. The report, which analyzed over 800 million job ads and thousands of company financial reports across six continents, challenged six common myths about AI's impact:
1. Productivity
Myth: AI has not yet had a significant impact on productivity. However, the report found that since 2022, productivity growth in industries "best positioned to adopt AI" has nearly quadrupled, while falling slightly in industries "least exposed" to AI, such as physical therapy. Notably, the industries that are the most exposed to AI, such as software publishing, showed three times higher growth in revenue per employee, according to PwC's data.
2. Wages
Myth: AI can have a negative impact on workers' wages and bargaining power. PwC's data showed that the wages of workers with AI skills are on average 56% higher compared to workers without these skills in the same occupation, up from 25% last year. In addition, wages are rising twice as fast in industries that are the most exposed to AI compared to the industries least exposed.
3. Job Numbers
Myth: AI may lead to a decrease in job numbers. The report found that while occupations with lower exposure to AI saw strong job growth at 65% between 2019 and 2024, growth remained robust — albeit slower — even in occupations more exposed to the technology (38%).
4. Inequality
Myth: AI may exacerbate inequalities in opportunities and wages for workers. Contrary to fears that AI will worsen inequality, the report findings show that wages and employment are rising for jobs that are augmentable and automatable by the technology. The report noted that employer demand for formal degrees is declining faster in AI-exposed jobs, creating broader opportunities "for millions".
5. Skills
Myth: AI may "deskill" jobs that it automates. The report found that instead, AI can enrich automatable jobs by freeing up employees from tedious tasks to practice more complex skills and decision making. For example, data entry clerks can evolve into a "higher value" role such as data analysts, according to PwC.
6. Automation
Myth: AI may devalue jobs that it highly automates. The data shows that not only are wages rising for jobs that are highly automatable, but the technology is also reshaping these jobs to become more "complex and creative," and ultimately, make people more valuable.
Could 'gentler' job growth be helpful?
The study offers another perspective: In a world where many countries have declining working-age populations, softening job growth in AI-exposed occupations could even "be helpful" and benefit such countries. The productivity boost by AI can actually create a "multiplier effect" on the available workforce and satisfy the gaps that companies might not have been able to be fill otherwise, as well as growth for businesses, said Atkinson. "It's a prediction supported already by the productivity data we're seeing," he added. "I think it could absolutely and will be a good thing."
It is critical to avoid the trap of low ambition. Instead of limiting our focus to automating yesterday's jobs, let's create the new jobs and industries of the future. PwC's 2025 AI Jobs Barometer
| 2025-06-06T00:00:00 |
2025/06/06
|
https://www.cnbc.com/2025/06/06/ai-makes-workers-more-valuable-not-less-according-to-new-report.html
|
[
{
"date": "2025/06/06",
"position": 71,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 75,
"query": "AI employment"
},
{
"date": "2025/06/06",
"position": 14,
"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 71,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 63,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 13,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/06",
"position": 14,
"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 69,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 12,
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},
{
"date": "2025/06/06",
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"query": "AI impact jobs"
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{
"date": "2025/06/06",
"position": 65,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 93,
"query": "AI employment"
},
{
"date": "2025/06/06",
"position": 11,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 69,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 13,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/06",
"position": 67,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 64,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 79,
"query": "AI employment"
},
{
"date": "2025/06/06",
"position": 67,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 16,
"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 14,
"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 7,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 11,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/06",
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{
"date": "2025/06/06",
"position": 71,
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{
"date": "2025/06/06",
"position": 70,
"query": "artificial intelligence employment"
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{
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"query": "artificial intelligence workers"
},
{
"date": "2025/06/06",
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"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 67,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 14,
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{
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"position": 70,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 67,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 11,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/06",
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"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 69,
"query": "AI employment"
},
{
"date": "2025/06/06",
"position": 12,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 70,
"query": "AI workers"
},
{
"date": "2025/06/06",
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"query": "artificial intelligence workers"
},
{
"date": "2025/06/06",
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"query": "AI employment"
},
{
"date": "2025/06/06",
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{
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"position": 69,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 65,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 7,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 70,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 75,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 17,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/06",
"position": 14,
"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 16,
"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 12,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 71,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 87,
"query": "AI employment"
},
{
"date": "2025/06/06",
"position": 67,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 63,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 13,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/06",
"position": 14,
"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 11,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 69,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 16,
"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 71,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 98,
"query": "AI employment"
},
{
"date": "2025/06/06",
"position": 25,
"query": "AI impact jobs"
},
{
"date": "2025/06/06",
"position": 66,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 65,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 70,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 61,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 46,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 66,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 45,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 71,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/06",
"position": 61,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 72,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 11,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/06",
"position": 11,
"query": "AI wages"
},
{
"date": "2025/06/06",
"position": 7,
"query": "AI workers"
},
{
"date": "2025/06/06",
"position": 12,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/06",
"position": 11,
"query": "artificial intelligence workers"
}
] |
Will AI improve or eliminate jobs? It depends on who you ask.
|
Will AI improve or eliminate jobs? It depends on who you ask.
|
https://www.hbs.edu
|
[] |
Altman predicted some people will work "better and faster" with AI, though some will see their jobs "totally go away," and new roles will evolve ...
|
Experts inartificial intelligence and economics say the technology could reshape the labor market, but how disruptive it will be is still unclear. Even if AI isn't as radical a shift as some predict, it's still likely to benefit the business leaders and individual workers who best learn to apply it.
BOSTON — Experts on artificial intelligence and the economy have a wide range of predictions about the impact of AI systems on the labor market.
On the pessimistic side, economist Anton Korinek predicted during a recent interview with Harvard Business School's Institute for the Study of Business in Global Society (BiGS) that AI systems could soon be powerful enough to replace large swaths of human labor.
“That means human workers, including you and me, we would become easily substitutable by AI," said Korinek, a professor at the University of Virginia.
Korinek predicted that so-called artificial general intelligence (AGI), AI systems with thinking capabilities similar to or greater than humans, could be achieved within as few as five years. That, he warned, could throw the economic and social order into a tailspin, driving down human wage levels and requiring new systems for ensuring income within the economy. “Whenever that happens, then the economic, the social, the political implications are just going to be severe,” he said.
Korinek isn't alone in sounding warnings about the potential dire consequences of the AI technology that's taken the world by storm since OpenAI launched ChatGPT in late 2022.
However, more optimistic experts say that it may take a long time before AI supplants humans in a wide range of fields — if it ever does — and that for the foreseeable future, the technology may be more likely to supplement human labor and creativity. Many say it may even create new types of jobs.
“In every technological revolution, people predict the end of jobs, and it never happens,” OpenAI cofounder and CEO Sam Altman said during a May 2024 appearance at Harvard. “I don't think [it] will happen this time, but [jobs] will change.”
Working ‘better and faster’
Altman predicted some people will work "better and faster" with AI, though some will see their jobs "totally go away," and new roles will evolve. That's similar to the effect of previous technologies, from the car to the internet.
Another expert thinks that AI will augment human creativity. Oren Etzioni, the founding CEO of the Allen Institute for Artificial Intelligence (Ai2) and a University of Washington professor emeritus of computer science, said during a recent BiGS interview, "Writers, artists, many of us are using it to become more productive and more creative.”
The technology can even help save lives, Etzioni said, by aiding in scientific research and helping humans with risky endeavors — from driving to medicine — although building in proper safeguards and human overrides may be key.
AI's effect is already visible in fields such as computer programming. Microsoft CEO Satya Nadella recently said that 20% to 30% of code for some company projects is now created with AI. Across the industry, developers increasingly embrace "vibe coding," a term for trusting in AI to generate sections of simpler code.
Still, Etzioni said, human coders aren't going to disappear, because even the best AI can't generate "complex, original programs" on their own. "Coding is not going to disappear, but it's going to be on steroids," he said.
‘No significant impact’ yet
So far, studies indicate AI doesn't appear to be widely eliminating white-collar work. One recent paper by scholars at the University of Chicago and the University of Copenhagen looked at 25,000 workers in Denmark, which the authors say has AI uptake that is similar to that in the U.S. They found “no significant impact on earnings or recorded hours in any occupation,” although the technology did bring modest productivity gains, and even new work tasks, to some.
Labor effects may increase as companies become more adept at deploying AI and the technology continues to improve, with some recent research suggesting that employers are still determining exactly how to use the technology. One study of an online freelance marketplace, where the research authors suggested that changes in labor demand may be reflected before it is seen in full-time employment, found declines in demand for work in writing and translation. Meanwhile, demand soared for AI-related tasks, such as machine-learning coding and AI-powered chatbot development.
Similarly, a January 2025 report by freelancing platform Upwork found demand for annotation and labeling work, needed to prep data for use by AI, up by 220% year-over-year.
“We’re also seeing rapid growth in human-centric roles like career coaching and training,
which are up 74% year-over-year,” Kelly Monahan, managing director of the Upwork Research Institute, wrote in an email. "These roles are critical as businesses realize that thriving in the age of AI isn’t just about building the tech; it’s about helping people adapt to it."
Advice: ‘Be proactive’ in harnessing AI
Still, Monahan acknowledged, AI may impact some jobs. “As with any technological shift, we expect human workers to transition toward more complex tasks that command higher wages, while simpler, more repetitive work will face higher risk of disruption from AI,” she wrote.
What remains to be seen is exactly how severe that disruption may be, and how readily workers can shift into roles enhanced by AI or that the technology simply can't do. Also unclear is the extent to which expected productivity gains from AI translate into greater wages, or shorter hours at comparable pay, for the average worker.
Zoom CEO Eric Yuan recently predicted that humans may soon only need to work a four-day work week, thanks to AI help. But both Korinek and Altman have suggested new government policies, such as a guaranteed universal basic income, might be needed to ensure everyday people share in AI-driven prosperity. If it's done right, “we can improve the standard of living for people more than we ever have before,” Altman wrote back in 2021.
Even without such drastic changes or interventions, AI may be poised to shift how many work — and to bring disproportionate benefit to business leaders and workers who figure out how best to harness the technology.
“The reason that I advocate using AI at work is that you won't be replaced by an AI system, but you might be replaced by a person who uses AI better than you,” Etzioni said. “So be proactive and up level your work with AI.”
| 2025-06-06T00:00:00 |
https://www.hbs.edu/bigs/will-artificial-intelligence-improve-or-eliminate-jobs
|
[
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{
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{
"date": "2025/06/06",
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},
{
"date": "2025/06/06",
"position": 85,
"query": "AI employers"
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{
"date": "2025/06/06",
"position": 2,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/06",
"position": 23,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/06",
"position": 43,
"query": "artificial intelligence employment"
}
] |
|
Fear of Job Losses Rise Amid AI Adoption - AAF
|
Fear of Job Losses Rise Amid AI Adoption
|
https://www.americanactionforum.org
|
[
"Fred Ashton",
"Douglas Holtz-Eakin"
] |
Yes, it is likely that the increased adoption of AI will cause structural friction in the labor market and lead to job losses. Perhaps entire ...
|
The Daily Dish
Fred Ashton
An opening line from a 1982 New York Times article discussing the impact of computers on the job market reads: “As new computer-based technologies are installed to improve productivity and reduce labor costs, there is growing concern about whether the nation will create the number of jobs it needs.” Similar warnings dominate the headlines today, this time about artificial intelligence (AI).
Recently, AI development firm Anthropic’s CEO Dario Amodei forecasted that AI could wipe out roughly 50 percent of all entry-level white-collar jobs and cause unemployment to spike as high as 20 percent. The fear of job displacement amid technological advancements is nothing new, but the often-bleak forecasts of mass job losses rarely fully materialize.
Yes, it is likely that the increased adoption of AI will cause structural friction in the labor market and lead to job losses. Perhaps entire occupations will disappear, just as the computer eliminated the need for keypunch operators. Yet what is often overlooked is how new technologies tend to create entirely novel industries and occupations, reshape existing jobs, and generate demand for new, more productive skills. Newly minted lawyers, for example, may no longer be needed to perform the mundane task of writing simple contracts. AI can do this in a matter of minutes. But their skills could be put to more productive use that creates greater value for clients. Moreover, firms planning for the long term would be unlikely to slash entry-level work on the scale predicted by Amodei as these workers will eventually be needed to fill more senior roles. Instead, firms would likely adjust their demand for skills. From a macroeconomic perspective, AI promises to provide a boost to productivity and growth, fueling the overall demand for labor.
The use cases for AI are still largely unknown. Some cannot yet be imagined. But just like the computer and previous technological advancements, AI could usher in a productivity boom that leaves workers better equipped to serve their customers and for entire new industries and occupations to be created.
Freddy’s Forecast: May Jobs
The April jobs report showed employers added 177,000 new hires to their payrolls while the unemployment rate was unchanged at 4.2 percent. Average hourly earnings rose by 6 cents, or 0.2 percent for an annual gain of 3.8 percent.
May data from payroll processor ADP showed that hiring continued to slow. Private payrolls expanded by just 37,000 during the month, down from a revised 60,000 in April. The manufacturing sector shed 3,000 jobs while tariff uncertainty weighed on the trade, transportation, and utilities sector, which cut 4,000 positions. The professional and business services cut 17,000 workers, and education and health services, which has been a leader in job growth, slashed 13,000.
The Federal Reserve’s Beige Book – which gathers anecdotal evidence on current economic conditions throughout the 12 Federal Reserve Districts – reported on June 4 that employment was little changed from the prior survey published on April 23. According to the report, all Districts described lower labor demand, declining hours worked and overtime, hiring pauses, and staff reduction plans.
Various indicators from the JOLTS report showed signs of stabilizing in recent months. The pace of hiring, which had been on a downward trend since early 2022, has largely leveled off since September 2024. The level of quits has followed a similar pattern. The break in the downtrend suggests that the labor market may be returning to its normal churn.
High frequency jobless claims data have trended higher over the past few months. The last two reports have lifted initial jobless claims from 226,000 to 247,000 as of May 31. Continuing claims remained above 1.9 million for the past two weeks, suggesting it is increasingly difficult to find a job.
For the May report, expect topline payroll growth of 120,000, a downshift from the three-month average of 155,000 as employers remained cautious amid tariff and other economic uncertainty. Expect the unemployment rate to tick up to 4.3 percent, which would be the highest level since October 2021, while growth in average hourly earnings rises to 0.3 percent.
| 2025-06-06T00:00:00 |
https://www.americanactionforum.org/daily-dish/fear-of-job-losses-rise-amid-ai-adoption/
|
[
{
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"position": 58,
"query": "AI job creation vs elimination"
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{
"date": "2025/06/06",
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{
"date": "2025/06/06",
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"query": "AI unemployment rate"
},
{
"date": "2025/06/06",
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"query": "AI unemployment rate"
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{
"date": "2025/06/06",
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{
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|
AI Recruiting in 2025: The Definitive Guide - Phenom
|
The Ultimate 2025 AI Recruiting Guide: Save Time, Hire Smarter, Stay Ahead
|
https://www.phenom.com
|
[] |
With AI automating repetitive tasks, from resume screening to interview scheduling, recruitment cycles become significantly shorter. This not ...
|
Artificial intelligence (AI) is proving its worth to recruitment teams by providing benefits like efficiency, personalization, and data-informed decision making. 76% of companies predict that their organizations will implement AI technology within the next 12–18 months to stay competitive, according to Gartner .
Not only has AI augmented the relationship between people and technology, it’s also changed the role of HR when attracting, engaging, hiring, and retaining talent.
The modern workforce is starting to grasp the power of AI, but conversations about using AI-driven technology in recruitment effectively can vary, even for seasoned HR professionals.
In this guide, we’re removing the complexity from the equation, adding clarity to the role AI plays in recruiting activities, and providing straightforward information on AI's positive impact on HR and TA teams (and in turn, the entire organization).
This guide will help you:
Better understand AI and its effects on talent acquisition
Leverage AI benefits and overcome key recruiting challenges
Discover essential AI-powered technology that will make life easier for recruiters — and candidates
Preview the future of what AI holds for recruiting In This Article
What is AI for Recruiting?
AI recruiting is the process of using artificial intelligence (AI) to augment and automate manual, repetitive tasks while offering personalization and data insights throughout the hiring process. AI is the science of training machines to simulate human intelligence and develop systems that can perform tasks that typically require human intelligence.
For instance, many industries have applied AI to quickly process large amounts of data to improve efficiency, accuracy, and productivity. In its simplest terms, AI leverages automation but adds intelligence — learning, reasoning, and adapting — to solve complex, repeatable problems with quality results
Better screening. Better interviews. Discover the smarter way to assess candidates.
Similar automation capabilities and benefits can be applied to recruiting, especially for repetitive, high-volume hiring processes such as sourcing, screening, scheduling, and interviewing. AI-powered technology is meant to speed up time-consuming manual processes so recruiters can focus on more valuable human-initiatives; AI is not meant to replace human recruiters — despite what some resistors might believe.
Recruiting AI enables talent acquisition teams to discover passive candidates and unlock data-driven insights that guide decision-making and better outcomes, such as quality of hire. This implementation paves the way for AI recruiting assistants that are interwoven into AI recruitment tools that deliver the right jobs to the right talent while building the right teams for the company.
Resource: How Recruitment Leaders can Leverage AI to Supercharge the Candidate Experience
The Difference Between Artificial Intelligence & Machine Learning
The terms artificial intelligence (AI) and machine learning (ML) are often used interchangeably, but there's a key difference between the two concepts : machine learning is actually a subset of artificial intelligence. Recruiters will find familiarity with the basic differences to be helpful in their jobs.
While artificial intelligence allows machines to make decisions and solve complex problems, ML is the process of making machines “intelligent” by feeding them data sets and specific examples. From that information, the machines can learn to detect nuances and patterns on which to base informed decisions. In short: AI is the goal, and ML is one of the ways to achieve it.
Catch the full conversation on AI for recruiting in this episode of Talent Experience Live >
Why is AI Important for Recruiting?
From a broad-brush perspective, artificial intelligence in hiring processes improve efficiency through intelligence and automation of tedious tasks — freeing recruitment teams up to focus more on strategic, big-picture goals. When you get AI right, it blends into the background and is there for support. It’s also important to note that these tools should be considered as an AI recruiting assistant or advisor to recruiters — it does not replace the need for human interaction during the recruitment process.
As recruiting AI continues to become more mainstream and the market becomes increasingly competitive, TA leaders need to consider integrating AI-powered recruiting software to thrive in an environment where working faster and smarter is a requisite.
AI tools can also help drive better TA outcomes by enabling high-level personalization and data insights.
Related: Should I Apply Automation, Intelligence, or Both? How Job Zones Can Help HR.
AI as a Strategic Partner in Proactive Recruitment
AI’s real power lies in its ability to shift recruitment from a reactive process to a proactive strategy. With predictive capabilities, AI can surface high-potential candidates before they even apply, helping recruiters engage talent earlier and more meaningfully. Instead of waiting for the perfect resume to land in their inbox, recruiters are now empowered with data-driven insights to identify and connect with best-fit candidates, ultimately reducing hiring costs, improving time-to-fill, and creating the gold standard in candidate experiences.
AI + Automation: Work Smarter, Not Harder
Recruiters are constantly under pressure to do more with less — and AI-powered tools make it possible. By automating time-consuming, manual tasks, AI frees up recruitment teams to focus on strategic initiatives. For example:
Sourcing: AI-powered matching and scoring capabilities identify the best-fit candidates automatically.
Screening: Candidates are ranked based on predefined criteria to streamline shortlisting.
Scheduling: AI chatbots and calendar integrations coordinate interviews efficiently.
With recruiters spending up to 30 hours a week on sourcing alone , automation isn’t just helpful — it’s changing the game.
Related: AI in Action: 5 Industry Leaders Reveal How AI is Transforming Talent Acquisition and Management
AI + Personalization: Delivering Tailored Talent Experiences
Exceptional talent experiences begin with relevance. AI enables personalization throughout the entire talent lifecycle:
Candidates receive customized job recommendations and content based on their profile, search behavior, and preferences
Employees benefit from AI-driven career pathing, alumni network connections, and internal mobility opportunities
Recruiters gain personalized talent pipelines with suggested matches based on compatibility and historical success
This level of personalization improves engagement, builds loyalty, and helps move talent faster through the funnel.
AI + Data Insights: Better Information, Better Decisions
Talent leaders have long struggled with data quality and reliability. AI recruiting insights empower recruiters and talent acquisition professionals with the right information they need to hire best-fit talent faster:
Discover new passive candidates and rediscover existing candidates
Understand candidate intent and behavior through collection of behavioral signals across the candidate journey
Tap into market trends and cloud-based suggestions
Monitor pipeline health and talent pool dynamics
With this intelligence, recruiters can spend more time on high-value interactions, reducing time to hire and cost per hire while improving quality of hire.
AI + Bias Control: Supporting Diversity and Inclusion
AI also plays a vital role in promoting fair and inclusive hiring practices. By transparently grading candidates based on skills and experience — rather than demographic or background data — AI helps reduce unconscious bias. While AI must be implemented thoughtfully to avoid introducing new biases, when done right, it enhances an organization’s commitment to equitable hiring.
What are the Challenges of Applying AI in Recruiting?
HR and TA departments should be aware of a few hurdles in utilizing AI recruiting software AI can’t deliver real insights without reliable data to learn from. Understanding candidate intent and behavior starts with capturing clean, structured data across the entire talent journey. When that data is unified and accessible, AI can recognize patterns, predict intent, and personalize experiences, helping you identify who’s ready to apply, who needs nurturing, and where to focus your efforts. That’s why selection of the right platform is crucial.
Organizations should choose a technology partner whose platform is built to capture and connect data across every interaction — from sourcing and screening to engagement and interviewing. The right platform doesn’t just store information; it continuously learns from it, ensuring your AI models are fueled by accurate, up-to-date insights. This enables recruiters to make faster, smarter decisions while delivering more relevant, personalized experiences to every candidate.
Transparency and Trust in AI Recommendations. AI must move beyond “black box” decision-making by using explainable systems that clearly communicate why candidates are recommended, helping recruiters build trust, ensure fairness, and make confident, compliant hiring decisions.
Data Quality and Bias Detection. The effectiveness of AI in hiring hinges on clean, unbiased data; modern platforms must include ongoing bias detection and mitigation tools to prevent automation from reinforcing inequities in recruitment.
Legal, Ethical, and Organizational Considerations. As regulations evolve, organizations must proactively document AI decision-making, ensure ethical compliance, and prepare internal teams through transparency, education, and ethical alignment in AI-driven hiring practices.
Securing Buy-In. Adoption success depends on reframing AI as an enabler — not a replacement — by offering live demos, feedback loops, and empowering internal champions to drive a culture of learning, experimentation, and skill growth.
Related: Change Management Success: How NTT and QuantumWork Tackle HR Tech Change
What AI Recruiting Tools Are Available?
AI and machine learning help candidates, recruiters, employees, and management throughout their journey, enabling them to achieve their end goals faster. AI powers the following core functionalities:
Personalization delivers tailored content throughout the entire talent lifecycle. AI powers personalized experiences on company career sites by providing job recommendations and dynamic content based on a candidate’s profile, search history, similar job openings, and locations.
For employees, AI powers the same personalization features as external candidates within the talent marketplace, along with career pathing, learning and development opportunities, mentoring, and referrals.
For recruiters and management, AI powers a personalized pipeline with matching skills and compatibility so recruiters automatically discover new talent and rediscover past quality candidates. Plus, insights into interview performance can help organizations continuously improve their interview process.
Related: Humanizing Automation to Create a Personalized Talent Experience
Intelligent Search on a career site delivers accurate, relevant job results to help candidates find the right job. Search that provides irrelevant and inconclusive results leads to low talent conversion rates for organizations. Instead, search must be intelligent enough to understand the intent and context of a candidate’s inquiry, as well as the relationship between words. Also known as semantic search, this type of search functionality seeks to understand language the same way a human would.
The ability to match the right job to the right candidate is critical to converting top talent. AI powers spell correction, prediction, synonyms, and natural language processing in order to provide the most relevant search results.
Conversational HR chatbots that are powered by artificial intelligence help people find the best-fit job faster with personalized conversations, engagement, job searching, screening, and scheduling. Over 12 months, the Phenom chatbot engaged with 20 million candidates, learning from each interaction to deliver smarter, more personalized job recommendations using AI and machine learning.
Leveraging a rich database, the chatbot uses both natural language processing and natural language understanding to ensure it comprehends the intent behind a candidate’s question and serves accurate answers. In HR, this is a complicated matter. Recruiters empower the bot further by analyzing the job seekers’ conversations and supplying it with additional responses that satisfy their inquiries.
A talent CRM can build, engage, and track talent pipelines, as well as enhance productivity using dynamic lists, actionable insights, fit scoring, and more. It helps recruiters easily identify new talent and stay connected to top talent through the use of AI insights.
Interview scheduling automates the scheduling process for candidates, recruiters, hiring managers, and anyone else involved in the recruitment process by accessing hiring team members’ calendars and syncing their schedules so that candidates can easily choose a time for their interview that works best for all parties.
Related: What is an AI Scheduling Tool and What Are the Benefits?
Powered by the talent CRM, the process is seamless for both candidates and recruiters. All the candidate has to do is choose a time listed that works for them, and the interview is automatically scheduled. The interview then shows up on the hiring team’s calendar, omitting the typical back-and-forth communication that comes with manual interview scheduling.
Screening tools in the talent CRM can be configured so that manual phone screens can be eliminated and helps candidates receive a timely and great first impression with workflows that streamlines the screening process for recruiters and hiring managers.
Actionable Insights provide fit and engagement scoring, which allows teams to discover new job seekers, rediscover existing candidates, and view dynamic talent pools — relieving the longtime struggle that talent leaders have with data quality and reliability.
In addition, AI-powered solutions allow recruiters to spend more time with the most qualified candidates, reducing time-to-hire, cost-per-hire, and improving quality of hire. The evolution of AI hiring trends continues to expand as HR professionals discover new use cases and ways to streamline their day-to-day activities. For example, generative AI for HR is currently changing the game for users and technology vendors.
Related: Why ChatGPT Is NOT The Best GenAI Tool for HR (And What Is)
The Rise of Generative AI (GenAI) and AI Agents in Recruitment
GenAI has ushered in a new era of creativity and personalization in recruitment technology. Unlike traditional AI, which primarily focuses on analyzing and optimizing data, GenAI goes a step further — it creates. From generating personalized outreach messages to writing job descriptions and interview questions, GenAI enables recruitment teams to craft tailored candidate experiences at scale. It’s not just about identifying the right talent anymore; it’s about engaging them with the right message, at the right time.
Where traditional AI systems help automate repetitive tasks, GenAI acts as a creative partner, enhancing candidate engagement, reducing recruiter workload, and enabling faster, more meaningful connections throughout the hiring process.
How to Leverage GenAI in Recruitment
GenAI is transforming recruitment by streamlining processes, enhancing candidate engagement, and improving hiring decisions. Here’s how recruiters can harness its power effectively:
1. Automated Job Descriptions & Personalized Outreach
GenAI can generate compelling job descriptions tailored to specific roles, ensuring clarity and inclusivity. Additionally, it enables personalized candidate outreach by crafting custom messages based on a candidate’s skills, experience, and interests, leading to higher response rates.
2. AI-Powered Resume Screening & Matching
Manually sifting through resumes can be time-consuming. GenAI can analyze and rank candidates based on job requirements, identifying the best fits efficiently. It can also reduce bias by focusing on skills and experience rather than demographic factors.
3. Chatbots for Candidate Engagement
AI-driven chatbots can handle initial candidate interactions, answer FAQs, schedule interviews, and even conduct pre-screening assessments. This ensures a seamless experience for applicants while freeing up recruiters to focus on more strategic tasks.
4. Predictive Analytics for Better Hiring Decisions
By analyzing past hiring data, GenAI can predict which candidates are most likely to succeed in a role. It can assess cultural fit, performance potential, and even suggest areas for upskilling, helping recruiters make informed decisions.
5. Reducing Time-to-Hire
With AI automating repetitive tasks, from resume screening to interview scheduling, recruitment cycles become significantly shorter. This not only benefits hiring teams but also improves the candidate experience by reducing waiting times.
Introducing AI Agents: Automation Meets Intelligence
AI agents are the next evolution in recruitment technology. These agents don’t just respond to prompts — they reason, act, and collaborate across the entire talent lifecycle. Phenom X+ Agent Studio leads this innovation with zero-configuration AI agents powered by X+ Ontologies, a framework that standardizes and interprets enterprise-wide HR data to align talent strategies with business goals. Let’s take a closer look at how these systems work together to deliver intelligent, valuable, and efficient agents to support your TA teams at every stage in the hiring funnel.
Automation Engine: Driving Efficient Hiring Processes
Automation Engine serves as the foundation of intelligent hiring, career growth, and retention experiences. This backend powerhouse enables organizations to implement and monitor automation workflows within talent lifecycle processes. With Automation Engine you can:
Identify, build, implement, and monitor automation workflows in talent lifecycle processes
Drastically reduce time to hire and enhance the talent experience by automating tedious tasks and mitigate manual work like candidate sourcing, scoring, screening, and scheduling.
Deliver highly-personalized experiences for candidates, at scale
Improve efficiency, conversion rates and hire a higher volume of quality hires — fast!
Find your focus: Hire the right fit faster, and then repurpose your team’s energy to strategically acquire talent.
Talent Companion: Personalized Candidate Engagement
Talent Companion acts as an always-on, omnichannel AI recruiting assistant, enhancing candidate engagement throughout the hiring journey. Its capabilities include:
Job Discovery : Guides candidates towards finding the right role for them with flexible natural language understanding.
Real-Time Assistance: Provides instant responses to candidate queries, eliminating uncertainty.
Interview Preparation: Helps candidates get ready for interviews by offering guidance and reminders.
Streamlined Application Process: Ensures a frictionless experience by guiding candidates through each step of their journey.
Talent Experience Engine: Powering Data-Driven Talent Marketing
Talent Experience Engine takes recruitment marketing to the next level by leveraging artificial intelligence to create compelling and personalized candidate engagement strategies. With this tool, talent marketers can:
Generate Content at Scale: Phenom X+ automates creation of landing pages, emails, and SMS campaigns tailored to diverse audience segments.
Identify High-Performing Segments: Real-time data helps pinpoint the most relevant talent pools, optimizing targeting strategies.
Personalize Candidate Journeys: Data-driven insights allow for structured engagement plans, improving conversion and retention.
Automate Outreach: AI determines the best communication channels and timing to maximize impact and efficiency.
Phenom Hiring Intelligence sets itself apart by unifying screening, scheduling, interviewing, and evaluation into one seamless platform. Unlike disconnected solutions, Phenom delivers a continuous hiring experience that eliminates silos, enhances productivity, and simplifies even the most complex hiring processes. What truly distinguishes the platform is its ability to continuously optimize your interviewing team's performance through data-driven insights and coaching opportunities.
By providing actionable insights, automated workflows, and a fully integrated approach, organizations can accelerate time-to-hire, elevate quality of hire, and realize measurable cost savings — all while ensuring a consistent, efficient, and data-driven talent journey from start to finish.
X+ Agents: Elevating AI Capabilities in Recruiting
With Generative AI and AI Agents, Phenom revolutionizes HR processes. These AI-powered agents work collaboratively to complete tasks, anticipate challenges, and improve accuracy across hiring and retention workflows. By proactively refining prompts and enhancing decision-making, AI Agents augment recruiter efficiency and candidate engagement.
AI has transformed industries, and Phenom’s design-centric platform integrates intelligence to understand user and customer needs, replacing time-consuming manual work with automated and augmented processes. This shift empowers HR teams to be more productive and operational.
When HR teams effectively leverage data, integrations, automation, and AI, they can:
Enhance task effectiveness and processes
Identify and eliminate disruptions to productivity
Support various talent acquisition and management use cases
Related: Ethical AI Development: Balancing Innovation with Responsibility
How Will AI Change the Role of the Recruiter?
The evolution ofAI for recruiting is more accurately described as a human-centered approach that uses AI to enhance job performance. AI serves as the invaluable assistant you can’t live without — that never forgets a thing it’s “told.” In essence, AI and automation allow recruiters to evolve .
AI helps recruiters make more effective decisions quicker, and free them from humdrum and manual tasks. With better insights and more time at hand, the evolved recruiter will be able to:
Be more proactive . Rather than simply backfilling open job roles, AI will give recruiters the data insights – and enough time – to apply strategic hiring practices.
Focus on relationship-building. With more time back in their day, recruiters can dedicate more time with best-fit candidates, going deeper than a resume to determine culture fit and opportunities.
Align more closely with hiring managers. Recruiters use AI-driven visuals showing KPIs such as the quality of hire to educate hiring managers on outcomes.
By incorporating an AI recruiting assistant and leveraging artificial intelligence in hiring, recruiters can ensure the best talent is engaged and retained effortlessly.
Customer Spotlight: 1000+ Hires, 6 Weeks: Alight's High-Volume Automation Story
A Summary of Using AI in Recruiting
HR teams around the world have adapted their people strategies to address unprecedented change — but one thing is certain: technology is essential to the success of our teams, organizations, and millions of workers looking for the right job.
Artificial intelligence is here to support the talent experience in powerful ways — and we are only at the cusp of its potential. Now’s the time to embrace AI so that we may focus on what truly matters: building meaningful relationships with our candidates and employees.
AI is important in recruiting to help TA teams work more efficiently, deliver personalized and best-in-class candidate experiences, and attract and hire top talent.
Benefits include high-powered automation, insights to drive stronger personalization and decision-making, and bias control to ensure a fair and compliant hiring process..
Challenges lie in ensuring quality data to feed the system, securing user buy-in, and preventing existing biases from entering the system.
AI-driven recruiting tools include personalized job recommendations and generating content, intelligent search, chatbots, fit and engagement scoring, interview assistant, insights, candidate discovery, and AI agents.
AIhas evolved the recruiter role by freeing up manual work so that they can focus on relationship-building and proactive hiring strategies, and providing insights to drive hiring forward.
Enhancing the Talent Experience with Phenom AI
By connecting billions of data points and millions of interactions from candidates, recruiters, employees, and managers, Phenom AI is able to help candidates find and choose you faster, employees develop their skills and evolve, recruiters become wildly productive, managers build stronger-performing teams, HR aligns employee development with company goals, and HRIS creates a holistic tech infrastructure through seamless integrations.
Strategies include:
Personalized job recommendations for candidates and employees based on skills, experience, location, search history, and profile
Hyper-personalized content creation aligned to the candidate's talent journey, generate emails, structured interview guides, and candidate profile summaries.
Tailored referrals based on employer match, similar colleagues, alumni, and more
Intelligent search based on user intent and natural language processing
Conversational chatbot that sources, screens, and matches candidates with best-fit jobs
A talent CRM that builds, engages, and tracks talent pipelines, as well as enhances productivity using dynamic lists, actionable insights, fit scoring, and more
Automated Interview Scheduling to provide a seamless interviewing experience for candidates and recruiters
One-way video assessments to fast-forward the screening process for high-volume roles
Dynamic fit scoring to elevate best-fit candidates, enabling recruiters to fill roles faster
Job insights to discover and rediscover leads based on fit
Data-driven skills insights to drive employee learning, development, and career pathing
Interview Intelligence to continuously optimize your interviewing team's performance through data-driven insights and coaching opportunities.
Want to recruit like the best in the business? Download The Definitive Guide to AI for Recruiting and see how it’s done.
| 2025-06-06T00:00:00 |
https://www.phenom.com/blog/recruiting-ai-guide
|
[
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{
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},
{
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},
{
"date": "2025/06/06",
"position": 71,
"query": "job automation statistics"
}
] |
|
Generative AI and workforce transformation - TLT LLP
|
Generative AI and workforce transformation - 5 big questions with Sarah Skeen
|
https://www.tlt.com
|
[] |
As generative AI moves from experimentation to enterprise-scale adoption, the workplace is being reshaped. New requirements, new roles and ...
|
As generative AI moves from experimentation to enterprise-scale adoption, the workplace is being reshaped. New requirements, new roles and new risks are emerging and how businesses respond will have long-term consequences. We spoke with Sarah Skeen, Partner, in our Employment team, to explore five big questions clients are asking as they prepare for the future of work in an AI-driven world.
Key takeaways include:
HR and legal teams must be at the heart of AI strategy: As AI transforms how financial services operate, early and active involvement from HR and legal is essential to manage risks, shape inclusive deployment, and support long-term organisational change and not just technical implementation.
As AI transforms how financial services operate, early and active involvement from HR and legal is essential to manage risks, shape inclusive deployment, and support long-term organisational change and not just technical implementation. AI is reshaping roles, not just removing them: Rather than a story of job loss, AI is driving role evolution. Organisations need to focus on reskilling, redeployment and transparency to support workforce transitions, while addressing new legal and ethical responsibilities.
Rather than a story of job loss, AI is driving role evolution. Organisations need to focus on reskilling, redeployment and transparency to support workforce transitions, while addressing new legal and ethical responsibilities. Responsible AI demands a people-first mindset: Diversity, inclusion and fairness must be integrated into AI systems from the outset. That includes thoughtful governance of recruitment tools, awareness of bias in datasets, and ensuring workforce strategies align with broader organisational values.
1. What’s changing — and why does it matter now?
The biggest shift is how quickly AI is becoming embedded in business-as-usual processes. What started as isolated pilot projects has become a wave of transformation encompassing almost everything from recruitment and onboarding to workflow automation and performance management.
Businesses are realising AI isn’t just about technology, it’s about people, and the risks and opportunities go hand-in-hand. AI can unlock huge gains in efficiency and innovation, but only if organisations bring their workforce with them. Failing to address issues, such as capability gaps, transparency, and trust could slow adoption and create internal resistance at a time when speed and confidence are critical.
The organisations that get AI transformation right are those that treat workforce readiness as a strategic priority, not an afterthought.
2. What’s the opportunity and what should clients be cautious about?
AI offers the potential to elevate the workforce by reducing the burden of repetitive tasks and enabling employees to spend more time on complex and nuanced responsibilities. It can empower teams to move faster, analyse more data, and deliver more personalised client experiences. But that’s only half the story.
The risks are real. When AI tools are introduced without clear communication or sufficient support, employees can feel disempowered or even displaced. There are also legal and ethical pitfalls — from discriminatory hiring practices driven by biased training data to unclear decision-making in performance management tools.
Organisations need to move fast, but they also need to move carefully. That means engaging HR and legal teams early, building clear governance around AI use in people processes, and ensuring leadership is visible and aligned on the approach.
3. How are financial services organisations responding?
There’s a clear divide between the firms implementing AI and those that are still hesitant. Whilst some are already using AI to redesign roles, automate documentation, and support knowledge work. Others are in the early stages of developing internal guidance or forming cross-functional steering groups.
One of the most consistent themes is the need for clarity around roles and responsibilities. Who owns AI implementation from a workforce perspective? Where do HR, IT and legal functions intersect? How do you ensure your governance frameworks are future-proof — not just for today’s tools, but for tomorrow’s capabilities?
The most forward-thinking organisations are starting to treat AI deployment as a people strategy challenge as much as a technology challenge. That shift in mindset is where the real progress happens.
4. What are the most pressing legal and ethical issues?
AI creates a new layer of complexity in traditional employment law. If an AI tool is used to assess performance or inform disciplinary action, can its decision-making process be audited? What happens if a recruitment algorithm produces biased outcomes, even unintentionally? And who’s liable when automated systems lead to errors or oversights?
Transparency and accountability are the big themes here as they are in other areas such as data privacy. Employees — and regulators — will expect to understand how decisions are made and to see that fairness, diversity and inclusion have been meaningfully considered in AI system design.
There’s also a growing expectation that businesses will proactively assess the impact of AI on their workforce and take steps to mitigate harm — whether through reskilling, redeployment or robust consultation processes. It’s not just about legal compliance; it’s about reputation, retention, and long-term value.
5. How can businesses prepare their workforce for what comes next?
Preparing for the future means shifting from a reactive mindset to a proactive strategy. This starts with involving HR and legal at the outset — not once the technology is already live. It means designing implementation roadmaps that consider not just what AI can do, but what impact it will have on people, roles and culture.
Employees need to feel confident using AI, but also confident that their employer is using it responsibly. That trust takes time to build — and it starts with transparency.
As AI continues to evolve, the most resilient organisations will be those that keep workforce transformation tightly aligned with business strategy, ethics and regulation. They’ll see AI not as a threat to jobs, but as a catalyst for reinvention — and a reason to invest in their people like never before.
At TLT, we help you ask the right questions—so you can deliver the right solutions for your people and your business.
Download our AI Legal Playbook to stay ahead of the risks, regulations and opportunities shaping the future of financial services.
This publication is intended for general guidance and represents our understanding of the relevant law and practice as at June 2025. Specific advice should be sought for specific cases. For more information see our terms & conditions.
| 2025-06-06T00:00:00 |
https://www.tlt.com/insights-and-events/insight/generative-ai-and-workforce-transformation---5-big-questions-with-sarah-skeen/
|
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|
AI is accelerating workforce transformation – Are you prepared?
|
AI is accelerating workforce transformation – Are you prepared? — BrightBox Group
|
https://www.brightboxgrp.com
|
[
"Matthew Banks"
] |
AI is accelerating workforce transformation – Are you prepared? ... Once the preserve of science fiction, the age of artificial intelligence is ...
|
Once the preserve of science fiction, the age of artificial intelligence is very much upon us, and it is advancing at an astonishing rate. Today’s business and technology leaders are no longer questioning whether AI will transform how work is done, but how fast.
Skills that formed the bedrock of technical roles are now being redefined by machine learning models and intelligent tools, rendering static job descriptions almost obsolete. Indeed, if you’re not continuously adapting your team’s skills mix to match the demands of the AI age, you’re already falling behind.
As the gap between AI-driven organisations and the slow movers continues to widen at pace, the room for delay is vanishing. It’s the leadership decisions taken today that will determine your competitiveness tomorrow – and that tomorrow is actually tomorrow.
The speed of change
The rate at which AI is reshaping the nature of work is unprecedented. According to the World Economic Forum’s ‘Future of Jobs Report’, 44% of workers’ core skills are expected to change within the next five years. That’s nearly half the skillset of the average employee either evolved or automated.
However, new human roles are emerging just as quickly as skills are being commandeered by AI. Prompt engineering, for example, has become an essential discipline, while data annotation and LLM fine-tuning have become core tasks for AI operations.
Elsewhere, tools and techniques that mattered just a year or two ago are being replaced by entirely new approaches, sometimes in a matter of months. The expiration date of technical knowledge is shortening dramatically, with some estimates suggesting that the half-life of technical skills is now less than 2.5 years.
Skills aren’t just human anymore
Within AI-augmented workplaces across the globe, job roles are not fulfilled by human ability alone; they’re composite skill ecosystems where traditional coding, AI literacy, and adaptability must coexist.
Take software engineering as an example. A discipline once dependent on human knowledge of languages and frameworks has seen tools like GitHub Copilot and ChatGPT alter the rhythm of daily work. Developers are now learning to collaborate with models that autocomplete code, suggest design patterns, and explain unfamiliar syntax in real time.
And it’s a shift that goes beyond engineering. DevOps teams are automating infrastructure decisions using AI-powered observability tools, while in QA, testers are training models to identify potential regressions before they hit production. In all kinds of scenarios, adaptability is overshadowing expertise.
The cost of standing still
AI can be thought of as a tidal force; you can’t outswim it, but if you learn to ride the wave, the opportunities become vast. Teams that resist re-skilling will not only find that innovation slows; they’ll find that the resultant skills gap leads to considerable friction points in digital transformation. The inevitable result is that productivity dips, while competitors who embraced AI-first workflows surge ahead.
More critically, organisations risk falling foul of emerging compliance frameworks. As AI governance becomes more regulated, teams without foundational AI literacy may find themselves exposed to risk they can’t assess let alone mitigate.
It's not just internal teams this applies to either. Your suppliers and partners need to be fluent in this new operating environment, too, because if the ecosystem around you isn’t evolving, it’s your progress that stalls.
How prepared are you?
The checklist below can serve as a litmus test for your organisation’s readiness:
Are you mapping future skill requirements on a monthly or quarterly basis?
Can your teams upskill to meet new technical needs within 30 days?
Are you able to monitor the market to understand what new AI or human skills you should bring into your organisation in the next six months?
Are your workflows designed for AI-human collaboration, not just automation?
Answering “yes” to all four doesn’t mean the job is done, it just means you’re on the right path. Anything less should serve as a wake-up call.
Get ahead of the curve
It’s essential to move beyond viewing workforce transformation as a project and instead view it as a permanent condition. At BrightBox, we help businesses access AI-capable, pre-vetted talent across engineering, machine learning, cloud, and more.
Join our upcoming webinar to learn how leading CTOs are managing AI-driven change with confidence and speed. You’ll gain practical insight into skill-mapping frameworks, rapid upskilling strategies, and how to build AI-ready teams without starting from scratch.
| 2025-06-06T00:00:00 |
https://www.brightboxgrp.com/blog/ai-workforce-transformation
|
[
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},
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{
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},
{
"date": "2025/06/06",
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|
Generative AI and Workforce Transformation: 5 Big Questions
|
Generative AI and Workforce Transformation: 5 Big Questions
|
https://www.lexology.com
|
[] |
As generative AI moves from experimentation to enterprise-scale adoption, the workplace is being reshaped. New requirements, new roles and ...
|
As generative AI moves from experimentation to enterprise-scale adoption, the workplace is being reshaped. New requirements, new roles and new risks are emerging and how businesses respond will have long-term consequences. We spoke with Sarah Skeen, Partner, in our Employment team, to explore five big questions clients are asking as they prepare for the future of work in an AI-driven world.
Key takeaways include:
HR and legal teams must be at the heart of AI strategy: As AI transforms how financial services operate, early and active involvement from HR and legal is essential to manage risks, shape inclusive deployment, and support long-term organisational change and not just technical implementation.
As AI transforms how financial services operate, early and active involvement from HR and legal is essential to manage risks, shape inclusive deployment, and support long-term organisational change and not just technical implementation. AI is reshaping roles, not just removing them: Rather than a story of job loss, AI is driving role evolution. Organisations need to focus on reskilling, redeployment and transparency to support workforce transitions, while addressing new legal and ethical responsibilities.
Rather than a story of job loss, AI is driving role evolution. Organisations need to focus on reskilling, redeployment and transparency to support workforce transitions, while addressing new legal and ethical responsibilities. Responsible AI demands a people-first mindset: Diversity, inclusion and fairness must be integrated into AI systems from the outset. That includes thoughtful governance of recruitment tools, awareness of bias in datasets, and ensuring workforce strategies align with broader organisational values.
1. What’s changing — and why does it matter now?
The biggest shift is how quickly AI is becoming embedded in business-as-usual processes. What started as isolated pilot projects has become a wave of transformation encompassing almost everything from recruitment and onboarding to workflow automation and performance management.
Businesses are realising AI isn’t just about technology, it’s about people, and the risks and opportunities go hand-in-hand. AI can unlock huge gains in efficiency and innovation, but only if organisations bring their workforce with them. Failing to address issues, such as capability gaps, transparency, and trust could slow adoption and create internal resistance at a time when speed and confidence are critical.
The organisations that get AI transformation right are those that treat workforce readiness as a strategic priority, not an afterthought.
2. What’s the opportunity and what should clients be cautious about?
AI offers the potential to elevate the workforce by reducing the burden of repetitive tasks and enabling employees to spend more time on complex and nuanced responsibilities. It can empower teams to move faster, analyse more data, and deliver more personalised client experiences. But that’s only half the story.
The risks are real. When AI tools are introduced without clear communication or sufficient support, employees can feel disempowered or even displaced. There are also legal and ethical pitfalls — from discriminatory hiring practices driven by biased training data to unclear decision-making in performance management tools.
Organisations need to move fast, but they also need to move carefully. That means engaging HR and legal teams early, building clear governance around AI use in people processes, and ensuring leadership is visible and aligned on the approach.
3. How are financial services organisations responding?
There’s a clear divide between the firms implementing AI and those that are still hesitant. Whilst some are already using AI to redesign roles, automate documentation, and support knowledge work. Others are in the early stages of developing internal guidance or forming cross-functional steering groups.
One of the most consistent themes is the need for clarity around roles and responsibilities. Who owns AI implementation from a workforce perspective? Where do HR, IT and legal functions intersect? How do you ensure your governance frameworks are future-proof — not just for today’s tools, but for tomorrow’s capabilities?
The most forward-thinking organisations are starting to treat AI deployment as a people strategy challenge as much as a technology challenge. That shift in mindset is where the real progress happens.
4. What are the most pressing legal and ethical issues?
AI creates a new layer of complexity in traditional employment law. If an AI tool is used to assess performance or inform disciplinary action, can its decision-making process be audited? What happens if a recruitment algorithm produces biased outcomes, even unintentionally? And who’s liable when automated systems lead to errors or oversights?
Transparency and accountability are the big themes here as they are in other areas such as data privacy. Employees — and regulators — will expect to understand how decisions are made and to see that fairness, diversity and inclusion have been meaningfully considered in AI system design.
There’s also a growing expectation that businesses will proactively assess the impact of AI on their workforce and take steps to mitigate harm — whether through reskilling, redeployment or robust consultation processes. It’s not just about legal compliance; it’s about reputation, retention, and long-term value.
5. How can businesses prepare their workforce for what comes next?
Preparing for the future means shifting from a reactive mindset to a proactive strategy. This starts with involving HR and legal at the outset — not once the technology is already live. It means designing implementation roadmaps that consider not just what AI can do, but what impact it will have on people, roles and culture.
Employees need to feel confident using AI, but also confident that their employer is using it responsibly. That trust takes time to build — and it starts with transparency.
As AI continues to evolve, the most resilient organisations will be those that keep workforce transformation tightly aligned with business strategy, ethics and regulation. They’ll see AI not as a threat to jobs, but as a catalyst for reinvention — and a reason to invest in their people like never before.
| 2025-06-06T00:00:00 |
https://www.lexology.com/library/detail.aspx?g=4aeb7416-0327-44b3-96f7-ca2adfdda382
|
[
{
"date": "2025/06/06",
"position": 73,
"query": "AI workforce transformation"
},
{
"date": "2025/06/06",
"position": 75,
"query": "AI workforce transformation"
},
{
"date": "2025/06/06",
"position": 83,
"query": "AI workforce transformation"
},
{
"date": "2025/06/06",
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"query": "AI workforce transformation"
},
{
"date": "2025/06/06",
"position": 83,
"query": "AI workforce transformation"
},
{
"date": "2025/06/06",
"position": 74,
"query": "AI workforce transformation"
},
{
"date": "2025/06/06",
"position": 75,
"query": "AI workforce transformation"
},
{
"date": "2025/06/06",
"position": 74,
"query": "AI workforce transformation"
}
] |
|
International Coalition Of Worker Unions Declares Emergency Over ...
|
International Coalition Of Worker Unions Declares Emergency Over AI Use In Animation
|
https://www.cartoonbrew.com
|
[
"Amid Amidi",
"More Articles",
"Cartoon Brew Connect",
"Jamie Lang",
"Chris Robinson"
] |
A collective of international animation unions, federations, and organizations are calling for action over the usage of artificial intelligence.
|
A collective of international animation unions, federations, and organizations are calling for action over the usage of artificial intelligence, citing its destructive impact on the craft and business of animation, as well as on industry workers.
The coalition of organizations, numbering over two dozen in total, have issued a statement (read it in full below) that calls on regulators and lawmakers to enact legislation that protects workers and their rights. They are also asking producers, showrunners, and industry executives to protect the creative culture of animation and prioritize workers and the work created by humans.
Organizations that have signed and support the statement include ABRACA (animation workers union, Belgium), AWI (animation workers union, Ireland), CSVI (video game union, Spain), La Guilde française des scénaristes (writers union, France), SNTPCT (animation/vfx workers union, France), FIM (International Federation of Musicians), The Animation Guild (animation workers union, U.S.), SPIAC-CGT (animation workers union, France), and Kunstenbond (illustration, comic, and animation workers union, Netherlands).
In addition to the statement, the coalition is inviting all animation workers, students, and allies who are attending Annecy next week, as well as press and media, to a public townhall. It will take place 2pm on Thursday, June 12, at the Pâquier, which is the big, flat esplanade in front of the Bonlieu. See map below for the meeting location:
Here is the coalition’s full statement on artificial intelligence:
Animation industry in danger: World unions declare emergency in the face of generative AI use
It is an undeniable fact that the animation industry has been suffering greatly these last few years. The economics of streaming have been proven to be not at all lucrative and the increased spending during the pandemic led to the unavoidable burst of the streaming bubble. It is the workers that were staffed up with false promises that are feeling the repercussions through mass layoffs, the increased use of outsourcing, mergers and acquisitions that lead to the closure of studios and ever decreasing budgets. This echoes across multiple audiovisual entertainment industries and affects workers in animation, music, VFX and the gaming industry.
The rapid expansion of Generative AI in animation is propelled by the perceived beliefs that it is the answer to these developments. To work in these industries is a constant battle to prove our economic worth to a very small number of people, and to those people genAI brings an offer too good to be true: a near magical machine that can produce words and images from a simple and vague description.
Generative AI is neither a tool, nor effective, nor cheap. It is a copying machine that is flawed, destructive and expensive to run. GenAI literally builds upon and draws not only from the copyrighted works it was trained on, but also from the local human cultural values and norms embedded within those works. It poses an immediate threat to creative innovation and renewal, replacing the richness and diversity that characterize human creativity with a creativity shaped by the biases of those controlling and using it. It actively pushes creatives out of their respective industries, which will not only lead to the inevitable loss of knowledge and talent that will never be recuperated fully, but also directly leads to the privatisation of all art process and thinking.
GenAI is a technology that seeks not to support artists, but to destroy them. The absence of humans is a feature, not a bug, of AI art. It is not a tool. We do not “use” genAi – we negotiate with it to try and make it do the things we want it to do. GenAI promises only the loss of employment and livelihood for the millions of people worldwide that work at keeping the world connected through their art.
Unfortunately, the audiovisual industry is not the only victim of this increasingly damaging tech development. This same technology is being used to foster dissent, confusion and distrust among the public and has wide-ranging implications beyond international security, including the fabrication of criminal evidence and news, new forms of sexual harassment including deepfake pornography and/or privacy violations.The computational power required to train and use generative AI models demands a staggering amount of electricity and water which directly strains municipal water supplies and disrupts local ecosystems. This unchecked growth and unjustified techno-optimism comes with incredible environmental consequences, including expanding demand for computing power, larger carbon footprints, shifts in patterns of electricity demands and an accelerated depletion of natural resources, additionally exploiting without any respect for human rights.
As such, there is a need for protection frameworks around the ethical and fair use of AI. For this we refer to the research brief of the International Labour Organization (ILO) which proposes the concept of “3Cs” (compensation, control on the use of the work of the creator, informed consent), but also for policies, nationally and internationally, to manage workforce transition through skills development, as well as the use of social protection to support workers affected by AI.
Consent: A reasonable balance between on the one hand technological innovation and on the other hand a sustainable and strong cultural and creative sector, requires that training AI with copyright-protected works should only be possible with the (informed) consent of the author(s) of those works.
A reasonable balance between on the one hand technological innovation and on the other hand a sustainable and strong cultural and creative sector, requires that training AI with copyright-protected works should only be possible with the (informed) consent of the author(s) of those works. Compensation: Performers and creators should be fairly compensated for the use of their work including but not limited to illustrations, animations, writing, voicework, likeness, or image, in AI generated content.
Performers and creators should be fairly compensated for the use of their work including but not limited to illustrations, animations, writing, voicework, likeness, or image, in AI generated content. Controls: Creators — such as writers, musicians, filmmakers, visual artists, and other professionals — need to be able to govern how their works, identities, and creative inputs are used, adapted, or reproduced by AI systems. This control ensures that the creators’ intellectual property (IP), labour, and reputations are respected and that they receive fair recognition and compensation. In order for this to be realized, creators need to have an understanding on what AI – and particularly GenAI – entails; it is also necessary to build agency among them to negotiate relevant employment conditions.
We call upon the regulators, lawmakers and governments to fight for culture and art and the value it provides, to draft and implement legislation that protects those workers and those rights.
We call upon producers, showrunners, studioheads and production staff to understand and protect our creative culture and to prioritize both the workers and our work.
We call upon all creative workers worldwide to unite. We ask that you support human made works. We ask that you speak up against the implementation of AI. We ask that you become informed and unionise with your fellow workers to protect our art and culture, our work and our livelihood.
| 2025-06-07T00:00:00 |
2025/06/07
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https://www.cartoonbrew.com/artist-rights/an-international-coalition-of-worker-unions-declares-emergency-over-ai-use-in-animation-247671.html
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[
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"date": "2025/06/06",
"position": 55,
"query": "AI labor union"
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"date": "2025/06/06",
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"date": "2025/06/06",
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"query": "AI labor union"
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"date": "2025/06/06",
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"position": 65,
"query": "AI labor union"
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"date": "2025/06/06",
"position": 16,
"query": "artificial intelligence labor union"
}
] |
Proposed State AI Rule Ban Could Alter Employer Compliance
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Proposed State AI Rule Ban Could Alter Employer Compliance
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https://www.law360.com
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[
"Sign Up Now"
] |
A proposal in the congressional budget bill that would ban state and local enforcement of laws and regulations governing artificial ...
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Proposed State AI Rule Ban Could Alter Employer Compliance
By Amanda Blair, Benjamin Ebbink and Braden Lawes ·
The U.S. House of Representatives recently passed a sweeping proposal to impose a 10-year moratorium on state-level regulation of artificial intelligence — a move that could dramatically reshape the regulatory landscape for...
To view the full article, register now.
| 2025-06-06T00:00:00 |
https://www.law360.com/employment-authority/articles/2350396/proposed-state-ai-rule-ban-could-alter-employer-compliance
|
[
{
"date": "2025/06/06",
"position": 94,
"query": "AI regulation employment"
},
{
"date": "2025/06/06",
"position": 95,
"query": "AI regulation employment"
},
{
"date": "2025/06/06",
"position": 91,
"query": "AI regulation employment"
},
{
"date": "2025/06/06",
"position": 91,
"query": "AI regulation employment"
},
{
"date": "2025/06/06",
"position": 97,
"query": "AI regulation employment"
},
{
"date": "2025/06/06",
"position": 92,
"query": "AI regulation employment"
},
{
"date": "2025/06/06",
"position": 93,
"query": "AI regulation employment"
},
{
"date": "2025/06/06",
"position": 89,
"query": "AI regulation employment"
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{
"date": "2025/06/06",
"position": 90,
"query": "AI regulation employment"
},
{
"date": "2025/06/06",
"position": 91,
"query": "AI regulation employment"
}
] |
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AI risks 'broken' career ladder for college graduates, some experts say
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AI risks 'broken' career ladder for college graduates, some experts say
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https://abcnews.go.com
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[
"Abc News"
] |
Analysts who spoke to ABC News said AI could replace or reorient entry-level jobs in some white-collar fields targeted by college graduates, ...
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Artificial intelligence could upend entry-level work as recent college graduates enter the job market, eliminating many positions at the bottom of the white-collar career ladder or at least reshaping them, some experts told ABC News.
Such forecasts follow yearslong advances in AI-fueled chatbots, and declarations from some company executives about the onset of AI automation.
Dario Amodei, CEO of Anthropic, which created an AI model called Claude, told Axios last week that technology could cut U.S. entry-level jobs by half within five years.
When Business Insider laid off 21% of its staff last week, CEO Barbara Ping said the company would go "all in on AI" in an effort to "scale and operate more efficiently."
Analysts who spoke to ABC News said AI could replace or reorient entry-level jobs in some white-collar fields targeted by college graduates, such as computer programming and law.
Current job woes for this cohort, they added, likely owe in part to economic conditions beyond technology. Many blue-collar and other hands-on jobs will remain largely untouched by AI, they said, noting that tech-savvy young workers may be best positioned to fill new jobs that do incorporate AI.
"We're in the flux of dramatic change," said Lynn Wu, a professor of operations, information and decisions at the University of Pennsylvania. "I sympathize with college graduates. In the short run, they may stay with mom and dad for a while. But in the long run, they'll be fine. They're AI natives."
Over the early months of 2025, the job market for recent college graduates "deteriorated noticeably," the New York Federal Reserve said in April. It did not provide a reason for the trend.
The unemployment rate for recent college graduates reached 5.8%, its highest level since 2021, while the underemployment rate soared above 40%, the New York Fed said.
Youth unemployment likely stems from trends in the broader economy rather than AI, Anu Madgavkar, the head of labor market research at the McKinsey Global Institute, told ABC News
The softening job market coincides with business uncertainty and gloomy economic forecasts elicited by President Donald Trump's tariff policy.
"It's not surprising we're seeing this unemployment for young people," Madgavkar said. "There is a lot of economic uncertainty."
Still, entry-level tasks in white collar professions stand at serious risk from AI, analysts said, pointing to the technology's capacity to perform written and computational tasks as opposed to manual work.
Anthropic CEO Dario Amodei looks on as he takes part in a session on AI during the World Economic Forum (WEF) annual meeting in Davos, on Jan. 23, 2025. Fabrice Coffrini/AFP via Getty Images, FILE
AI could replace work previously performed by low-level employees, such as legal assistants compiling relevant precedent for a case or computer programmers writing a basic set of code, Madgavkar said.
"Is the bleeding edge or the first type of work to be hit a little more skewed toward entry-level, more basic work getting automated right now? That's probably true," Madgavkar said. "You could have fewer people getting a foothold."
Speaking bluntly, Wu said: "The biggest problem is that the career ladder is being broken."
For the most part, however, Madgavkar said entry-level positions would change rather than disappear. Managers will prize problem-solving and analysis over tasks dependent on sheer effort, she added, noting the required set of skills will likely include a capacity to use AI.
"I don't think it means we'll have no demand for entry-level workers or massively less demand," Madgavakar said. "I just think expectations for young people to use these tools will accelerate very quickly."
Some jobs and tasks remain largely immune to AI automation, analysts said, pointing to hands-on work such as manual labor and trades, as well as professional roles like doctors and upper management.
Isabella Loaiza, a researcher at the Massachusetts Institute of Technology who studies AI and the workforce, co-authored a study examining the shift in jobs and tasks across the U.S. economy between 2016 and 2024.
Rather than dispense with qualities like critical thinking and empathy, workplace technology heightened the need for workers who exhibit those attributes, Loaiza said, citing demand for occupations like early-education teachers, home health aides and therapists.
"It is true we're seeing AI having an impact on white-collar work instead of more blue-collar work," Loaiza said.
But, she added, "We found that jobs that are very human-intensive are probably more robust."
| 2025-06-06T00:00:00 |
https://abcnews.go.com/Business/ai-risks-broken-career-ladder-college-graduates-experts/story?id=122527744
|
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{
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"position": 88,
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},
{
"date": "2025/06/06",
"position": 58,
"query": "AI unemployment rate"
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"query": "AI impact jobs"
},
{
"date": "2025/06/06",
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"query": "AI replacing workers"
},
{
"date": "2025/06/06",
"position": 87,
"query": "AI replacing workers"
},
{
"date": "2025/06/06",
"position": 2,
"query": "AI unemployment rate"
},
{
"date": "2025/06/06",
"position": 12,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/06",
"position": 65,
"query": "artificial intelligence employment"
}
] |
|
Trump AI Czar on Universal Basic Income: 'It's Not Going to Happen'
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Trump's AI czar says UBI-style cash payments are 'not going to happen'
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https://www.businessinsider.com
|
[
"Lauren Edmonds"
] |
Trump's AI czar says UBI-style cash payments are 'not going to happen' · AI leaders like Elon Musk and Sam Altman have long called for a ...
|
This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now.
Americans probably won't be getting a universal basic income as long as President Donald Trump's AI czar has a say in the matter.
David Sacks, the cofounder of Craft Ventures and a member of the so-called "PayPal Mafia," which includes Elon Musk and Peter Thiel, is now a top White House policy advisor for AI.
It's an important role as rapid advances in AI bring about generational changes in how the world lives and works. The technology is already reshaping the job market, as chatbots like ChatGPT begin to do the work of entry-level employees.
Those at the forefront of the AI revolution have long warned about the risk AI poses to jobs, and have called for a universal basic income to soften the blow. A UBI is a government program that distributes no-strings-attached checks to all residents to spend how they please. Numerous cities and states are already experimenting with its humble cousin, a guaranteed basic income, which distributes checks to specific populations in need.
The idea has a long history, and support for these kinds of programs has skyrocketed at the local level in recent years. Any consideration of a basic income at the federal level, however, will likely have to wait. Sacks is not a fan.
The AI czar said on X this week that such government "welfare" is a "fantasy."
"The future of AI has become a Rorschach test where everyone sees what they want. The Left envisions a post-economic order in which people stop working and instead receive government benefits," Sacks wrote. "In other words, everyone on welfare. This is their fantasy; it's not going to happen."
Although reports from recipients who participate in basic income programs are overwhelmingly positive, they have faced political pushback.
Related stories Business Insider tells the innovative stories you want to know Business Insider tells the innovative stories you want to know
Last year, Republicans in Arizona voted to ban basic income programs in the state, and similar opposition efforts have gained traction in Iowa, Texas, and South Dakota. Lawmakers in several states have argued that the checks increase reliance on the government and dissuade recipients from working.
OpenAI CEO Sam Altman helped fund one of the largest basic income studies, which found, in part, that it encouraged recipients to work harder.
Elon Musk, who until recently was the face of Trump's effort to reduce government spending, has said a basic income will likely play a role in future economies as AI continues to rapidly develop.
Sacks' comments came as another prominent AI leader, Google DeepMind CEO Demis Hassabis, called for not just a universal basic income, but a "universal high income" at SXSW in London this week.
When asked about AI's impact on jobs, Hassabis said there would be a "huge amount of change," but that "new, even better" jobs could replace affected positions and boost productivity.
"Beyond that, we may need things like universal high income or some way of distributing all the additional productivity that AI will produce in the economy," Hassabis said.
Representatives for the White House and DeepMind did not respond to a request for comment from Business Insider.
| 2025-06-06T00:00:00 |
https://www.businessinsider.com/trump-ai-czar-david-sacks-universal-basic-income-ai-jobs-2025-6
|
[
{
"date": "2025/06/06",
"position": 50,
"query": "universal basic income AI"
},
{
"date": "2025/06/06",
"position": 50,
"query": "universal basic income AI"
},
{
"date": "2025/06/06",
"position": 44,
"query": "universal basic income AI"
},
{
"date": "2025/06/06",
"position": 41,
"query": "universal basic income AI"
}
] |
|
Artificial intelligence in teaching | Instructions for teaching
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Artificial intelligence in teaching
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https://teaching.helsinki.fi
|
[] |
The possibility of using artificial intelligence (AI) challenges teachers to adopt new ways of planning learning, creating assignments and assessing ...
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AI guides teachers to design learning assignments that are more applied in nature and geared to higher levels of expertise (cf. Bloom’s taxonomy). With easier and faster information-seeking, learning focuses instead on the analysis and assessment of the content acquired, the justification of interpretations made and the creation of new knowledge. This means teachers have to carefully consider the learning assignments they give to students and what kind of guidance and instruction they need. AI-generated output can easily answer a simple open-ended question or at least provide a good basis for a general essay assignment. This means that practising appropriate referencing becomes increasingly important.
AI helps produce responses that sound convincing to assignments asking the student to reflect on learning material. It is not enough to ask students to keep a learning journal outlining their challenges and including critical reflection. This is such a well-established type of text that AI tools such as ChatGPT can generate a response largely on the student’s behalf if the student attaches their lecture notes to a prompt and requests a reflective summary.
Hence, the teacher should experiment with AI tools to see the responses they produce to the planned learning assignments, and then consider how the assignments could be developed with appropriate instructions to make learning more meaningful. In several of the examples listed below, AI can help students complete assignments more quickly. This means you should outline assignments so that students are guided towards achieving the targeted learning outcomes of the course regardless of the means they use to complete the assignment.
Examples of learning assignments:
AI-generated text can be used as a basis, but the student’s own comments and thoughts must be clearly separated from it.
Students can be asked to apply information in case-based or problem-based learning. As part of the assignment, the original and follow-up questions posed to the AI tool must be documented. At the same time, students practise using AI as part of information-seeking and assess the output critically. Students can be asked to use source material provided by the teacher and report their reasoned solutions so as to make the learning process visible.
The conventions of academic writing should continue to be followed: sources must be mentioned, direct quotations clearly indicated and the student’s own comments distinguished from others’ work.
When exploring and seeking information on a new topic, the processing of information can be supported with follow-up questions (e.g., students can be asked for applied examples or to consider any unclear issues). AI can help with this, but the role of the assignment in the course should be minor or the assignment should not affect assessment.
Process writing and the use of interim feedback
Instructions for AI use
The basic premise is that AI-generated text cannot be presented as one’s own. It can be referred to under the name of the AI model and the date of the generated text. Students are responsible for their own texts, and plagiarism is strictly prohibited.
The teacher should provide instructions on how to use artificial intelligence (AI) in course assignments and how to report its use:
When providing guidance, consider whether a certain type of use is recommended or prohibited, and explain the reasons to the students.
AI-powered services can be used for various purposes, such as language translation, text editing, or idea generation. Students may also find it difficult to ascertain if a service is using AI in the background. Therefore, it is advisable to instruct students to cite not only to their sources of information but also to the tools they have used and specify how they have used them in completing their assignments.
Similarly, you can instruct students on what kind of AI use does not need to be reported if it is not relevant to the learning objectives of the assignment.
You can instruct students on how to use AI in the following way, for example:
Distinguish the text produced by AI from your own and add a reference to the name of the AI model or the service used, and the date when the material was generated.
Write down (e.g., in a footnote) the applications you used and their use, for example, if you used a service for idea generation, language checking, or text editing.
At the moment, it is not possible to reliably determine whether an answer has been produced by an artificial intelligence or a student. There are online services that assess whether a text is generated by AI, but even their response is only an estimation. The way AI has been used, for example, for proofreading or translation of one's own text, can affect this estimation. Additionally, it should be noted that a teacher is not allowed to input a student's answer into external services outside of the university, since they may not necessarily comply with GDPR requirements.
Note that there are differences in the levels of data protection of the AI services provided by the University. For more information see the IT HelpDesk guide Generative AI ath the University. In any case teachers are not allowed to input any learning assignments or other materials student produce to the AI services. The process of using AI on a course should therefore be planned so that only students themselves input their owen materials to these services. When using CurreChat on a course the teacher can guide the the process by creating instructive prompts that when used, instruct the language model how to reply or give feedback to students' prompts. For example, CurreChat can be instructed to pay special attention to certain details, or give hints on the student might improve their answer based on an exemplar answer.
| 2025-06-06T00:00:00 |
https://teaching.helsinki.fi/instructions/article/artificial-intelligence-teaching
|
[
{
"date": "2025/06/06",
"position": 70,
"query": "AI education"
}
] |
|
What should Education look like in the midst of Artificial ...
|
What should Education look like in the midst of Artificial Intelligence? — Barry Morisse
|
https://barrymorisse.com
|
[
"Barry Morisse"
] |
So if I try to bed down what artificial intelligence represents, my best attempt is that an AI system is a computer system that is able to perform tasks that ...
|
What should education look like in the midst of significant advancements in Artificial Intelligence?
Good afternoon ladies and gentlemen, it is a great privilege to be with you today – thank you to Craig from BRIDGE, and to Virginia and the team for inviting me to share some of my thoughts.
My name is Barry Morisse and today I stand in front of you as a researcher and ethicist in the field of artificial intelligence. My day job is with a small company called En-novate which designs and facilitates global immersion trips for talented South African entrepreneurs and business people. Our trips aim to expose the participants to what is happening in the major technological hubs. We operate across 11 cities and in this vein, I’ve spent much of the last year travelling to some of the most influential startup hubs around the globe, trying to get a handle on where technology is going.
Now my focus is on the field of artificial intelligence – a key technology that I believe is going to revolutionise our world – not just in a technical sense but also, and perhaps more importantly, socially, ethically and philosophically. All of these are admittedly heady concepts.
So, I hope that you will forgive some of my idealism as I share my thoughts today. I stand here on the outside looking in at the education system and as a result cannot possibly relate to the systemic challenges and constraints that all of you in the industry deal with on a day to day basis. So I empathise with the fact that much of the optimism which I might share in this presentation may seem naïve and impractical. That may be true. However, the purpose of my talk is not to provide a magic bullet – but rather to start a conversation about artificial intelligence and how I believe the education system needs to adapt as a result.
Here we go.
Part 1: Why should you care?
Just the term ‘artificial intelligence’ has become a buzzword over the last few years and is a very nebulous term. Although the field itself has been around since the 1950s, it’s only in the last decade where the rapid advancements have forced mainstream society to pay attention. Unfortunately, as with all hyped technologies, the media frenzy often serves to muddy the waters and the term slowly becomes more and more vague – with plenty of misrepresentations getting in the way of clarity.
So if I try to bed down what artificial intelligence represents, my best attempt is that an AI system is a computer system that is able to perform tasks that traditionally required human intelligence at a level of competence that equals or exceeds that level of which humans are capable.
Let me illustrate with the example of self-driving cars.
As I’m sure you know, there is a serious arms race happening at the moment between the likes of Google, Tesla and a myriad of other firms who are racing to create a fully autonomous car that can drive itself anywhere that we want it to go – without requiring a human driver at the wheel. While to some that may feel like Sci-Fi, the truth of the matter is that the technology is very close to being able to do just that – and it just a matter of time until the software running in that car is able to drive much more safely and more effectively than any of us. Thus, taking a task that we previously imagined would always require human intervention and rendering it obsolete.
That is a clear example of artificial intelligence and it has serious implications for our society – which we’ll touch on a bit later.
The point I want to make here though is that if we use that same logic – the simple pocket calculator could once have been considered artificial intelligence.
Prior to computational systems being developed – the mere act of multiplication was considered inherent to human intelligence. We then design a machine that is 100% accurate at a negligible cost and it renders human calculators obsolete.
The point is that once artificial intelligence is embedded in our day to day lives, we stop thinking about it as artificial and it simply becomes another tool that we use. AI’s advancement is inevitable as we strive to make our lives better and due to its foundational nature at the heart of computer science – it will impact every industry out there. Regardless of how little you know about it, or even how little you care about it – it is and will continue to impact your daily life on a micro-perspective and our society and workforce on a macro-perspective. If we don’t prepare for it, if we don’t talk about its effects, if we simply choose to stick our heads in the sand – we will be on the wrong side of history.
Part 2: The Impact of Automation
And that is where the education system plays such a pivotal role. We have to do everything within our power to prepare the generation of tomorrow for a world that doesn’t look anything like the world of today.
If we look back over the last few centuries, we’ve seen the same story play out again and again. Farming machinery augments and eventually replaces human labour. Henry Ford’s automobiles disrupt the horse-and-cart, rendering an entire transport system obsolete. The machine assembly line replaces its human version, emptying factories of almost all their unskilled workers. These, which were all huge innovations in their time, caused the same panic that we hear today. What will all those people do? How will they feed their families? Are their employers ultimately responsible for finding the solution or is this the modern form of Darwinism?
One of the key roles that educators play is to train and prepare young people to join the global workforce. You work tirelessly to equip your students with the skills they need to contribute successfully to the world. In this vein, it is crucially important that we consider which types of jobs and tasks will be made obsolete by artificial intelligence in the near future. The cold hard truth is that a vast array of routine tasks, computations and processes will become completely automated in the coming years and that the humans that used to perform these jobs will find themselves locked out of the market.
In 2018, a working paper by the OECD attempted to codify the risks to certain professions due to automation and came up with these results. Now as you would imagine, the science behind these sorts of predictions is always up to serious debate – but what I find interesting is that while blue-collar jobs are most at risk, as is to be expected, there is a whole ecosystem of white-collar work that is also at serious risk. What this illustrates is that the scope of change that is going to happen to our economy is wider than we’ve ever seen before. And that’s why many have started to describe it as the fourth industrial revolution.
It’s not doom and gloom though. As with every revolution before this, the technology opens the doors for new industries, jobs and value to be created, improving human living conditions and, ultimately, pushing our species forward. Over a long-enough timeframe it should become clear that the advancements are incredibly beneficial, even though certain segments of the population may be left behind - essentially, because they couldn’t adapt fast enough. Proactive action on our behalf can ensure that our students are not part of that group that is left behind.
Part 3: What Do We Change?
The hard part of all of this is figuring out how to prepare for an uncertain future. How do we prepare for a world that we can’t quite imagine? It’s been a trope for a while now that the education system as a whole hasn’t adapted quickly enough for a 21st century world and, for the most part, still functions as an industrial revolution machine – procuring the skills for the challenges of the past.
So I think it is uncontroversial to say that the system needs a serious update. And although these sorts of systemic changes often give us stomach ache due to their massive scale and significant difficulty – I actually think it represents an incredible opportunity for Africa to break new ground and chart a new course for itself. Education has and always will be the Archimedes lever that we can use to change the course of people’s lives and as such, remains the most important tool we have in creating the future that we want.
Let’s get a bit more tactical.
It’s clear to me that the education system needs to shift its focus away from skills where automation and AI will have a serious advantage. It is naïve to think that we are going to be able to compete with machines on tasks that require computation, information recall, precision processing, etc. We have to accept that those types of tasks are going to be offloaded to AI systems. This is a scary concept of course, especially in a country like ours – where unemployment is so prevalent – but we have to be able to let these go in order to create space to craft new curriculums and new modes of teaching.
Again, I will emphasise that there is an opportunity here to forge a more fulfilling future for young people and by letting go of tasks that are easily automated, we stand to create whole new industries which calls more on our humanity. But this requires bold action from decision makers in the space.
Ok, so assuming we’ve let those go – what skills do we aim to replace them with?
This is a very hard question. Some people when tackling this question talk about skills that are ‘future-proof’ which I think is a terrible term. As I mentioned earlier – the goalposts will continue to move and the AI of 2025 will be the pocket calculator of 2030. And so, to predict that there is some sort of magic bullet that is immune to the march of technology is unbelievably naïve. I don’t think any of us are in a position to suggest that, say, computer programming is a skill that will never be automated – for example. The game of trying to pick careers decades in advance just doesn’t work.
And we’ve seen this in the millennial generation. When my parents were being educated, they were prepared to work in a single career for their whole life. That world no longer exists and the vast majority of people in my generation will work in 5 or 6 completely different career paths during their lifetimes – many of which we can’t even imagine as we sit here today.
I think that a more fruitful way of looking at it is a real attempt to prepare young people to be as flexible and adaptable as possible – instead of pigeon-holing them and preaching the power of specialisation. What humans do better than machines is generalisation. By that I mean – humans are incredibly good at large scale problem solving especially in cases where the problem has never been seen before. Because we have the ability to draw parallels and patterns from seemingly disparate parts of our knowledge to connect dots and carve new solutions from those patterns.
These are the types of skills that I think we should be focusing on – and I want to call them meta-skills because they are one level of abstraction higher than specialised skills such as mathematics or language or programming. Let me explain what I mean by taking you through four meta-skills that gives a human being the edge over the AI of the next decade.
The first one is the meta-skill of problem solving. It’s an obvious one, a foundational skillset that all educators aim to nurture in their students, but the way we go about teaching problem solving needs to take account of what the world looks like today. Can we teach our students to be resourceful by using the internet while also maintaining a sceptical eye on what they find? Can we teach them to look at things from first principles and encourage them to challenge the status quo assumptions? How can we champion the scientific method as a methodical and responsible way of understanding the world? Problem solving should be a foundational focus.
The second meta-skill is that of creative thinking. How do you create something truly original? How do we create the spaces for our students to take risks and try things that may seem unconventional or foolhardy? On the whole we tend to unconsciously punish creative thinking and champion conformity – simply because it’s easier to manage large groups of students when we have serious standardisation, rules, procedures, etc. That tendency needs to change – because the unique individuality and creative energy that each student brings with them is the key for them to find a place to contribute in a world of machines.
The third one is learning how to learn. In a life where you change careers a number of times, the ability to keep learning and keep retraining yourself in order to stay relevant is crucial. Their adaptability in a changing world is dependent on how effectively they can take in new information, assess its relevance, accuracy and impact on their current situation and then forge new mental pathways as a result. We are going to have to constantly be re-inventing ourselves throughout our career. So this skill of learning how to learn is one where I think we should be allocating a lot more of our time.
And the last one is what I’ve called scaling our humanity. The best way I can describe this is with a story. I took part in a programme in Berlin last year focused on the future of work. The incubation hub that was running in invited 15 young people from around the world to brainstorm solutions for the threats that automation was posing to the administrative workforce of BMW – the car company. At that stage BMW had over 600 people in their global head office whose jobs were for all intents and purposes – obsolete. So they gathered a group of thinkers from across the world to try and find unique solutions.
I was greatly encouraged by the discussions that took place there. Initially, I expected that we would discuss the usual solutions that get bandied about – upskilling, learning to code, transitioning into different roles etc. But what was really refreshing was the thoughtfulness that echoed in those discussions about how we can scale our ‘humanity’.
The nature of the technological shift means that tasks that require the human touch will become ever more valuable. Human creativity, relationship-based service, or a range of other tasks that require empathy, judgment, intuition or an intrinsic understanding of human behaviour all become increasingly rare and valuable. With this perspective, instead of surrendering to the idea that the rise of AI is an inescapable path towards human obsolescence, AI may in fact liberate us from the types of tasks that we didn’t really enjoy doing anyway and free up time and resources to scale the human-centric tasks to a level we have never seen before. For example, what if a company’s human resources department wasn’t bogged down by the administrative tasks of dealing with payroll, leave forms, medical aid and the like, but could rather focus all their energy on proactive care for their employees – looking after their physical and mental health. Thinking about AI in this way allows a radical paradigm shift about what a human resources department can be and allows those employees (who went into HR because they wanted to interact with people) to do more of the tasks that they find fulfilling. That’s where the opportunity lies.
These are the kinds of meta-skills are what we should be talking about, rather than the content of the next science textbook. The internet has democratised access to information and its now available instantly at a volume that we can’t quite fathom. That’s not the bottleneck. The bottleneck is how effectively we can curate that information and use it to solve novel problems, scaling our uniquely human qualities.
Part 4: What is our responsibility?
The future will be inextricably linked with AI systems and as we develop them we must make some very difficult decisions as to how to deal with the externalities.
Some thinkers in the field have coined the term ‘human-centered AI’ which is of course terribly cheesy – but I think has some great tenets sitting behind it. The basic ideas is that computer science needs a fresh dose of humanity. This comes in three pillars:
1. The development of AI should be guided by a concern for its impact on human society.
2. AI should augment human skills, not replace them.
3. AI must incorporate more of the versatility, nuance and depth of human intellect.
Now I don’t bring these up here to suggest that educators are the ones who need to steer the development of AI. Instead I bring it up to show that educators can play a major role in preparing the human side of the equation to thrive in a world where AI systems are ubiquitous. Rather than replacing us, AI can make us better at what we do. The technology is full of potential for the human race – if we prepare ourselves accordingly.
If we are going to bury our heads in the sand and continue on the path that we are on, we are going to produce a generation of people who are thoroughly ill-equipped for a 22nd century world and who will be made obsolete due to advancing technology.
However, if we can equip our people with the meta-skills needed to thrive alongside the machines, we can empower them to take charge of their own destiny and use the AI tools to solve problems that we could never have dreamed of solving – pushing the human race forward.
I don’t have all the answers – but I know what the right direction is. We have the responsibility to start sounding the alarm and to start turning the ship now.
Thank you.
| 2025-06-06T00:00:00 |
https://barrymorisse.com/blog/education-ai
|
[
{
"date": "2025/06/06",
"position": 76,
"query": "AI education"
}
] |
|
AI Is a Weapon Pointed at America. Our Best Defense Is ...
|
AI Is a Weapon Pointed at America. Our Best Defense Is Education.
|
https://thefulcrum.us
|
[
"Hugo Balta",
"Steven Hill",
"Andrew Byron",
"Mike",
"Kristina Becvar",
"Kevin Frazier",
"David L. Nevins",
"Stephanie R. Toliver",
"Robert Cropf",
"Layla Halilbasic"
] |
An AI Education Corps offers a bold, concrete path to rapidly build the widespread AI literacy that our national security and economic future demand. It's an ...
|
In early May, Ada Miranda drove her pickup truck through the hills of the Puerto Rican subbarrio of Vegas Arriba, just down the road from Iris and Serafin’s mountainside home. In the backseat, a stack of laminated green posters, punctuated with the heading ‘CONOCE TU SISTEMA SOLAR’, slid back and forth as the truck lurched over potholes.
Finally, she reached a gravel pull-off on the side of the road just across from a row of houses. It was a sunny day, and a breathtaking view of the Cordillera Central rose behind the houses — a few of which featured newly installed solar panels. Ada turned off her truck and set down her chai latte, which a neighbor had made for her that morning. She grabbed a green poster from her stack and made her way across the street toward one of the homes.
There were two men in the driveway working on repairing a car, but as Ada approached, they set down their tools and each greeted her with a hug.
CAPTION: Ada Miranda explains a solar system to a family who recently had rooftop solar panels installed on their home.
“I love what I do, but I love more that I can help people,” she said. “I have a saying, if I make a person happy a year, I’m done. But right now, I know that there’s a lot of people who need help, who I’ve been helping.”
Rooftop solar is spreading across Adjuntas and neighboring municipalities. However, these solar panels are usually not being installed because residents are actively seeking them out — community organizers like Ada are spreading the word, one household at a time. She works for the Let’s Share The Sun Foundation, a nonprofit that helps fund solar panels for rural communities in Puerto Rico. The foundation has partnered with Casa Pueblo, an Adjuntas-based environmental justice organization, to help residents install solar panels, with a focus on those who use electricity to power medical equipment.
Through Casa Pueblo’s own solar waitlist, radio promotions, and simply asking around, installers like Ada have connected with people who need solar but can’t afford it. Now, she spends much of her time in Adjuntas installing panels. After the installations are complete, she checks in on each household one by one, ensuring they understand how to operate the new system.
To outsiders, identifying residents who need solar the most seems like a difficult task. Puerto Rico passed a law in 1998 stating that it would cover the electric costs for residents who rely on life-saving medical equipment. But there’s still no streamlined database of which residents need these costs covered — even though, according to the federal emPOWER database , the island is home to some 46,000 at-risk Medicare patients.
CAPTION: Adjuntas, nicknamed la Ciudad del Gigante Dormido (“city of the sleeping giant”) due to the shape of the mountains surrounding the town, sits in Puerto Rico’s Cordillera Central.
In many smaller mountain towns, residents have turned to neighbors and friends to help find and support at-risk individuals.
“One of the very important things that helps a local project is that we go to the people, we don't stay here,” said Francisco Valentín, who runs a community health clinic in Utuado, another mountain municipality near Adjuntas.
Valentín has lived in Utuado his entire life and has witnessed firsthand how sick and elderly residents struggle without reliable emergency services, especially during Hurricane Maria. Twelve years ago, he started his clinic, COSSAO, in a former agricultural supply building. Today, the clinic is entirely powered by solar energy and employs a doctor and several nurses who provide check-ups to residents in need.
Central to his mission, though, is keeping track of at-risk residents. COSSAO’s nurses also serve as “health promoters”, whose job is to seek out households with special needs. The clinic has its own emergency medical vans and equipment to clear roads during disasters, allowing it to send help to at-risk households within 48 hours of an emergency.
“We’ve lived here for long enough, that we know, where are the people who need respiratory equipment, people who need refrigeration for their medicines?” Valentín said. “We already know all the people in six communities, we know all people that have special needs.”
“If we don't take care of the future of our communities,” he added, “no one is going to.”
—
CAPTION: Olga Hernández Molina stands with a wall of portraits in her home. She served on Adjuntas’ community police force for many years.
Olga Hernández Molina’s walls are covered in plaques. Most of them are from her career as a captain for Adjuntas’ police force — community awards for her decades of service, photographs of the police force at team potlucks.
In February, she hung a new plaque on her wall — one from the Let’s Share the Sun Foundation, signifying her newly installed solar panels.
Olga lives in Alto de Cuba, a neighborhood a few blocks away from the town square that Massol-Deya said has been historically underserved. The Foundation has installed over 30 rooftop solar systems there since 2023, including on Olga’s home. Like Serafin from Vegas Arriba, Olga is diabetic and relies on her solar panels to keep her medications stable in her refrigerator.
“When the darkness comes, I feel afraid,” she said. “Just a few hours without the medication makes me very stressed… but thanks to God for the panels, I feel much more relaxed.”
From the top of a small hill around the corner from Olga’s house, solar panels can be seen atop nearly every house on her block. Alto de Cuba’s grocery store also features solar panels, which were funded and installed by Casa Pueblo.
A few of the solar panels on Olga’s block, though, are funded by the Puerto Rican government, according to her brother, Rafael Hernandez.
“[The government does] the best they can, because they don’t have a lot of money to work on that with,” Rafael said. “Already last summer, a couple families went there and then got the help [they needed].”
“But it's a lot of people,” he added. “Lots more people need help.”
On average, solar systems can cost over $10,000 out-of-pocket. Federal tax credits can cover up to 30% of the total cost of a system, and Puerto Rico’s net metering program helps make utility bills for solar households even lower.
But in Adjuntas, where the average household income is just over $18,000 per year, these upfront costs can feel insurmountable, even with government assistance.
“There’s a commercial on TV about the lottery, which actually says, ‘if you win this lottery, you can get your rooftop solar system,’” said Ruth Santiago, an environmental lawyer based in Salinas, Puerto Rico. “But we didn’t really see material support for [solar] — the amounts of funding allocated for these kinds of alternatives were far smaller than what we see for the investment in existing fossil fuel plants.”
CAPTION: A Puerto Rican flag flies in the wind outside Casa Pueblo in Adjuntas.
Private grant funding is a key reason why so many of Adjuntas’ at-risk households have solar panels. The Let’s Share the Sun Foundation is largely funded by private donors and receives 10% of its funding from Jordan Energy, a solar company based in upstate New York. Casa Pueblo also receives most of its solar funding from private grants and the sale of its own coffee.
Still, residents like Rafael and Olga said they’re afraid of what could happen to communities like theirs if the government doesn’t scale up funding for rooftop solar. The Department of Energy recently announced that it is redirecting $365 million in funding from the Puerto Rico Renewable Energy Fund, originally intended to provide rooftop solar to health clinics and rural community centers, and instead investing that money into “technologies that improve system flexibility and response.”
Experts like Vila are concerned that this money will go back into costly fossil fuel developments, rather than scaling up rooftop solar as a more accessible option.
“We are walking away from what should be Puerto Rico's transformation and what should be the direction for the future of Puerto Rico's energy sector,” Vila said.
In Adjuntas, advocates like Massol-Deya have pledged to continue their work, building rooftop solar — and community independence — from the ground up.
But without government support, other mountain communities could continue to be left in the dark.
“The government has focused on San Juan, and has forgotten the rest of the towns, and the poor people,” said Iris. “I would like that they help everybody, that each person should receive a solar system, because the needs are not only in Adjuntas, but in every town.”
Lily Carey is a graduate student in journalism at Northwestern University.
Please help the Fulcrum in its mission of nurturing the next generation of journalists by donating HERE!
| 2025-06-06T00:00:00 |
2025/06/06
|
https://thefulcrum.us/governance-legislation/artificial-intelligence-in-education
|
[
{
"date": "2025/06/06",
"position": 81,
"query": "AI education"
}
] |
A New Map for the AI-Education Frontier
|
A New Map for the AI-Education Frontier
|
https://www.edtechdigest.com
|
[
"Victor Rivero"
] |
“It's there to help faculty and students embrace the ever-deepening influence of AI in their lives and careers; and for others who can benefit from increased ...
|
What happens when a university doesn’t just adapt to change—but decides to lead it? Camille Dempsey gave my students a look inside PennWest’s bold new center.
GUEST COLUMN | by Mark Gura
Good timing can be a beautiful thing. Sometime between Professor Camille Dempsey accepting my invitation to visit my online class, PennWest officially launched its new Center for Artificial Intelligence and Emerging Technologies, naming her its director. Synchronicity and opportunity!
I teach “Technology Integration for School Leaders,” offered by Touro University’s Graduate School of Technology. To spice class meetings up, each semester I invite in a few edtech movers, shakers and important influencers for a conversation to provide sharp perspective and vision, and assure the class’s relevance.
‘To spice class meetings up, each semester I invite in a few edtech movers, shakers and important influencers for a conversation to provide sharp perspective and vision, and assure the class’s relevance.’
Much of the conversation we had with Dr. Dempsey leaned in the direction of satisfying our curiosity about this new center, a development I see having as high significance for the field.
True, over the past couple of years many universities have seen fit to include AI as part of what their courses and periodic workshops cover. However, for an institution of Higher Ed to perceive a growing and deepening need as acute and full of opportunity and possibility, that it creates a distinct organizational entity to address it, is worthy of notice. Here are some highlights from Camille’s Zoom-based conversation with us.
Our exchange focused on the new center’s mission. And with apologies and deference to Star Trek creator, Gene Rodenberry, I can’t resist paraphrasing his famous line, “to boldly go where no school has gone before!” And it turns out this is pretty much what the center is there for.
Camille explained that the new center started as a hub for PennWest’s region. “It’s there to help faculty and students embrace the ever-deepening influence of AI in their lives and careers; and for others who can benefit from increased awareness of digitally influenced education. The center, even prior to its official launch, has been providing info and service to a variety of stakeholders. The reality is that there’s a need and the center is the university’s effort to provide support in the area of AI and beyond. Requests keep coming in for information and clarity about something that so many people are struggling to get up to speed on.”
For me, a great bonus was that this was a professional reunion with Camille. We had worked together a few decades back, along with other committed envelope pushers, to introduce the New York City school system to classroom technology, bringing instruction up to speed with new teaching and learning possibilities.
The conversation revealed that Camille and I are on the same page. When we introduce EdTech to educators, we push for what I like to call a Biggest Big Picture Understanding, a view from10 steps back where one can see the full scope of the field. We agree that it’s easy to slip into niche understandings, something that’s important to be cautious of as AI becomes more and more prominent.
Her Own Direct Experience
Camille, I could see, forms much of her edtech understanding and advice to teachers, school leaders, and district superintendents on her own direct life and teaching experience.
For example, she shared that MS copilot is used at PennWest, but like everyone else she’s learning to cope with AI resources that insist on being used. She sees our level of access to them as a sort of new ‘Tech Divide.’ But it’s a divide that must be crossed as this redefining resource set is a change-enabler that’s definitely not going away and that’s gaining traction rapidly.
Dr. Camille Dempsey is Associate Professor of Education and Program Coordinator for the M.Ed. in Educational Technology and Online Teaching at PennWest. A former K–12 teacher and nonprofit administrator, she holds degrees from Duquesne, Columbia Teachers College, Penn, and the Pennsylvania Academy of the Fine Arts. An internationally recognized scholar in educational technology, Camille has led efforts to integrate AI in schools, including through ISTE’s K–12 AI Explorations program.
She is a recipient of ISTE’s “20 to Watch” award, the PAECT Educational Technology Impact Award, and the Ero W. Davidson State Award for Technology & Communications. Her research explores how technology reshapes human presence and consciousness, and she is the founder of the Theory of Virtuality Culture. Camille also consults on AI, ethics, and policy with institutions worldwide, including the U.S. Department of Education and international partners.
She holds multiple technology certifications, is a Google AI Mastermind for Women, and serves in leadership roles across ISTE, PAECT, and STEM advisory boards.
In her own teaching, Camille is experimenting with AI supported grading. She reports that she finds this shift in her practice to be “quite an adventure.” She states that she likes to “give highly personalized feedback so it’s an interesting dilemma to balance satisfying the needs of the student, while coping with the demands on time and effort of the teacher.”
While she doesn’t want to “outsource her brain to a robot” because she strives for authenticity in what she hands off to students, she has been finding great potential and usefulness in the rubrics AI offers her. She insists, though, that AI is meant to be an iterative process, one in which the human driver of the process doesn’t simply accept and employ the AI output, but rather goes back and forth with it, changing and tweaking things “until you arrive at something you feel is truly right.” And, Camille points out, tongue in cheek and smile in her voice, that “At least when it comes to creating rubrics, AI may do a better job than I do!”
‘AI is meant to be an iterative process, one in which the human driver of the process doesn’t simply accept and employ the AI output, but rather goes back and forth with it, changing and tweaking things “until you arrive at something you feel is truly right.”’
She spoke of President Trump’s recently signed executive order to support AI Education in the nation’s schools, observing that even though much federal funding, and the Education Department’s Office of Educational Technology, has been cut, here’s a new funding source targeted at AI. And that it will be interesting to see how this trickles down to K-12 Education. I agree and see the important resulting need; school administrators’ will have to acquire much more understanding of AI in order to ensure that their local programs develop meaningfully and impactfully.
Our Mutual Belief
Both of us made clear our mutual belief that the use of social media is a crucial enabler for today’s connected educators. Camille stresses to her own students, as well, not to overlook what we both see as an important platform on which educators can connect, network, and share professional knowledge and perspective. I’m a member of a good number of Facebook groups that function as professional learning networks including groups of teachers who discuss AI in the classroom. I encourage my Touro students to follow suit.
Beyond congratulating Camille on the center’s launch and her designation as its director, I wanted my students to get some insight into what it means to have a university-based center like this, why its emergence is important, as well as what it likely will add to the field.
To this point, Camille shared having recently given a day of PD for 187 teachers and administrators on AI Literacy and took particular pleasure in the fact that the top level of administration chose to sit and learn side by side with the teachers, receiving a full day of learning. And I agree, that the administrators stayed on beyond the pre-event coffee and networking and the opening plenary session speeches and on into the full day’s content, is a strong indicator of how important this work is regarded.
When asked about other schools developing hubs like hers Camille related that there are a few she’s aware of. In Pennsylvania; one at Penn State another at Carnegie Mellon, focusing in particular on Robotics. She shared a great afterthought, that it would be wonderful to see the development of a national hub or some other mechanism for aggregating the work that’s being done at this level in a variety of settings.
‘…it would be wonderful to see the development of a national hub or some other mechanism for aggregating the work that’s being done at this level in a variety of settings.’
By the way, the center identifies itself as a Center for AI and Emerging Technologies. And so I probed a bit about that. Augmented Reality is one of what will be a portfolio of technologies that it will provide focus and insight on.
Yes, there are still great numbers of educators who are getting themselves caught up with pre-AI technology, Google Classroom and the like. And true, that’s essential. But at the same time it’s great to see that there are people dedicating themselves to supporting colleagues who want to go in the opposite direction—to explore what’s new and more cutting edge with an eye, not just toward satisfying their personal curiosity, but to practical adoption to improve K-12 teaching and learning.
Rich Potential Moving Forward
In concluding our class discussion, I dropped a hot potato question in Camille’s lap. How would you recommend average, rank and file, preK–12 teachers across our nation take charge of their crucial PD need to get themselves further up to speed on AI in Education? She wisely recommended programs and resources from ISTE. And unexpectedly, but ever so wisely, again, she recommended teachers use AI resources themselves to develop a bit of a personal plan on preparing to teach in a world that will be ever more AI-centric.
Bottom line for me? Our universities represent such rich potential to help our nation meet the mandate to move forward quickly in embracing and benefitting from a set of resources that is truly transformational if understood properly. The establishment of centers like PennWest’s should be recognized, encouraged, and cloned.
And to have a fondly remembered former colleague visit my class, where I get myself and up and coming school technology leaders well informed on what’s happening and coming at us—that was such sweet icing on the cake!
—
Mark Gura is Editor-at-Large for EdTech Digest and author of Creative SEL: Using Hands-On Projects to Boost Social-Emotional Learning and of The Edtech Advocate’s Guide to Leading Change in Schools (ISTE), and co-author of State of EdTech: The Minds Behind What’s Now and What’s Next (EdTech Digest). He also authored Make, Learn Succeed: Building a Culture of Creativity in Your School (ISTE). He taught at New York City public schools in East Harlem for two decades. He spent five years as a curriculum developer for the central office and was eventually tapped to be the New York City Department of Education’s director of the Office of Instructional Technology, assisting over 1,700 schools serving 1.1 million students in America’s largest school system. In addition to his role at EdTech Digest, he is currently a professor at Touro College Graduate School of Technology.
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| 2025-06-06T00:00:00 |
2025/06/06
|
https://www.edtechdigest.com/2025/06/06/a-new-map-for-the-ai-education-frontier/
|
[
{
"date": "2025/06/06",
"position": 99,
"query": "AI education"
}
] |
Companies Are Using AI to Make Faster Decisions in Sales ...
|
Companies Are Using AI to Make Faster Decisions in Sales and Marketing
|
https://hbr.org
|
[
"Prabhakant Sinha",
"Arun Shastri",
"Sally Lorimer",
"Srihari Sarangan",
"Is A Cofounder Of Zs",
"A Global Professional-Services Firm. He Is A Coauthor Of The",
"Is A Leader Of The Artificial Intelligence Practice At Zs",
"A Global Professional-Services Firm",
"Teaches Sales Executives At Northwestern S Kellogg School Of Management. He Is A Coauthor Of The",
"Is A Principal At Zs"
] |
Decision-making in sales and marketing is shifting from reflective to reflexive, leveraging real-time data and AI to enable immediate, context-aware.
|
is a leader of the artificial intelligence practice at ZS, a global professional-services firm, and teaches sales executives at Northwestern’s Kellogg School of Management. He is a coauthor of the HBR Sales Management Handbook
| 2025-06-06T00:00:00 |
2025/06/06
|
https://hbr.org/2025/06/companies-are-using-ai-to-make-faster-decisions-in-sales-and-marketing
|
[
{
"date": "2025/06/06",
"position": 19,
"query": "AI employers"
}
] |
25 Best AI Security Companies: Securing Models,Data & ...
|
25 Best AI Security Companies: Securing Models,Data & Infrastructure (2025)
|
https://mindgard.ai
|
[
"Fergal Glynn"
] |
This list highlights 25 leading AI security vendors that help organizations defend against emerging threats, harden AI models, and streamline security ...
|
As artificial intelligence becomes embedded in everything from customer service to critical infrastructure, securing these systems—and using AI to improve security itself—has become a top priority. Traditional tools weren’t built for adversarial prompts, model theft, or real-time anomaly detection at scale.
That’s why a new generation of AI security companies is emerging. This list highlights 25 leading AI security vendors that help organizations defend against emerging threats, harden AI models, and streamline security operations with speed and precision.
However, choosing the right AI security company for your organization’s needs isn’t as cut-and-dry as it may seem. That’s why we’ve identified examples of the best AI security companies for various use cases, including:
Company Key Features Use Cases Notable Strength Mindgard Automated red teaming, CI/CD integration, artifact scanning AI model security, adversarial attack defense, offensive security Best for securing AI systems Vectra AI AI-powered threat detection, hybrid visibility Identity, cloud, and SaaS threat detection Great for attacker movement visibility Cyera Agentless deployment, DataDNA classification Sensitive data discovery & protection Great for DSPM Abnormal Security Behavioral AI, insider risk detection Email threat prevention (BEC, phishing) Great for email security Rapid7 MDR, AI-driven alert triage Cloud and hybrid threat detection Great for attack surface visibility
Mindgard is a pioneering AI security company specializing in autonomous red teaming and continuous security testing for artificial intelligence systems. Founded in 2022 at Lancaster University and now based in London, Mindgard leverages over a decade of academic research to address the unique vulnerabilities inherent in AI models, particularly those that traditional security applications often overlook. The company’s flagship Offensive Security platform is designed to detect and remediate AI-specific threats at runtime, ensuring robust protection across the AI lifecycle.
Mindgard’s Offensive Security solution enables organizations to proactively identify and mitigate a range of AI-specific vulnerabilities, including prompt injections, model inversion, data poisoning, evasion attacks, and other adversarial attacks. It integrates seamlessly into existing CI/CD pipelines and supports a wide range of AI models, from large language models (LLMs) to image and audio systems. Mindgard’s extensive attack library—aligned with the MITRE ATLAS™ framework—and automated testing capabilities allow for the rapid identification of risks, reducing testing times from months to minutes.
Key Features:
Automated AI red teaming
Extensive attack library
CI/CD integration
Compliance-ready reporting
Artifact scanning
Vectra AI is a cybersecurity company that specializes in AI-driven threat detection and response. Founded in 2012 and headquartered in San Jose, California, Vectra AI operates in over 113 countries, providing AI security services to companies spanning a variety of industries, including finance, healthcare, education, and government.
The Vectra AI platform delivers comprehensive visibility across hybrid attack surfaces, encompassing identity systems, public cloud, SaaS applications, and data center networks. It leverages patented behavior-based AI to detect and stop advanced attacks that often evade traditional security tools.
Key Features:
AI-powered threat detection
Attack Signal Intelligence™
Agentless deployment
Automated response capabilities
Hybrid and multi-cloud visibility
Cyera is a rapidly growing data security company that offers an AI-native platform designed to help organizations discover, classify, and protect sensitive data across different environments, including SaaS, PaaS, IaaS, and on-premise systems. The company, founded in 2021, has quickly become a leader in the data security posture management (DSPM) space.
The core of Cyera’s platform is its AI-driven engine, which enables rapid deployment without the need for agents. This allows for quick data scanning, classification, and risk assessment across an organization’s entire digital ecosystem. Cyera’s DataDNA technology utilizes machine learning, named entity recognition, and large language models to achieve high-precision data classification, reducing false positives and providing actionable security insights.
Key Features:
Rapid agentless deployment
Advanced data classification with DataDNA
Identity access management
Comprehensive data discovery
Automated remediation workflows
Abnormal Security is a cybersecurity company that leverages AI to protect organizations from advanced email threats, including phishing, business email compromise (BEC), and account takeovers. Founded in 2018, the company’s Abnormal Behavior Platform leverages behavioral AI to detect anomalies in email communications by establishing a baseline of normal behavior for each user and vendor within an organization. This approach enables the platform to identify and remediate malicious emails that traditional security solutions might miss.
Abnormal Security’s AI-native architecture integrates seamlessly with cloud email platforms like Microsoft 365 and Google Workspace through API connections, allowing for real-time threat detection and response without the need for manual intervention. By analyzing thousands of signals related to user behavior and communication patterns, the platform can autonomously neutralize threats, reducing the burden on security teams and minimizing the risk of human error.
Key Features:
Behavioral AI-based detection
Autonomous threat prevention
Insider risk detection
Advanced attachment and link scanning
User-friendly incident response tools
Founded in 2011 and headquartered in Boston, Massachusetts, Rapid7 offers solutions to help organizations manage risk and eliminate threats across modern cloud environments. It offers a suite of products and services designed to provide visibility, analytics, and automation to simplify complex security challenges.
The Rapid7 AI Engine processes over 4.8 trillion security events weekly, enabling accurate threat detection and alert triage. By distinguishing between malicious and benign alerts, it reduces false positives and allows security analysts to focus on genuine threats. The AI Engine also powers an AI-native Security Operations Center (SOC) assistant, which leverages Rapid7's extensive internal knowledge base to guide analysts through complex investigations and streamline response workflows.
Key Features:
24/7 managed detection and response (MDR) services
Continuous vulnerability assessment and prioritization
Advanced detection, investigation, and response capabilities
Dynamic application security testing (DAST) for web applications and APIs
Enforces ML/LLM security standards
Other AI Security Companies to Consider
Company Key Features Use Cases Notable Strength 7AI Autonomous AI agents, modular design EDR, red teaming, compliance Great for automated security tasks Arctic Wolf Managed detection, risk prioritization SMB to enterprise threat response Great for managed SOC Armis Centrix Asset visibility, risk prioritization IoT, OT, IT asset management Great for cyber exposure management Check Point ThreatCloud AI, unified architecture Network, cloud, and endpoint security Great for unified threat prevention CrowdStrike Falcon platform, real-time EDR Endpoint & threat intelligence Great for scalable endpoint security CyberArk Zero trust, natural language AI Identity and privileged access security Great for identity threat protection Cynet All-in-one, UBA, deception tech SMB-focused threat protection Great for unified security on a budget Darktrace Self-learning AI, real-time response Anomaly detection across networks Great for autonomous threat mitigation Exabeam AI assistant, behavior analytics SIEM and SOC optimization Great for efficient threat triage Fortinet FortiAI, integrated security fabric Network, AI model, and app protection Great for full-spectrum defense Google SecOps Gemini AI, SIEM + SOAR Cross-platform incident response Great for cloud-native security ops Hunters Pre-built detection, automated correlation Lean SOC optimization Great for lean security teams Microsoft Copilot Threat intel, guided workflows Enterprise-scale threat hunting Great for LLM-based SOC assistance Mimecast AI/NLP threat detection, misaddress protection Email continuity and security Great for email collaboration protection Okta Adaptive MFA, behavior tracking IAM and policy enforcement Great for identity access management Proofpoint NexusAI, data classification Email and user behavior threats Great for targeted threat protection SentinelOne Singularity XDR, rollback recovery Endpoint and identity threat detection Great for autonomous threat response Shield AI AI autonomy, GPS-free ops Military unmanned systems Great for battlefield AI security Sophos Intercept X, GenAI-assisted XDR Malware and zero-day threat prevention Great for AI-enhanced malware defense Zscaler Phishing prevention, AI segmentation Zero Trust and real-time threat prevention Great for cloud-native threat prevention
Founded in 2024 and based in Boston,7AI is a cybersecurity company that leverages autonomous AI agents to handle routine, repetitive tasks traditionally managed by human analysts.
Its Agentic Security Platform deploys specialized swarming AI agents that can autonomously respond to alerts, enrich data, conduct investigations, and draw conclusions without human intervention. These agents are designed to offload non-human work, freeing up security teams to focus on high-value tasks.
Key Features:
Deploys autonomous AI agents
Supports EDR investigations, cloud security, compliance monitoring, identity threat detection, and red teaming
Modular agent architecture
Arctic Wolf, founded in 2012, is based in Eden Prairie, Minnesota. It specializes in providing managed security services to organizations of various sizes across multiple industries. Arctic Wolf’s Aurora Platform is a cloud-native security operations platform that ingests and analyzes over 7 trillion security events weekly.
It’s designed to deliver scalable, automated threat detection, response, and remediation capabilities, leveraging AI and machine learning to reduce noise and transform thousands of daily alerts into a single actionable ticket for most customers.
Key Features:
Managed detection and response
Continuous vulnerability scanning and risk prioritization
Human-centric employee training
Armis Centrix™ is a comprehensive cyber exposure management platform designed to provide organizations with real-time visibility and control over their entire digital attack surface. Powered by the Armis AI-driven Asset Intelligence Engine, it enables the discovery, protection, and management of billions of assets worldwide, including IT, OT, IoT, and medical devices.
The platform delivers deep situational awareness across diverse environments—physical, virtual, cloud, and logical. Armis Centrix™ offers a unified asset inventory, enriched with contextual information, facilitating effective risk management and compliance reporting.
Key Features:
Comprehensive asset visibility
AI-powered risk prioritization
Continuous threat detection and response
Founded in 1993, Check Point is a leading global provider of cybersecurity solutions. Check Point’s Infinity Architecture is a unified security platform that delivers advanced threat prevention across various environments.
This platform incorporates ThreatCloud AI, a robust threat intelligence engine that utilizes over 50 AI engines and data from hundreds of millions of sensors to detect and block known and unknown threats, including phishing, ransomware, and zero-day attacks. The platform's AI capabilities enable real-time sharing of threat intelligence across networks, cloud services, endpoints, and mobile devices, ensuring consistent and comprehensive protection.
Key Features:
Automates tasks like policy setup and threat hunting
Shares AI-driven intel across all environments.
AI enforces access control and segmentation
Founded in 2011, CrowdStrike is a cybersecurity company based in Austin, Texas. Its Falcon platform is an AI-native, cloud-delivered solution designed to provide comprehensive protection across various digital environments.
Falcon utilizes a single, lightweight agent to deliver real-time visibility and protection, integrating capabilities such as endpoint detection and response (EDR), next-generation antivirus, threat intelligence, and managed threat hunting. The platform’s architecture allows for rapid deployment and scalability, enabling organizations to unify their security operations and reduce complexity.
Key Features:
Managed threat hunting via Falcon OverWatch
Monitors for credential theft, lateral movement, and privilege escalation
Contextual intelligence to understand adversaries, anticipate attacks, and strengthen defenses
CyberArk was founded in 1999 and is now a publicly traded company on the NASDAQ (ticker symbol: CYBR) that serves 10,000+ customers across 110 countries. CyberArk offers a comprehensive Identity Security Platform that integrates intelligent privilege controls, continuous threat detection, and lifecycle management to enforce zero trust and least privilege principles across hybrid and multi-cloud infrastructures.
CORA AI, an advanced AI engine embedded throughout the platform, transforms identity-centric data into actionable insights and automates critical security functions, including anomaly detection, adaptive multi-factor authentication (MFA), and real-time policy recommendations based on user behavior.
Key Features:
Performs complex tasks via natural language commands
Zero trust and least privilege enforcement
Applies identity security principles to autonomous AI agents
Cynet, based in Boston, MA, offers an all-in-one cybersecurity platform designed to simplify and strengthen threat protection for organizations of all sizes, particularly small to medium-sized businesses (SMBs) and managed service providers (MSPs).
CyAI, its proprietary AI engine, leverages machine learning models trained on millions of samples to analyze executable files across endpoints, enabling the detection of both known and zero-day threats before they can cause harm.
Key Features:
Combines endpoint protection, NDR, UBA, and deception tech in one platform
Scalable for SMBs and MSPs
Built-in playbooks and automated workflows
Darktrace, based in the UK, leverages artificial intelligence to provide real-time threat detection and autonomous response across a variety of digital environments. Founded in 2013, the company has developed a platform that learns the unique patterns within a company’s network, enabling swift identification and mitigation of potential threats.
Darktrace’s Self-Learning AI builds an evolving understanding of “normal” behavior within a network by analyzing thousands of metrics. This enables the system to detect subtle variations that may indicate emerging threats, including novel malware and sophisticated cyberattacks.
Key Features:
Cross-domain visibility to detect multi-stage attacks
Explainable AI automatically investigates and interprets threats
Automatically takes action in real time to contain threats
Exabeam was founded in 2013 and is headquartered in Foster City, California. Exabeam’s Security Operations Platform uses AI and automation to streamline threat detection, investigation, and response.
Its Threat Center serves as a centralized workspace, while Exabeam Copilot—an AI assistant—offers real-time insights and recommended actions to speed up resolution. Machine learning models analyze large data sets to detect subtle anomalies and reduce false positives. Over time, the system learns from incidents to continually improve threat detection accuracy and response efficiency.
Key Features:
AI-driven playbooks to accelerate response workflows
Uses ML to detect anomalies based on typical user and device behavior
Learns from past security incidents to improve detection accuracy
Fortinet, established in 2000 and based in Sunnyvale, California, provides comprehensive security solutions that safeguard networks, data, and applications across diverse environments. Fortinet Security Fabric is the company’s integrated platform that unifies various security components, enabling seamless communication and coordinated defense mechanisms across an organization’s infrastructure.
With over 15 years of AI research and development and more than 500 AI-related patents, Fortinet has developed a mature AI ecosystem designed to enhance threat detection, automate security operations, and protect AI systems themselves. This AI-driven approach is exemplified by FortiAI, a suite of solutions that leverages machine learning and automation to address the evolving cybersecurity landscape.
Key Features:
Integrated platform unifies endpoint, network, cloud, and application security
Combines real-time threat detection, automated alert triage, and protection for AI models and data
AI-powered threat detection and automated incident response
Google Security Operations (Google SecOps) is a cloud-native, AI-driven platform designed to unify threat detection, investigation, and response (TDIR) across diverse environments. It integrates Security Information and Event Management (SIEM), Security Orchestration, Automation, and Response (SOAR), and threat intelligence capabilities into a cohesive system, enabling security teams to efficiently manage and respond to threats.
At the heart of Google SecOps is Gemini, an AI-powered assistant that enhances security operations through natural language processing and machine learning. Gemini allows analysts to perform complex searches using plain language, generate YARA-L detection rules, and receive contextual summaries of security incidents. It also assists in creating and editing response playbooks, streamlining the incident response process.
Key Features:
AI-powered threat detection and investigation
Integrated SIEM and SOAR
Cloud-native scalability
Hunters is a cybersecurity company offering an AI-driven, next-generation Security Information and Event Management (SIEM) platform designed to enhance the efficiency and effectiveness of Security Operations Centers (SOCs), particularly those with limited resources.
The company’s Pathfinder AI employs a network of specialized AI agents to autonomously investigate and correlate security data across various domains such as network, cloud, identity, and endpoints. These agents work collaboratively to prioritize threats, filter out noise, and generate comprehensive attack narratives, enabling security teams to focus on genuine threats without the burden of manual triage.
Key Features:
Pre-built detections with no manual rule-tuning needed
Automated correlation links alerts, filters noise, and prioritizes threats
Collects and normalizes data from tools like AWS and GCP for full visibility
Microsoft Security Copilot is a generative AI-powered assistant designed to enhance the efficiency and capabilities of security and IT professionals. By leveraging Microsoft's vast threat intelligence and integrating with various security tools, Security Copilot enables teams to respond to cyber threats at machine speed and scale.
Security Copilot combines a large language model with security-specific capabilities, allowing users to interact using natural language prompts. This facilitates tasks such as incident response, threat hunting, intelligence gathering, and posture management.
Key Features:
Built-in threat intelligence from Microsoft
AI-generated incident summaries and guided threat hunting steps
Supports custom plugins and workbooks
Founded in 2003, Mimecast specializes in advanced email and collaboration security solutions, protecting against a wide range of cyber threats, including phishing, malware, and business email compromise attacks. By leveraging AI technologies such as NLP, machine learning, and computer vision, Mimecast enhances its ability to detect and neutralize sophisticated cyber threats.
NLP enables the system to analyze the context and intent of email content, effectively identifying and blocking BEC attacks that rely on social engineering tactics rather than malicious attachments or links. It also offers a Misaddressed Email Protection feature, which leverages AI to monitor users’ email-sending patterns, alerting them when an email is being sent to an unrecognized or potentially incorrect address to prevent accidental data leaks.
Key Features:
Spots spoofed domains and fake branding
Smart archiving uses AI for email continuity and classification
Warns users before emailing the wrong recipient
Okta is a leading identity and access management (IAM) company that provides cloud-based solutions to secure user authentication and manage digital identities across enterprises. Founded in 2009, Okta offers a suite of services—including Single Sign-On (SSO), Multi-Factor Authentication (MFA), and Identity Governance—designed to streamline access control while enhancing security.
Okta AI leverages over a decade of identity data and threat intelligence to deliver real-time identity actions that enhance security and user experience. For instance, AI-driven features like Identity Threat Protection continuously assess risks and automate responses to identity-based threats, such as phishing and credential stuffing attacks. It also offers a Policy Recommender, which suggests optimal security policies based on organizational needs, and Adaptive MFA, which adjusts authentication requirements dynamically based on user behavior and context.
Key Features:
Adaptive MFA adjusts login security based on context
Policy Recommender suggests optimal access rules
Behavior analytics trackers user and entity actions
Proofpoint, founded in 2002, offers a comprehensive suite of cloud-based solutions designed to stop targeted threats, safeguard data, and enhance user resilience against cyberattacks. The platform’s AI engine, NexusAI, uses ML and deep learning techniques to analyze 100 billion+ data points daily to identify and block sophisticated cyber threats.
This includes detecting phishing campaigns, business email compromise (BEC) attempts, and anomalous user behavior in cloud accounts. NexusAI's ability to continuously learn from real-world threat data ensures that Proofpoint's security measures adapt to evolving attack vectors.
Key Features:
Smart classification tags sensitive data automatically
Email coaching trains users in real time
Detects threats with ML and flags unusual user actions
Founded in 2013 and based in Mountain View, California, SentinelOne’s primary offering is its Singularity™ Platform, which unifies endpoint protection, extended detection and response (XDR), identity threat detection, and cloud security into a single, AI-powered solution.
Purple AI, SentinelOne’s generative AI security analyst, empowers security teams by automating complex threat hunting and incident response tasks. Through a natural language interface, analysts can query security data, receive AI-generated summaries, and execute remediation actions, significantly reducing mean time to detect and respond to threats.
Key Features:
AI blocks threats in real time without cloud reliance
Rollback reverses ransomware damage automatically
Fast, scalable threat analytics across data sources
Shield AI is a San Diego-based defense technology company founded in 2015 that specializes in developing AI-powered autonomous systems for military applications. Hivemind, Shield AI’s AI pilot, enables unmanned systems to operate securely in highly contested and GPS-denied environments, where traditional systems fail. It doesn’t rely on remote control or communications infrastructure, dramatically reducing exposure to jamming, spoofing, and cyber interference.
Hivemind’s onboard autonomy eliminates the need for real-time data links, which are often the weakest link in electronic warfare. Instead, the system makes decisions locally, using AI for real-time mapping, threat detection, and navigation, even during signal-denied or adversarial conditions. This autonomy greatly enhances operational resilience while minimizing cyberattack vectors.
Key Features:
GPS-free autonomy reduces the risk of jamming and spoofing
Real-time AI mapping navigates threats on the fly
AI dogfighting trains against live threats
Founded in 1985 and based in Abingdon, Oxfordshire in the UK, Sophos has evolved from developing antivirus software to offering a comprehensive suite of security products and services. Since 2017, Sophos has embedded AI capabilities across its product portfolio, enabling the identification and mitigation of both known and novel cyber threats.
For instance, Sophos Intercept X employs deep learning neural networks to detect malware without relying solely on signature-based methods, thereby improving defense against zero-day attacks, and Sophos's Extended Detection and Response (XDR) platform incorporates GenAI features that assist security analysts in accelerating investigations.
Key Features:
Spots known and unknown malware without signatures
Summarizes threats and suggests actions
AI models refined by Sophos X-Ops intelligence for live threat updates
Zscaler, headquartered in San Jose, California, is most well-known for its Zero Trust Exchange platform that facilitates secure, direct-to-cloud connections, eliminating the need for traditional network security appliances. The company's AI-driven capabilities enable real-time threat detection and response, leveraging vast datasets to identify and mitigate sophisticated cyber threats.
For instance, Zscaler's AI-powered phishing prevention system analyzes over 300 trillion daily signals to detect and block credential theft and browser exploitation attempts. Additionally, its AI-powered segmentation simplifies user-to-application segmentation, minimizing attack surfaces and preventing lateral movement within networks.
Key Features:
AI threat detection blocks threats in real-time
Zero-trust segmentation automates user-to-app segmentation
Secures tools like ChatGPT with prompt inspection
Tips for Selecting the Best AI Security Company
Choosing the best AI security company in the evolving AI-driven threat environment requires more than simply examining AI-based product assertions. The wrong choice can lead to blind spots, false confidence, or wasted time. Here’s what to look for when evaluating AI security companies.
Define Your Security Priorities
First, clarify what you need from an AI security company. Do you need to protect AI systems such as LLMs and vision models from adversarial threats? Or are you looking for vendors that apply AI technology to enhance your overall cybersecurity posture?
Evaluate the Depth of AI Capabilities
Don’t take “AI-powered” at face value. Ask how machine learning or generative AI is actually being used. Does the system have the ability to identify new threats while correlating unrelated signals and autonomously adapting over time?
The best AI systems reduce your analysts’ workload rather than just restructuring manual tasks. Choose vendors that showcase practical, real-time anomaly detection methods combined with behavioral analytics and automated response capabilities.
Look for Seamless Integration
Your security stack is already complex. New tools should integrate seamlessly with your existing security systems, such as SIEM, SOAR, EDR, cloud platforms, and identity systems. Choose products that provide APIs while also offering built-in connectors and automation capabilities. Stay away from vendors that need custom plumbing or require you to completely change your workflows to realize value.
Prioritize Real-World Results
Case studies, benchmarks, and third-party validation matter. Ask AI security vendors for proof that their AI improves detection rates, reduces dwell time, or streamlines investigations. Talk to current customers if possible. You want a company that performs well under pressure.
Final Thoughts
AI dynamics change rapidly, and so do the threats. Whether you're defending AI systems or using AI to secure your infrastructure, choosing the right security partner is critical. From email protection to endpoint defense and adversarial testing, the companies in this list represent a range of capabilities tailored to modern threats.
For organizations looking to secure their AI systems at the model level, Mindgard’s Offensive Security solution stands out. Our platform’s automated red teaming, real-time threat detection, and deep integration with CI/CD pipelines provide robust, continuous protection across the AI lifecycle.
With a foundation rooted in academic research and a platform aligned with MITRE ATLAS™, Mindgard offers a purpose-built, offensive security approach to identifying and neutralizing AI-specific vulnerabilities, making it a strong choice for enterprises serious about securing their AI stack. Request a demo to learn more.
Frequently Asked Questions
How do AI security companies differ from traditional cybersecurity firms?
Traditional cybersecurity focuses on networks, endpoints, and cloud infrastructure, while AI security companies specialize in:
Protecting AI models (e.g., LLMs, vision systems) from adversarial attacks.
Leveraging AI to improve threat detection, automate responses, and analyze behavior anomalies at scale.
Can AI security tools replace human security teams?
No, AI security tools can’t replace human security teams, but they can augment human analysts by:
Reducing false positives
Automating repetitive tasks (e.g., alert triage)
Providing real-time threat insights
Human oversight remains critical for complex decision-making
What’s the difference between AI-native and AI-bolted security solutions?
AI-native security solutions like Darktrace and Vectra AI are built from the ground up with AI core to their functionality. AI-bolted solutions are traditional tools with added ML features, although these tools may lack depth in protecting against AI-specific threats.
How do AI-powered email security tools (e.g., Abnormal Security) work?
These tools use behavioral AI to model normal user and email activity, flagging anomalies like phishing attempts, impersonation, and business email compromise based on context rather than static rules.
How do I evaluate an AI security vendor’s effectiveness?
Assess their threat detection depth (e.g., adversarial attack coverage), ability to secure AI pipelines, runtime monitoring capabilities, integration flexibility, and credibility through case studies, benchmarks, or MITRE ATLAS™ alignment.
| 2025-06-06T00:00:00 |
https://mindgard.ai/blog/best-ai-security-companies
|
[
{
"date": "2025/06/06",
"position": 25,
"query": "AI employers"
}
] |
|
News - Stanford HAI
|
Stanford HAI
|
https://hai.stanford.edu
|
[
"Shana Lynch"
] |
... AI's abilities, and highlights areas ripe for research and development. Explore all the latest from HAI. AllNewsMedia MentionsAnnouncements. Explore all the ...
|
As part of Stanford's emphasis on advancing responsible AI, Stanford HAI and the Stanford Artificial Intelligence Lab (SAIL) are teaming up to build on their existing legacies on the foundations, development, applications, and study of AI technologies.
| 2025-06-06T00:00:00 |
https://hai.stanford.edu/news
|
[
{
"date": "2025/06/06",
"position": 79,
"query": "AI journalism"
},
{
"date": "2025/06/06",
"position": 75,
"query": "artificial intelligence journalism"
}
] |
|
Is AI beginning to replace human jobs? 7 major layoff ...
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Is AI beginning to replace human jobs? 7 major layoff announcements raise concerns
|
https://www.cnbctv18.com
|
[] |
Several major tech and retail companies have announced significant layoffs, with some explicitly linking the cuts to AI adoption and automation.
|
1 / 7
Procter & Gamble (P&G) announced on June 5 that it plans to cut 7,000 jobs over the next two years as part of its efforts to build a more agile organisation. While it is not yet clear which regions or divisions will be impacted, the company expects to incur over $1 billion in pre-tax restructuring costs across FY25 and FY26. These will cover severance, transition, and system changes.
2 / 7
Citigroup, also on June 5, said it plans to lay off around 3,500 technology roles in China as part of its cost-cutting strategy. In January last year, the US bank had already announced plans to reduce 10% of its global workforce, affecting approximately 20,000 employees.
3 / 7
Walmart intends to cut around 15,000 jobs across its global workforce, impacting its technology operations, e-commerce fulfilment in US stores, and advertising division Walmart Connect, according to a Reuters report dated May 21.
4 / 7
Walt Disney is set to lay off several hundred employees across its film, television, and corporate finance divisions, Reuters reported on June 2. This marks the fourth round of layoffs in just 10 months.
5 / 7
IBM plans to let go of around 8,000 employees, primarily within its Human Resources (HR) department, as it integrates artificial intelligence (AI) into its operations and back-office functions. The company had previously replaced about 200 HR roles with AI tools to handle repetitive administrative tasks.
6 / 7
Microsoft, on May 16, announced its second-largest round of layoffs, planning to cut 6,000 jobs—around 3% of its workforce—across all teams. The move is aimed at flattening the organisational structure and reducing management layers.
7 / 7
| 2025-06-06T00:00:00 |
2025/06/06
|
https://www.cnbctv18.com/photos/technology/ai-taking-real-human-jobs-layoffs-tech-19616315.htm
|
[
{
"date": "2025/06/06",
"position": 89,
"query": "AI layoffs"
}
] |
Experts offer advice to new college grads on entering the ...
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Experts offer advice to new college grads on entering the workforce in the age of AI
|
https://www.cbsnews.com
|
[
"Mary",
"Reporter",
"Mary Cunningham Is A Reporter For Cbs Moneywatch. Before Joining The Business",
"Finance Vertical",
"She Worked At",
"Minutes",
"Cbsnews.Com",
"Cbs News As Part Of The Cbs News Associate Program.",
"Read Full Bio",
"Alain"
] |
"There are signs that entry-level positions are being displaced by artificial intelligence at higher rates than the roles above them," said Matthew Martin, ...
|
Futurist explains how AI will change the way we live and work
New college graduates this year face an especially daunting task — putting their degrees to work just as "generative" artificial intelligence technology like ChatGPT is beginning to change the American workplace.
"We are entering an entirely new economy, so the knowledge economy that we have been in for the last 50 years or so is on the way out, and a new economy is on the way in," Aneesh Raman, Chief Economic Opportunity Officer at LinkedIn, told CBS MoneyWatch.
The impact of AI on Americans recently out of college is already visible across a range of industries and jobs, from technology and finance to media, legal fields and market research. As a result, for the first time unemployment among fresh grads recently surpassed the nation's overall jobless rate — a shift some experts attribute in part to the creeping influence of AI.
"There are signs that entry-level positions are being displaced by artificial intelligence at higher rates than the roles above them," said Matthew Martin, senior U.S. economist at Oxford Economics.
With the adoption of AI at work only expected to accelerate, we asked three experts across academia, recruitment and consulting for advice on how new college grads should navigate this new normal. Here's what they said.
Become fluent in AI
Perhaps most important, young job-seekers start using gen-AI tools — today.
"Almost anybody in that audience, irrespective of the job that they're pursuing, will be expected to use AI with some facility right away," said Joseph Fuller, a professor at Harvard Business School and founder of the Managing the Future of Work project, comparing the task to learning how to use Microsoft Office for a previous generation of grads.
To get the ball rolling, experts encourage those who are starting to hunt for work to familiarize themselves with the array of tools at their disposal, such as Anthropic's Claude or OpenAI's ChatGPT. That means learning how to engage with such tools beyond simply using them as a search engine.
"You want to get in a dialogue with it," Fuller said. "You want to ask it to take different perspectives."
Emily Rose McRae, an analyst at research and advisory firm Gartner, said learning how to use AI apps can also be a good way to develop transferable skills. For example, asking AI to summarize documents and then validating its findings to ensure accuracy.
Meanwhile, although AI can be helpful when it comes time to filling out job applications, users should proceed with caution given that recruiters can often spot AI-generated language, experts note. Nearly two-thirds of job candidates today use AI at some point in the application process, according to a report from recruitment firm Career Group Companies.
"If you're using it to write your cover letter and your resume and you did not review it, everyone can tell," McRae said.
Another way to gain potentially valuable experience with AI, while also seeking work, is for interview practice. For example, users can ask the chatbot both to provide sample questions they might face in an interview and then rate the quality of their responses.
"If you are using it as a tool to get your own understanding of self in interviews, you're going to start being leaps ahead of everyone else," Raman said.
Hone your soft skills
Experts say that as AI surpasses humans in executing certain tasks — think actuarial math or corporate compliance, for example —more attention will shift to job candidates' so-called soft skills, such as problem solving and communication.
"You cannot outsource your thinking to AI," LinkedIn's Raman said. "You have to continue to hone critical thinking and complex strategy thinking."
The focus will be less on your pedigree — where you went to school or even whether you have a college degree — he added, and more on what he calls the "5 Cs": curiosity, compassion, creativity, courage and communication.
To improve their soft skills, Fuller encourages entry-level job candidates to work on turning what they regard as their biggest weakness into a strength. For instance, if you typically shy away from public speaking or talking in groups, push yourself to get comfortable in those situations.
"The inability to do that is going to be penalized more severely in the work of the future than it has been in the past," he said.
The Harvard professor also suggested highlighting examples of advanced social skills directly on your resume to help paint a picture for recruiters of how you can contribute to the workplace.
Choose your employer wisely
Beyond skills development, experts say college grads should be thoughtful about the type of company they choose to work at, knowing that AI could drastically alter the business in the coming years.
"The most important thing, if you're a new grad, is where you work — not what you do at the place you're going to work," Raman told CBS MoneyWatch.
He encouraged college graduates to seek out employers that are integrating AI responsibly and with respect for their workforce — as opposed to embracing it chiefly to replace people. Companies that are adapting to what is a major technological shift in real time will typically offer the best opportunities for learning and growth, Fuller said.
In evaluating a prospective employer, young job candidates should try to gain an understanding of how they fit into the company's future. For example, McRae recommends asking hiring managers up front what types of investments the organization is making in its employees and what the room for growth looks like.
"What are they telling me they care about? What do career paths look like for this role like now? How do you help people develop the skills they need to become experts?" she said.
In researching companies, McRae also encouraged recent college grads to look for places that offer apprenticeship or rotational programs, which can offer ways to quickly ramp up their knowledge base, especially if traditional entry-level roles are in short supply.
| 2025-06-06T00:00:00 |
https://www.cbsnews.com/news/ai-jobs-chatgpt-college-graduate-work/
|
[
{
"date": "2025/06/06",
"position": 8,
"query": "ChatGPT employment impact"
}
] |
|
New Tulane study finds generative AI can boost employee ...
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New Tulane study finds generative AI can boost employee creativity—but only for strategic thinkers
|
https://news.tulane.edu
|
[] |
A new study led by Tulane University researchers reveals that generative AI tools, such as ChatGPT, can enhance employees' creativity.
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A new study led by Tulane University researchers reveals that generative AI tools, such as ChatGPT, can enhance employees' creativity — but only if they know how to think critically about their own work and utilize the tools effectively.
The study, set to be published in the Journal of Applied Psychology, is one of the first field experiments to investigate the impact of large language models (LLMs) on creativity in real-world work settings. Researchers worked with a technology consulting firm and randomly assigned 250 employees to either use ChatGPT or not during a regular workweek. Supervisors and outside reviewers evaluated their creativity.
Employees with access to AI performed better— generating more novel and practical ideas— than those who didn’t use the tool. But the boost wasn’t equal across the board.
"If we want people to thrive alongside AI, we need to start treating metacognitive skill development as a foundational part of education and professional training in the AI era." - Shuhua Sun
The employees who benefited most weren’t just using ChatGPT passively. They were actively thinking about how to approach their work, what problems they were trying to solve, and how best to use AI to support their goals. In short, they were skilled at managing their own thinking— planning, reflecting, and adjusting their approach as needed.
“Generative AI use doesn't automatically make people more creative. It boosts creativity only for employees who use ‘metacognitive strategies’ — those who actively analyze their tasks, monitor their thought processes and adjust their approaches,” said lead author Shuhua Sun, who holds the Peter W. and Paul A. Callais Professorship in Entrepreneurship at Tulane University’s A. B. Freeman School of Business.
These findings have significant implications for companies investing in AI to drive innovation. Simply rolling out tools like ChatGPT isn’t enough, the researchers say. To achieve results, companies also need to help employees develop better thinking habits— including how to assess problems, adjust strategies, and utilize new resources.
“Even the most advanced generative AI systems won’t enhance creativity if employees are passive consumers of their output and lack the metacognitive strategies needed to engage with them effectively. To unlock AI’s potential for boosting workplace creativity, organizations must go beyond simply deploying new tools—they also need to invest in developing employees’ metacognitive skills and promote thoughtful, strategic use of AI to acquire the cognitive job resources that support creative thinking,” Sun said.
The good news, according to the study, is that these thinking skills can be taught. The researchers point to short training programs that help workers become more intentional in how they plan, monitor, and adapt their work— all of which make them more effective at using AI tools creatively.
The study’s implications extend beyond the workplace. Sun and his coauthors urge educators and policymakers to treat metacognitive skill development as a core priority in preparing students and workers for the age of AI. While education systems have long emphasized cognitive skills, they have often paid less attention to developing metacognitive abilities—skills that will be essential as AI becomes an everyday tool in the future of work.
“If we want people to thrive alongside AI, we need to start treating metacognitive skill development as a foundational part of education and professional training in the AI era,” Sun said.
The study also included researchers from Renmin University of China, Nanyang Technological University, Rice University, and the Massachusetts Institute of Technology.
| 2025-06-06T00:00:00 |
https://news.tulane.edu/pr/new-tulane-study-finds-generative-ai-can-boost-employee-creativity-only-strategic-thinkers
|
[
{
"date": "2025/06/06",
"position": 15,
"query": "ChatGPT employment impact"
}
] |
|
13 Ways to Use ChatGPT at Work to Boost Your Workflow
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13 Ways to Use ChatGPT at Work to Boost Your Workflow
|
https://undetectable.ai
|
[
"About Christian Perry",
"Christian Perry Is The Founder",
"Ceo Of Undetectable Ai",
"Ranked The Best Ai Detector In The World Forbes",
"Responsible For The Most Advanced Humanization Technology On The Market. He Drives Ai Innovation With A Focus On Creating Tools That Help People Excel In Both Professional",
"Academic Environments. He Has Shared His Expertise In The Fields Of Ai",
"Machine Learning Technology On Prominent Outlets Such As Business Insider",
"Forbes",
"Nbc",
"Fox"
] |
As there are many practical uses of ChatGPT at work, let's focus on the ones that can give you the most positive impact without needing to do too much work.
|
As technology gets better and better, new tools will continue to emerge that optimize our lives and daily activities.
ChatGPT is one of those innovations that changes the way we approach work and academics. And using ChatGPT at work can make a big difference in your results.
The way we work is constantly evolving, offering new opportunities that help us optimize productivity and make life easier at our jobs.
ChatGPT has lead the latest wave of this kind of innovation.
In this article, we are going to share 13 effective strategies to seamlessly integrate ChatGPT at work and into your professional world so you’re able to unlock its full potential while improving the efficiency and effectiveness of your day to day tasks at hand.
Key Takeaways
ChatGPT optimizes workflow by assisting with tasks like automating repetitive work, generating creative content, researching, and summarizing information.
It offers advanced capabilities including voice interaction for hands-free operations and image handling for visual content creation, expanding its application contexts across diverse sectors like design, marketing, and healthcare.
Effective use of ChatGPT requires providing clear instructions, carefully reviewing its output for accuracy, and being prepared to edit and revise the content to meet specific needs and maintain a human touch.
Key practical applications include summarizing documents, generating ideas, creating various text formats (e.g., slogans, ad copy), translating languages, writing/polishing content, outsourcing mundane tasks, analyzing data, and assisting in decision-making and presentation development.
While highly beneficial, challenges include potential for added complexity, connectivity dependency for some features, and the crucial need to humanize AI-generated content (e.g., with Undetectable AI) to avoid detection and ensure natural readability.
How Does ChatGPT Work?
ChatGPT uses advanced AI to communicate with users via text-based messages.
The OpenAI system is trained with data sets that capture the ins and outs of human language and reproduce them as accurately as possible.
But it is only accurate to a certain degree.
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That’s why it is so important to use our ChatGPT Detector to see if it will be flagged as written by AI.
If it is, and most likely it will be if no revisions are made, you should use the Undetectable AI Humanizer to make the content read as if it were written by a human and pass all AI detectors.
At the core of ChatGPT is machine learning that constantly improves over time.
The system is trained with countless data sets to help better understand and respond to questions and commands as accurately as possible.
This adaptability is what sets ChatGPT apart and makes it an invaluable tool across various domains.
How to Use ChatGPT’s Custom Instructions?
You must provide precise instructions to control ChatGPT’s responses and adapt them to the specific needs of your work to ensure that the results meet your expectations.
This gives users more control. The more control you have, the better the result will be.
You can tailor ChatGPT to meet the specific requirements of your tasks at hand.
Doing so helps the results align closely with your desired outcome, enhancing the overall efficiency and effectiveness of your work.
ChatGPT is more than just an AI program.
It is a versatile tool that will increase your productivity and significantly improve your results when used the right way.
By understanding how the program works and providing accurate instructions, you can use ChatGPT in various professional areas and for creative purposes.
Exploring ChatGPT’s Voice and Image Capabilities
ChatGPT communicates via text-based messages and images.
This not only diversifies the possible applications but also opens the door for a more comprehensive and holistic integration into different work contexts.
Voice Interaction: Turning Words into Action
The ability to interact with the user via voice commands not only gives the program a natural feel but also changes the way we consume and produce information.
We can solve complex tasks, conduct research, or create content using only voice commands.
This is particularly helpful in areas where typing is not possible because hands are busy.
Image Handling: Turning Concepts into Visual Reality
Since ChatGPT can also process images, it becomes a valuable ally for creative minds such as designers who want to create visual content.
Visual content like appealing presentations and even the understanding of complex concepts through visual representations become possible.
Application Contexts in Organizations
The areas of application of ChatGPT’s voice and image functions are very diverse and can come in very handy to professionals seeking a wide variety of tools.
In businesses, voice functionality can be used to streamline administrative tasks and enable the creation of emails, reports, or messages without typing.
In addition, they can be used for the automated creation of visual content for presentations, reports, or promotional material.
Assistance in Specific Sectors
Sectors like education, graphic design, marketing, and even healthcare can benefit tremendously from ChatGPT’s advanced features.
Healthcare professionals, for example, can dictate patient transcriptions, while designers can receive contextually relevant visual suggestions for their projects.
Facilitating Innovation in Software Development
In software development, voice interaction can expedite code creation while allowing software developers to better express their ideas much faster.
Image manipulation can be used to create visual prototypes or to understand the structure of new software more quickly.
Challenges and Opportunities
Although these voice and image functions offer innovative possibilities, they also bring with them some challenges.
Security, accuracy and the need for specific training to understand certain contexts are important considerations that should be taken into consideration when integrating ChatGPT into everyday work.
The advanced features represent a remarkable development that not only offers a better experience but also paves the way for significant innovations in various professional sectors.
Why Create Images with Artificial Intelligence Using ChatGPT?
The ability to create images with ChatGPT adds visual dimension to your tasks.
This is particularly useful for presentations, design demands, or other situations where graphic elements are a must.
Practical Ways to Use ChatGPT at Work
As there are many practical uses of ChatGPT at work, let’s focus on the ones that can give you the most positive impact without needing to do too much work.
The more you can get out of this tool, the better you will become at your job.
Streamlining processes that take a lot of time or demand a lot of effort should be where you focus your efforts when incorporating ChatGPT in your workflow.
Doing so will make you more efficient and valuable at the job.
Automating Repetitive Tasks
ChatGPT can be used to automate routine tasks. This saves valuable time and resources.
Being able to speed up the mundane tasks that take a lot of time is a big bonus. It’s better to work smart than work hard.
And if you are spending loads of time doing grunt work that can easily be outsourced to ChatGPT, you will be able to focus more of your time on the stuff that brings the biggest results and helps you stand out at work.
Generating Creative Content
ChatGPT can be a valuable source of innovative ideas and creative concepts.
Creating content can take a long time if done manually. Not only do you need to think of the ideas, but you need to create the content as well.
ChatGPT can help you do both. You can create lists of content ideas that are relevant to your brand and then have the content created by ChatGPT itself.
Just don’t forget to humanize the content with Undetectable AI as mentioned earlier. This way, you will avoid AI detectors when putting your content out to the world.
Researching and Summarizing Information
ChatGPT makes it easier to research and summarize extensive data.
It offers an efficient approach to obtaining relevant information.
This is another one of the great things about utilizing ChatGPT into your arsenal.
Any of these time-consuming and simple-minded tasks that can be automated should be to save you time to focus on higher level demands that bring bigger results.
Providing Customer Service
Integrating ChatGPT into the customer support system can ensure the delivery of faster and more accurate responses.
It can also save you tons of time doing something that is quite easy to be automated by utilizing message sequencing that can be handled by a bot.
The responses used in the automation can easily be created by ChatGPT to make life more efficient.
What Are the Challenges of Using ChatGPT at Work?
Despite the numerous advantages, ChatGPT still faces some challenges in the workplace.
The need to provide clear instructions and the risk of inaccurate output in certain contexts are some of the biggest obstacles that need to be overcome when getting started.
So how does one get things kicked off when incorporating ChatGPT into your workflow?
Initiation to ChatGPT at Work: Navigating the Initial Steps
To make the most of the many capabilities of ChatGPT, it’s important to understand the basic steps.
Here is a step-by-step guide on how to begin your journey with ChatGPT so you don’t make any mistakes that can come back to haunt you later on:
1. Create your OpenAI Account:
The first step is to create an account with OpenAI. Access the website, follow the registration process, and familiarize yourself with the terms of use.
By creating an account, you gain access to ChatGPT’s exclusive features.
2. Ask ChatGPT a Question:
After creating your account, test the functions by asking ChatGPT a question.
Be clear and specific in your prompt in order to get the most relevant answer possible. ChatGPT is designed to understand a wide range of questions and commands.
Feel free to experiment with different approaches to find what works best for you and the results you are hoping to achieve.
3. Interact with ChatGPT’s Responses:
Interaction is key to unlocking the full potential of ChatGPT and optimizing the texts that are being produced for you.
Once you have received your first answer, you must evaluate it critically. ChatGPT is flexible and can continue building out better and better responses based on your interactions and prompts.
The program can provide creative insights and useful information, but it is not error-free. Not even close. Continuous interaction will improve the accuracy and relevance of responses.
Additional Tips for an Enhanced ChatGPT Experience:
The ChatGPT journey doesn’t stop with your interactions. You need to keep building out your approach in order to optimize your results and to have a better overall experience.
The more you communicate with ChatGPT, the more specific you are, and the more you train yourself on how to engage with your communication, the better your experience will be in the long run.
Try Custom Instructions:
Give specific, custom instructions to better tailor ChatGPT’s responses to your specific needs.
This leads to better results and content that won’t be as robotic or cliche that most people are used to seeing from ChatGPT and other AI-content generators.
Utilize Multimedia Capabilities:
Go beyond plain text by experimenting with ChatGPT’s voice and image features. This significantly broadens your options and allows for a richer and more diverse interaction.
You will also be able to create content that is more impactful for you business if you deliver more than just what’s expected from you. Always under-promise and over-deliver.
Deep Dive into Specific Tasks:
Guide ChatGPT with specific tasks, such as code generation, content creation, or data analysis. The more specific and targeted your instructions are, the better the results will be.
Be Aware of Limits:
Keep in mind that while ChatGPT produces impressive results, it also has limitations.
In complex or sensitive situations, it is advisable to check the answers and only use ChatGPT as a support tool.
The answers should always be complemented by your own experience and judgment.
And as mentioned, the humanization process to ensure that you aren’t delivering content that will be easily flagged by AI detectors.
By following these tips, you will be well-positioned to explore the full potential of ChatGPT, integrate it into your workflow, and leverage its advanced capabilities to boost productivity and creativity.
13 Ways to Use ChatGPT at Work
ChatGPT’s versatility exceeds many people’s basic expectations of its capabilities and offers an impressive range of features that can improve various areas of our daily tasks at work.
Let’s highlight 13 ways to incorporate ChatGPT into your professional routine:
1. Summarize Documents
Automate the process of summarizing large documents and gain a quick understanding of essential content without the need for detailed reading.
Not only will this speed things up but it will give you a better understanding of what’s coming across your desk and what is happening at the company.
2. Generate Ideas
Use ChatGPT to generate innovative ideas for projects, marketing campaigns, or to find solutions to complex problems.
Brainstorming with a group can be a lot of fun and lead to some great ideas. But sometimes, we are on our own.
And when that’s the case, brainstorming with ChatGPT is a great way to come up with loads of ideas that can eventually be executed and put into the road map.
3. Create Creative Text Formats
Take advantage of ChatGPT’s ability to generate creative texts, form catchy slogans, produce engaging narratives, or throw together ad copy for your advertising content.
Why not take advantage and lighten the load when it comes to creating your ad campaigns?
Using ChatGPT to help with the heavy lifting will let you focus on optimizing the campaigns and driving more business.
4. Translate Languages
Simplify the translation of documents into different languages, ensuring accurate and efficient understanding.
Going global with your business has never been easier. If you want to go into a new market, you don’t need a massive team of boots on the ground to make it happen anymore.
You can localize into new markets without even stamping your passport.
5. Write and Polish Content
Use ChatGPT to create high-quality content, e.g. articles, blog posts, or when reviewing existing content.
As mentioned earlier, don’t forget to humanize that content with our AI Humanizer before hitting publish.
This way, you’ll avoid detection by AI detector tools and put out content that engages your audience and ranks on Google to drive new traffic to your brand.
6. Outsource Mundane Tasks
No one likes doing mundane tasks, that should go without saying. So why not make ChatGPT do it for you?
Automate repetitive, mundane tasks so you can focus on strategic and more demanding activities.
7. Analyze Data
Not all companies have teams big enough or pockets deep enough to hire data scientists and analysts.
Sometimes, we need to make due with the resources we have available to us. So why not use ChatGPT to help with your data analysis needs?
Use ChatGPT to analyze complex data sets and identify patterns, trends, and valuable insights that can be used to make informed decisions.
8. Help You Find Information
ChatGPT makes it easier to search for specific information and research the work you need to produce.
Utilizing ChatGPT to do this research for you will save tons of time and provide more accurate results in extensive research.
9. Make Better and Faster Decisions
Integrate ChatGPT into the decision-making process. Receive quick insights that can inform strategic decisions.
Anytime you have the opportunity to streamline things at work, you should jump at the chance.
Making your role more efficient can open up new opportunities for you to grow both your business and your role in it.
10. Develop Presentations
Putting together presentations can be a tedious process. But not if you have help.
Create impactful presentations with ChatGPT. Create outlines, suggest content, structure, and even generate visuals to enrich your slides.
11. Create Software Applications
Use ChatGPT when developing new software applications. You can generate code or provide insights into architecture and functionalities.
This is a great option for lean startups with small teams and budgets that have big ideas and need to execute.
12. Debug and Understand Code with ChatGPT
ChatGPT can assist in debugging complex code, giving you a better understanding of logic and identifying errors.
Being able to do this without having a technical bone in your body when it comes to code will save tons of time and hassle.
13. Plan Your Day
Increase your productivity by using ChatGPT to plan, prioritize, and set meaningful deadlines for everyday tasks.
By incorporating ChatGPT into various areas of your work, you can leverage the full potential of this innovative tool while also boosting efficiency and creativity in the professional environment.
For even more productivity hacks, check out here.
Can ChatGPT Refuse to Answer Prompts?
Yes, in certain cases ChatGPT may refuse to respond to prompts if they violate its ethical guidelines or contain confidential information.
ChatGPT still offers significant potential to improve the workflow by ensuring efficiency, automation, and creativity.
Explore the different ways discussed above to integrate ChatGPT into your arsenal and increase productivity so you can achieve exceptional results.
See our AI Detector and Humanizer in action—just use the widget below!
Conclusion
ChatGPT is a powerful AI content tool that should be used to help you with your productivity.
While it’s advised to never just copy and paste your results without first making revisions and humanizing your content, it is advised to incorporate ChatGPT into your workflow or academic career to make life more efficient and productive.
When using ChatGPT to help assist you in your content production, make sure to use our ChatGPT Detector first and then humanize the content with our AI Humanizer tool.
| 2025-06-06T00:00:00 |
2025/06/06
|
https://undetectable.ai/blog/chatgpt-at-work/
|
[
{
"date": "2025/06/06",
"position": 87,
"query": "ChatGPT employment impact"
}
] |
Artificial Intelligence for Human Resources - IBM
|
Artificial Intelligence for Human Resources
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https://www.ibm.com
|
[] |
Usher in a new era with AI in human resources, where data analytics, ML and automation can work together to save people time and support better outcomes.
|
Artificial intelligence (AI) in human resources (HR) refers to the application of AI technologies to transform traditional HR functions and processes. It involves using a combination of algorithms, machine learning models and intelligent systems to automate repetitive tasks, gain deeper insights from HR data and support decision-making across an organization. These technologies also improve the employee experience by reducing friction and empowering HR professionals to focus on more creative or sensitive personnel issues.
AI in HR deploys various technologies capable of analyzing vast troves of data in real-time, recognizing patterns, generating content and simulating human-like interactions. These capabilities are changing how HR departments operate, allowing them to move from primarily administrative functions to more strategic roles within organizations.
Today’s HR leaders face multiple challenges: Evolving employee expectations, a global labor shortage and a growing skills gap. And with AI disrupting the business landscape at such a rapid pace, HR departments stand to play a significant role in managing change. According to research from the IBM Institute for Business Value, only 20% of executives say HR owns the future of work strategy at their organization. Which begs the question: If HR doesn’t own the future of work, who will? The technology, with its promise to upend the business landscape, is as much an HR initiative as an IT concern.
| 2025-06-06T00:00:00 |
https://www.ibm.com/think/topics/ai-in-hr
|
[
{
"date": "2025/06/06",
"position": 69,
"query": "artificial intelligence employment"
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{
"date": "2025/06/06",
"position": 98,
"query": "workplace AI adoption"
}
] |
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AI Surveillance Won't Stop Theft, but It Might Stop Unions
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AI Surveillance Won’t Stop Theft, but It Might Stop Unions
|
https://prospect.org
|
[
"Caleb Brennan"
] |
AI monitoring, for example, helps prevent theft at self-checkout kiosks by using cameras, sensors, and machine learning to analyze data and detect suspicious ...
|
× Expand Aaron M. Sprecher via AP Stores like Walmart seem a lot more excited about using surveillance tools on their own employees than on criminals.
Artificial intelligence, at least according to its most prominent backers, is going to revolutionize every industry in the country—including the people tasked with protecting retailers from shoplifters. In a special edition of the trade publication Loss Prevention Magazine (LPM), which bills itself as the premier periodical for “asset protection professionals,” AI is presented as an exciting opportunity for the retail industry.
Sandwiched between jargon-laced articles about “Promoting a Data-Driven Culture” and how AI can help assess “voice stress to pinpoint possible signs of deception” among detained shoplifters, LPM assures readers that enhancing the local Whole Foods or REI with state-of-the-art surveillance tech is a “no-brainer.” After all, LPM has argued in the past that retail theft is on the rise across the country.
Such advances in AI would supposedly augment and speed up key tasks in retail security, like analyzing CCTV footage. “As opposed to the laborious process of watching hours of video, AI monitoring, for example, helps prevent theft at self-checkout kiosks by using cameras, sensors, and machine learning to analyze data and detect suspicious activity,” says one feature in LPM.
More from Caleb Brennan
Though the chatter of a business-to-business magazine might seem benign, the pages of LPM reveal a candid portrait of how retail owners and management examine the social and economic landscape of the customers they serve and the workers they employ. For example, consider an LPM white paper on worker safety in retail: In the report, 1 in 4 workers are considering quitting their jobs not because of work conditions or stagnant wages, but because of the threat of amorphous, The Warriors-style gang members besieging Walmart.
Such developments portend a potential troubling future for retail employees, transforming their workplace—which employs more than a quarter of all U.S. workers—into an AI-powered panopticon. In this brave new world of worker surveillance, innocuous behavior will be criminalized, safety will be weaponized, and the ability to exercise one’s legally protected right to organize a union will be endangered.
WORKPLACE SURVEILLANCE, OF COURSE, is nothing new. At the turn of the 20th century, the hot new trend for manufacturing—similar in size then to retail today—was called “Taylorism.” This theory of employee supervision, pioneered by Frederick Taylor and also called “scientific management,” sought to maximize labor productivity as much as possible through elaborate tracking of workers’ time and movements. Managers could use stopwatches, time sheets, and other tools to ensure that not a single second of the working day would be “wasted.”
As the writer Robert Kanigel observed in his biography of Taylor, workers experienced even this rudimentary surveillance as tyrannical. A 1911 investigation by a Special House Committee concluded that the circumstances of Taylor’s methods were “the same as a slave driver’s whip on the negro, as it keeps [the worker] in a constant state of agitation.”
Taylor retorted that his system actually made workers more content in their labor. “I wish to state that until this last year, during the 30 years that scientific management has been gradually developed … there has never been a single strike of employees working under scientific management,” he told the Special Committee. Whether his system was actually just very good at controlling resentful people seems not to have occurred to him.
In this brave new world of worker surveillance, innocuous behavior will be criminalized and safety will be weaponized.
When workers did become recalcitrant, surveillance remained a key form of control. The Pinkertons, a notorious union-busting private security firm, used spying heavily to keep workers down in the late 19th and early 20th centuries. Their motto, “We Never Sleep,” often felt literal: Pinkerton spies were known not only to assault striking workers but also to infiltrate clandestine union meetings and collect names of all participants. (Incidentally, LPM praised the rebranded Pinkerton company in 2024. “Pinkerton stands at the forefront of retail security—vigilantly protecting what matters most in an industry where risks are as diverse as the products on the shelves,” an article from 2024 reads.)
Today, bosses don’t need armed thugs to enforce productivity rules; digital surveillance can do the job. Take the case of British banking conglomerate Barclays, which in 2020 was caught and fined for using heat and motion sensors to assess the amount of time its workers were spending at their desks.
As the academics Antonio Aloisi and Valerio De Stefano point out in their book Your Boss Is an Algorithm, we are living in a dystopia of employee monitoring. From ActivTrak, which “inspects the programs used and tells bosses if an employee is unfocussed, spending time on social media,” to Hubstaff and Sneek, which can “routinely take snapshots of employees through their webcams every five minutes or so to generate a timecard,” there is now a smorgasbord of Orwellian technology for managers.
Yet surveillance for loss prevention—which as an industry is quietly projected to double in value by 2030—is arguably even more pernicious due to its dubious motivations and the high likelihood that the data it gathers will be used for other purposes, particularly union busting. That this transformation in workplace surveillance coincided with sensationalized stories of lawless shoplifting sprees feels convenient for those seeking to profit from such consternations.
In the first place, it’s not clear that there is even a problem here. Following the post-pandemic surge in violent crime, lobbying groups like the National Retail Federation (NRF) leveraged the resulting anxiety, asserting that in 2021, there was supposedly $94.5 billion worth of inventory pilfered by organized crime rings preying on vulnerable retailers.
In reality, while retail crime did see an increase within some major American cities, overall there was no evidence for a national surge in shoplifting during this moral panic—especially not “organized retail theft.” The NRF later retracted its $94.5 billion claim and removed evidence that a 2020 study by the organization had found theft only cost retailers $720,000 for every $1 billion in sales.
Shoplifting rates do appear to be higher compared to pre-pandemic levels in places like New York, L.A., and Chicago. But that may have more to do with outside factors, like the cost-of-living crisis, and more importantly, there is reason to doubt AI surveillance will help at all.
SINCE THE SELF-CHECKOUT LANE became ubiquitous during the COVID-19 pandemic, workers in understaffed stores are now being deputized to maintain order. That’s where AI-powered technologies like Everseen come in. Everseen—which purports to use AI to flag insidious shoplifting behavior at self-checkouts and registers—has been deployed at retailers like Walmart for some time now. Anyone familiar with AI would not be surprised that Walmart employees have found this technology obnoxious and unreliable.
“You can imagine that adding a system that detects or stops shopper behavior that it deems to be ‘suspicious’ might still require some action from the frontline worker, whether that’s figuring out whether the behavior is actually suspicious, or dealing with a frustrated customer who’s been flagged for something,” Pegah Moradi, a Ph.D. candidate in information science at Cornell University, explained.
“If these flags are collected and easily provided to management, you can imagine that a worker might be under greater scrutiny during possible theft situations,” Moradi, who studies automation in the workplace, continued. “‘Why didn’t you do this?’, ‘Why did you do that?’ The power of the worker’s discretion is eroded when management trusts the AI signals more than the workers.”
Such an unreliable and potentially haphazard rollout of AI in the retail sector hasn’t stopped firms from buckling down. The U.S. Chamber of Commerce released a report praising the “Automated Worker Surveillance and Management” as a tool that could be instrumental in “Preventing Workplace Violence and Enhancing Safety and Security.” Meanwhile, Everseen filed a legal complaint in 2021 against Walmart, claiming that the superstore had stolen the firm’s trade secrets to develop “a Walmart copy of Everseen’s [Checkout Process Intelligence] technology.”
The AI surveillance hype contrasts with little attention paid to proven anti-shoplifting tools. As Amanda Mull writes at The Atlantic, understaffing, self-checkout machines, and poor logistics are all common in retailers, and all are associated with more theft. Progress could be made without the latest Big Tech gadget.
Meanwhile, stores like Walmart seem a lot more excited about using surveillance tools on their own employees than on criminals. A 2024 study of Walmart’s warehouse workers found that 45 percent felt “they always/most of the time have a sense of being monitored or watched on the job,” and that 58 percent of those polled “said the level of monitoring at Walmart is higher than at their previous job.”
Though such surveillance is ostensibly to protect the security of both workers and customers, it grants employers access to huge swaths of data that they can use for a variety of purposes. If stores monitor the traffic of customers as they move through the aisles, they can also track employees. It’s what information scientists Solon Barocas and Karen Levy have called “refractive surveillance,” wherein data collected from one group can be used to control another.
“This technology has been adopted and applied at such a rapid pace that the law has not caught up.”
“With [loss prevention] technology, they’re able to look at things like social media and past instances of theft or crime … and then create a different risk score of high, medium, and low for these different stores, and then allocate their loss prevention resources accordingly,” Madison Van Oort, an independent scholar, told the Prospect. Her research culminated in Worn Out, a book on retail surveillance and its consequences for workers.
“And so you can probably start to surmise, this is really similar to like predictive policing, right? It takes these stores that already have probably high theft or even instances of organizing, and then would continually allocate more research, more resources to those stores.”
Should workers at a retailer attempt to use social media to organize online or elevate their campaigns, Van Oort explained, these stores could be flagged to create higher risk scores for certain locations, and hence create yet another obstacle for union organizers. Without the ability to interact with each other without fear of surveillance, workers are unable to communicate with each other safely.
That’s how one Walmart employee, TaNeka Hightower, described her experience as a veteran Walmart employee and as someone who was a guinea pig for Walmart’s plan to have workers wear body cameras. Hightower has done everything from delivering groceries to working at her Nashville location’s vision center. And the way she tells it, the amount of monitoring at the store is “very detrimental to organizing co-workers.”
“We’re always under surveillance,” Hightower told me. “People have been fired for eating, drinking, or taking too long a break. We couldn’t talk to each other because even the pickup area where deliveries are received, the freezer, and the refrigerator are all [watched by cameras].”
According to Hightower, who has been with Walmart for seven years, this level of surveillance mixes with a punitive culture wherein threats about receiving disciplinary actions can be used to deny workers bonuses or cost them their jobs. “My file says I’m a troublemaker because they want people who are sheep, and I’m a goat,” Hightower said.
IF THIS ALL SOUNDS DISTURBINGLY LIKE how police behave, that might not be a coincidence. From the use of facial recognition software to the use of employee body cameras—which, in TaNeka’s case, appear to have been produced by Axon, the company that manufactures similar cameras for police and invented the taser—law enforcement tech is steadily encroaching into the retail sector.
At NRF Protect, the country’s premier loss prevention conference and trade show, retailers are encouraged to build lasting relationships with law enforcement by taking their local police chief out to lunch; customers and employees alike are painted as potential “bad guys” who need to be brought to justice; and technologies advertised at the conference are branded as being tested in police and military settings.
Some are fighting back against this AI surveillance push. Unions like the Retail, Wholesale and Department Store Union (RWDSU) have been incorporating clauses in new contracts that force employers to confer with workers before introducing new technologies to the shop floor, but this has yet to become the standard in an industry with such a low union rate.
At the state level, senators in Massachusetts, led by Sen. Dylan A. Fernandes, recently put forward a bill that would create new protections for workers by placing strict limits on monitoring, regulating automated decision systems, and allowing employees to refuse AI instructions.
“This technology has been adopted and applied at such a rapid pace that the law has not caught up,” Fernandes said. “We’re seeing a surge in technologies that can track keystrokes, monitor facial expressions, or automate discipline, often without transparency, oversight, or fairness.
“This bill is about drawing a clear line: Innovation cannot come at the expense of worker safety, or civil rights,” he added. “We don’t need to wait for a crisis or audit of abuses, this is about setting guardrails now to protect working people before harm becomes widespread.”
Alas, the federal government is ensconced with AI hype men, and as the Prospect has reported, Republicans’ One Big Beautiful Bill Act has a sneaky provision that would ban any state or local regulation of AI for ten years. Should it pass, retail employees and driverless car passengers alike better watch out.
| 2025-06-06T00:00:00 |
2025/06/06
|
https://prospect.org/labor/2025-06-06-ai-surveillance-wont-stop-theft-might-stop-unions/
|
[
{
"date": "2025/06/06",
"position": 9,
"query": "artificial intelligence labor union"
}
] |
Future of work
|
Equal Times
|
https://www.equaltimes.org
|
[
"Allison Corkery",
"Luc Triangle",
"Keith Jacobs",
"Jason Resnikoff",
"Atahualpa Blanchet"
] |
Trade union strategies on artificial intelligence and collective bargaining on algorithms. Atahualpa Blanchet: Through communication initiatives and the ...
|
Translators work in a changing and competitive field, where the use of new technologies – currently AI – is once again leading to the dehumanisation of their work and the deterioration of their working conditions, a trajectory that looks set to be the future for many other specialised professions.
| 2025-06-06T00:00:00 |
2025/06/06
|
https://www.equaltimes.org/future-of-work
|
[
{
"date": "2025/06/06",
"position": 59,
"query": "artificial intelligence labor union"
}
] |
Global trade union warns of a "concerted assault" on ...
|
Global trade union warns of a “concerted assault” on workers’ rights
|
https://www.democracywithoutborders.org
|
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These, the organization argues, are essential to restoring labor ... artificial intelligence before AI and corporate power undermine democracy and human rights.
|
Workers’ rights are in decline around the world, according to the 2025 Global Rights Index published by the International Trade Union Confederation (ITUC). The index, which reviews 151 countries, records the most widespread violations of labor rights since the index began in 2014. It warns that in numerous countries workers’ rights and democracy are under attack in tandem with the erosion of union freedoms.
According to the report, 87% of countries violated the right to strike and 80% violated the right to collective bargaining, with the latter figure going up one percent compared to the previous year. Access to justice for workers was restricted in 72% of countries, a sharp increase from last year’s 65%.
Only seven countries received the top score in the index’s rating system, down from 18 a decade ago. Meanwhile, ten countries were ranked among the worst places for working people: Bangladesh, Belarus, Egypt, Ecuador, Eswatini, Myanmar, Nigeria, the Philippines, Tunisia, and Turkey. In these nations, unionists face violence, criminal charges, or state-led persecution for carrying out legitimate activities.
We see the same playbook in action around the world
Referring to a “coup on democracy”, the world’s largest platform of national trade unions says that there is “a concerted, sustained assault by state authorities and the corporate underminers of democracy on the rights and welfare of workers. Increasingly, this attack is orchestrated by far-right demagogues backed by billionaires who are determined to reshape the world in their own interests at the expense of ordinary working people.”
ITUC General Secretary Luc Triangle according to The Guardian emphasized the political context of the findings. “This report is a wake-up call that democracy is under attack,” he said. “We see the same playbook of unfairness and authoritarianism in action around the world.”
He also underscored the growing concentration of wealth and its impact on workers: “The five richest people in the world more than doubled their wealth over the last five years, while 60% of the global workforce saw their real-term wages fall.” The ITUC connects this inequality to deliberate political decisions that have stripped away worker protections and empowered corporate interests.
Violations not limited to authoritarian states
The report finds that violations are no longer limited to authoritarian states. According to the ITUC, democratic governments are increasingly undermining labor protections through legal reforms, administrative restrictions, or budgetary cuts targeting unions. This trend is part of what the organization calls “a dangerous concentration of power,” where economic elites and political leaders jointly weaken labor standards.
Despite the overall decline, the report notes improvements in Australia, Mexico, and Oman, suggesting that progress is possible when governments adopt policies that strengthen worker protections. The ITUC calls for political action to support fair wages, secure employment, and universal social protections. These, the organization argues, are essential to restoring labor rights and reinforcing democratic institutions.
Speaking at a recent dialogue hosted by Democracy Without Borders, John Vlasto – an associate of the organization and Chair of the Board of the World Federalist Movement – highlighted a core imbalance at the heart of global economic injustice. While the economy has become globalized, he noted, politics has not kept pace. The absence of effective global mechanisms to regulate markets and enforce fairness, he argued, leaves economic power unchecked on a worldwide scale.
| 2025-06-06T00:00:00 |
2025/06/06
|
https://www.democracywithoutborders.org/36927/global-trade-union-warns-of-a-concerted-assault-on-workers-rights/
|
[
{
"date": "2025/06/06",
"position": 70,
"query": "artificial intelligence labor union"
}
] |
AI & Future of work - 6 June 2025 - by Johannes Sundlo
|
AI & Future of work - 6 June 2025
|
https://www.fullstackhr.io
|
[
"Johannes Sundlo"
] |
OpenAI turns ChatGPT Business into a first-class workplace app. Launched June 5, the new connectors let admins plug ChatGPT straight into HRIS, ATS, drive ...
|
Welcome to FullStack HR, and an extra welcome to the 102 people who have signed up since last edition.
If you haven’t yet subscribed, join the 9400+ smart, curious and like-minded future of work people by subscribing here:
OpenAI turns ChatGPT Business into a first-class workplace app
Launched June 5, the new connectors let admins plug ChatGPT straight into HRIS, ATS, drive repos and email while “Record Mode” auto-captures, transcribes and summarises meetings or voice notes for later audit. Flexible seat credits aim to remove licence caps for heavy users.
Why it matters for HR: Seamless data pipes mean recruiters can query requisitions, pay data or candidate files by chat, and employee-service teams get instant knowledge-base answers. Record Mode also builds an evidence trail that privacy and works-council colleagues will appreciate, so People Ops can champion adoption while still passing compliance checks.
Read more →
Workday launches Agent Partner Network and Agent Gateway
Announced at DevCon, the programme lets Accenture, AWS, Microsoft and others certify agents that plug into Workday’s Agent System of Record, while Gateway gives customers a single console to orchestrate them.
Why it matters for HR: Instead of waiting for Workday to ship every micro-feature, HRIT can now mix-and-match best-of-breed skills inference, pay-equity coaching and scheduling bots, without exporting data out of Workday’s security model. That keeps innovation cycles fast and the auditors calm.
Read more →
TIME Magazine: What Happens When AI Replaces Workers?
The essay argues that AGI could displace up to half of white-collar entry roles within five years and warns that universal basic income alone will not give citizens influence in an AI-driven economy. The author proposes “democratised AI ownership” so individuals can train private models and retain bargaining power.
Why it matters for HR: The piece reframes employee relations: fairness will increasingly hinge on who controls the models behind the work. HR will need policies on employee-owned agents, clarity on IP created with personal models and pathways for talent to upskill into AI governance and oversight roles rather than just operating the systems.
Read more →
EU Commission signals enforcement pause – but clarifies “high-risk” HR uses
Guidance published June 4 hints the Commission may delay full AI Act application while confirming that hiring, promotion and performance scoring tools remain “high-risk” and subject to strict obligations.
Why it matters for HR: This buys a little implementation time, yet the risk classification is locked in. CHROs should inventory every algorithm touching people decisions, gather vendor assurance docs and budget for conformity assessments before the grace period closes.
Read more →
Gemini can now summarise any video stored in Google Drive
Rolling out since May 30, Workspace and One AI Premium users can ask Gemini to pull highlights, action items and Q&A from long town-hall or training recordings.
Why it matters for HR: L&D teams can auto-generate recap mails and captions, improving accessibility, while managers finally get digestible takeaways from those two-hour all-hands.
Read more →
Josh Bersin declares “the L&D revolution is here”
In a June 1 brief, Bersin highlights Docebo’s shift to an AI-native architecture and Sana’s auto-generated learning paths, predicting that content authoring and skills mapping will soon be mostly machine-led.
Why it matters for HR: Budget will tilt from off-the-shelf courses to dynamic content engines. Upskill your L&D team in prompt design, data tagging and learning analytics to stay ahead.
Read more →
Ethan Mollick: How to Build an AI-First Organisation
In a 60-minute YouTube talk (!) Mollick argues that the worst mistake companies make with AI is thinking too small. Instead of chasing head-count cuts he urges leaders to redesign work so every employee gets a personal “AI sidekick” and so teams continuously pilot new agent workflows. He also stresses that culture beats code; without psychological safety staff will not experiment or report model failures.
Why it matters for HR: Mollick speaks to the real transformation task for HR: job architecture, capability building and change management. If AI sidekicks become the norm then role descriptions, performance criteria and learning paths must all shift toward “machine-team” collaboration skills. HR can champion safe-to-try cultures and create rotation programs that let employees practise with agents before business-critical launch.
Listen →
Business Insider: CEOs Privately Admit AI Will Shrink Teams
On 31 May two software investors told the “Twenty Minute VC” podcast that many CEOs expect 30-40 percent role reductions from AI but avoid saying so publicly to prevent backlash. They predict the layoffs will emerge within two years as efficiency targets crystallise.
Why it matters for HR: Transparency is becoming a strategic asset. If employees sense hidden agendas trust erodes and change efforts stall. HR can lead by publishing clear AI workforce impact assessments, co-designing re-skilling commitments with employee reps and establishing “AI transition councils” to keep dialogue open as automation ramps up.
Read more →
| 2025-06-06T00:00:00 |
https://www.fullstackhr.io/p/ai-and-future-of-work-6-june-2025
|
[
{
"date": "2025/06/06",
"position": 33,
"query": "future of work AI"
}
] |
|
The Paradox of AI and the Human Future of Work
|
The Paradox of AI and the Human Future of Work
|
https://blog.workday.com
|
[] |
The more we use AI to automate work, the more we crave what only humans can give—empathy, connection, and meaning. Ahead of the World Economic Forum in Davos ...
|
Why AI Makes Us Crave Connection
There’s a myth we need to bust: that more AI at work means less need for human interaction.
It’s the opposite.
When AI takes over the repetitive stuff—the scheduling, the report pulling, the data crunching—it doesn’t just free up time. It creates a void. A space that used to be filled with hustle gets replaced with… what, exactly?
That space is craving something real. Something human.
Think about it: as meetings get shorter, chatbots get smarter, and processes get automated, the little moments that made work feel like a shared experience start to disappear. The hallway conversations. The inside jokes. The “you okay?” from a teammate who actually means it.
AI is amazing at doing tasks. But it’s terrible at making people feel connected. And when those moments fade, people notice. Not always consciously. But in the “I don’t feel like I belong here anymore” kind of way.
And here’s the paradox: the more efficient we make work, the more meaning we have to consciously design back in.
So if you’re a leader thinking, “Great, AI just saved my team 10 hours a week,” the follow-up question has to be:
“What am I doing to reinvest that time into human connection?”
Because otherwise, all we’re doing is automating our way into isolation. Improving workplace communication is one place to start. But communicating better isn’t enough because people crave connection.
The Business Case for Connection
Let’s get real: human connection isn’t some squishy, feel-good perk. It’s a performance multiplier.
Teams that trust each other, that feel seen by their leaders, that know their work matters? They move faster. They solve problems more creatively. They stick around longer. And they burn out way less.
Don’t take my word for it. The research backs it up. In study after study, high-trust organizations outperform their peers—in productivity, profitability, innovation, you name it.
And yet, we’re still not budgeting for connection. We’re still not measuring it. We’re still treating it like “culture stuff” when it should be in every board-level strategy conversation.
Now here’s where AI comes back in.
When AI saves your team time, you have a choice. You can:
Funnel that time into more tasks.
Or reinvest it in the stuff that actually makes people want to show up.
AI is the ultimate efficiency engine. But connection is the ultimate loyalty engine.
If we get too focused on speeding up and forget to connect, we’ll win short-term and lose long-term. You can’t optimize your way to trust.
So the real business case for connection? It’s the only thing AI can’t do for you. And that makes it your biggest competitive advantage.
| 2025-06-06T00:00:00 |
2025/06/06
|
https://blog.workday.com/en-us/the-paradox-of-ai-and-the-human-future-of-work.html?sf226906254=1
|
[
{
"date": "2025/06/06",
"position": 83,
"query": "future of work AI"
}
] |
PwC Report Debunks AI Job Myths: Automation is Driving ...
|
PwC Report Debunks AI Job Myths: Automation is Driving Growth, Not Elimination
|
https://opendatascience.com
|
[
"Odsc Team"
] |
Rather than reducing wages, AI is linked to increased earnings. Workers with AI skills earn on average 56% more than peers in the same roles without those ...
|
Despite fears that AI will displace workers and suppress wages, new research from PwC reveals a different reality: AI is enhancing...
Despite fears that AI will displace workers and suppress wages, new research from PwC reveals a different reality: AI is enhancing worker value, not diminishing it. The 2025 AI Jobs Barometer, based on an analysis of over 800 million job ads and thousands of company financials across six continents, challenges six common misconceptions about AI’s impact on the workforce.
1. AI is Boosting Productivity
Contrary to the belief that AI has yet to impact productivity, the report finds that industries well-positioned for AI adoption have seen productivity growth nearly quadruple since 2022. Sectors like software publishing, highly exposed to AI, recorded three times higher revenue per employee than those with minimal exposure, such as physical therapy.
2. Wages Are Rising in AI-Exposed Fields
Rather than reducing wages, AI is linked to increased earnings. Workers with AI skills earn on average 56% more than peers in the same roles without those skills—a jump from 25% the year prior. Wage growth is also twice as fast in industries heavily influenced by AI technologies.
3. AI-Exposed Jobs Still Growing
While concerns persist that AI will shrink job opportunities, the study shows robust employment growth across sectors. Between 2019 and 2024, jobs in lower AI-exposed roles grew by 65%, while more AI-exposed roles still saw 38% growth.
4. AI Is Not Driving Inequality
The data do not support the assumption that AI exacerbates workforce inequality. AI is creating broader access to high-paying roles by reducing employer dependence on formal degrees. Jobs augmented by AI are seeing increases in both employment and wages.
5. AI Enriches Rather Than Deskills Roles
Rather than eliminating skill requirements, AI is freeing workers from repetitive tasks and allowing them to focus on higher-order decision-making. For example, roles like data entry are evolving into data analyst positions, enabling career growth.
6. Automation Can Increase Job Value
The report also refutes the idea that automation devalues jobs. Even in roles deemed highly automatable, wages are climbing, and responsibilities are becoming more complex and creative.
With aging populations and declining labor forces in many countries, the report argues that AI-driven productivity could help address workforce gaps.
PwC’s Joe Atkinson notes, “It could absolutely and will be a good thing.” The report urges organizations to approach AI as a growth lever, not merely a cost-cutting tool. “Instead of limiting our focus to automating yesterday’s jobs, let’s create the new jobs and industries of the future,” it concludes.
Get Hands-On With AI at Ai+ Training by ODSC
With that said, it’s still valuable for professionals to deepen their expertise in AI. Ai+ offers a robust catalog of on-demand and live training led by top practitioners in data science, machine learning, and AI.
Whether you’re an analyst, engineer, or decision-maker, Ai+ provides practical, project-based learning tailored to real-world applications—empowering you to stay ahead in a rapidly evolving tech landscape.
Learn more at aiplus.training.
| 2025-06-06T00:00:00 |
2025/06/06
|
https://opendatascience.com/pwc-report-debunks-ai-job-myths-automation-is-driving-growth-not-elimination/
|
[
{
"date": "2025/06/06",
"position": 19,
"query": "job automation statistics"
}
] |
Amid job loss fears due to automation, a shocking new ...
|
Amid job loss fears due to automation, a shocking new report reveals how AI is actually making workers ‘more valuable’
|
https://m.economictimes.com
|
[] |
Productivity in AI-exposed industries has nearly quadrupled since 2022, and wages for workers with AI skills are significantly higher. The study highlights AI's ...
|
The Speed of AI Innovation: A Double-Edged Sword?
Jobs and Wages Climb in AI-Exposed Occupations
— KirkDBorne (@KirkDBorne)
Busting the Biggest AI Myths
AI as a Job Enricher, Not a Job Killer
Could Gentler Job Growth Be a Hidden Blessing?
AI: From Efficiency Tool to Growth Strategy
As anxiety mounts over artificial intelligence (AI) threatening jobs and wages, a groundbreaking new study by professional services giant PwC turns the narrative on its head. Contrary to fears that AI will lead to widespread layoffs and wage suppression, the research shows that AI is making workers more valuable — boosting both employment and pay across industries.Joe Atkinson, PwC’s Global Chief AI Officer, emphasizes the unprecedented pace of AI advancements. Speaking to CNBC Make It, Atkinson noted, “The tech innovation is moving really, really fast — faster than anything we’ve ever seen.” Yet, instead of causing disruption through job losses, AI is creating new roles and opportunities. “What the report suggests, actually, is AI is creating jobs,” he said.The 2025 AI Jobs Barometer report, analyzing over 800 million job ads worldwide, reveals a surprising trend: jobs and wages are growing in nearly every role where AI can be applied. This includes occupations considered highly automatable, such as customer service and software development.Carol Stubbings, PwC UK’s Global Chief Commercial Officer, highlights a crucial challenge — not the loss of jobs but the evolving skillsets required. “Workers need to be prepared to take the new jobs that AI is creating,” she said. The report warns against complacency, urging workforce adaptation as the key to thriving alongside AI.PwC’s extensive research debunks six common misconceptions about AI’s impact on the labor market. Far from stagnating productivity, industries most exposed to AI have seen productivity growth nearly quadruple since 2022. Contrary to fears of wage suppression, workers with AI skills earn on average 56% more than their peers without those skills—a significant rise from 25% last year.Even the myth that AI reduces overall job numbers doesn’t hold up. Occupations less exposed to AI grew by 65% from 2019 to 2024, while AI-exposed jobs still posted a robust 38% growth. Furthermore, the report finds AI does not worsen inequality; wages and job opportunities are rising in AI-augmented and automatable roles, with employer demand for formal degrees decreasing in these sectors—potentially widening access.Another surprise: AI is enriching jobs traditionally seen as vulnerable to automation. By automating mundane tasks, AI frees workers to develop more complex, creative skills. Data entry clerks, for example, are evolving into data analysts, increasing their value in the workplace.The report also shows that even jobs highly susceptible to automation are becoming more complex and creative, ultimately enhancing human worth rather than devaluing it.With many countries facing declining working-age populations, the study suggests that moderated job growth in AI-affected fields might be beneficial. AI-driven productivity gains create a multiplier effect, filling workforce gaps and enabling companies to grow more efficiently.Atkinson concludes, “It’s a prediction supported by the productivity data we’re seeing… It could absolutely and will be a good thing.”The report urges companies to rethink AI as more than a cost-cutting tool. Instead, AI should be embraced as a powerful growth engine. Businesses are encouraged to help employees adapt, innovate, and collaborate to create new markets and revenue streams.“It is critical to avoid the trap of low ambition. Instead of limiting our focus to automating yesterday’s jobs, let’s create the new jobs and industries of the future,” the report advocates.Historically, technology has been a wellspring of new jobs — with two-thirds of today’s U.S. jobs nonexistent in 1940. PwC’s research suggests AI could ignite a similar wave of innovation, reshaping the workforce for decades to come.
| 2025-06-06T00:00:00 |
https://m.economictimes.com/magazines/panache/amid-job-loss-fears-due-to-automation-a-shocking-new-report-reveals-how-ai-is-actually-making-workers-more-valuable/articleshow/121679013.cms
|
[
{
"date": "2025/06/06",
"position": 34,
"query": "job automation statistics"
}
] |
|
Embracing the AI transition mindset for successful adoption
|
Embracing the AI transition mindset for successful adoption
|
https://www.cgi.com
|
[] |
By embracing an AI transition mindset, organizations can help their workforce confidently navigate change, turning AI adoption into a strategic advantage.
|
AI has become a fundamental driver of business transformation, reshaping industries and redefining how organizations innovate, compete and grow. As these technologies evolve, businesses face a pivotal moment—one that requires not just technical adaptation, but a shift in how AI is perceived and integrated into workplace culture. This shift can be challenging, but rather than focusing on uncertainty, organizations should embrace an AI transition mindset—a forward-thinking approach that enables employees, executives and customers to navigate AI-driven change with confidence and clarity.
The increasing reliance on AI brings both opportunities and uncertainties. Employees may wonder how AI will impact their roles, while executives grapple with ensuring AI’s ethical use aligns with company values. Customers and investors, too, seek reassurance that AI-driven decisions are transparent, unbiased and aligned with human oversight. In this landscape, trust becomes a competitive differentiator.
Across industries, organizations are rapidly accelerating their AI initiatives, spurred by advances in generative and traditional AI technologies. However, the speed of adoption brings risks. If AI implementation lacks transparency, clear communication or proper change management, organizations will face technical challenges and reputational and operational setbacks.
Organizations that develop an AI transition mindset—by combining governance, ethical leadership and proactive change management—will successfully harness AI’s full potential. This isn’t just about managing risks; it’s about building trust, fostering workforce adaptability and ensuring AI-driven growth is sustainable and embraced.
Let’s explore how organizations can adopt AI in a way that strengthens both business performance and human trust.
The role of change leadership in AI adoption: building trust and ensuring success
As organizations integrate AI into their operations, the focus often falls on technology and process optimization. However, successful AI adoption is not just about implementing new tools—it’s about preparing people to embrace change. Change leadership is crucial in fostering confidence, encouraging workforce adaptation and ensuring that AI initiatives reach their full potential.
When introduced thoughtfully, with clear communication and support, AI becomes an empowering tool rather than a source of uncertainty. Organizations that invest in structured change leadership create a workplace culture that is adaptable, innovative and future-ready.
Why change leadership matters in AI integration
Many organizations have experienced the challenge of rolling out new technologies, only to see adoption stall due to a lack of engagement or understanding. AI is no different—except the stakes are even higher. When organizations neglect the human aspect of AI adoption, they risk internal resistance, confusion and missed opportunities.
AI-driven change should be seen as a journey, not a one-time implementation. Just as organizations allocate resources to developing AI models and refining data governance, they must also dedicate time and effort to preparing employees for AI’s evolving role. When change leadership is integrated from the start, organizations can boost confidence, increase adoption rates and maximize the value of their AI investments.
Common pitfalls in AI rollouts—and how to avoid them
Organizations that struggle with AI adoption often make the same missteps. By proactively addressing these challenges, organizations can create a more seamless and positive AI transition:
Lack of transparent communication: Employees and customers should clearly understand how AI is being used, why it’s being adopted and its potential impact. When organizations fail to communicate AI’s role effectively, it can lead to skepticism and resistance.
Employees and customers should clearly understand how AI is being used, why it’s being adopted and its potential impact. When organizations fail to communicate AI’s role effectively, it can lead to skepticism and resistance. Underestimating the human factor: AI initiatives succeed when employees feel informed, empowered and prepared for change. Organizations that overlook training and support miss the opportunity to align AI adoption with workforce growth.
AI initiatives succeed when employees feel informed, empowered and prepared for change. Organizations that overlook training and support miss the opportunity to align AI adoption with workforce growth. Introducing change leadership too late: Many organizations wait until the final stages of AI implementation to introduce change management strategies. Instead, change leadership should be integrated from the beginning, ensuring that employees and stakeholders are engaged throughout the process.
Many organizations wait until the final stages of AI implementation to introduce change management strategies. Instead, change leadership should be integrated from the beginning, ensuring that employees and stakeholders are engaged throughout the process. Insufficient training and upskilling: AI adoption should be accompanied by structured learning opportunities. Employees need time to experiment, ask questions and build confidence in AI tools. A phased rollout with ongoing support ensures a smoother transition.
AI adoption should be accompanied by structured learning opportunities. Employees need time to experiment, ask questions and build confidence in AI tools. A phased rollout with ongoing support ensures a smoother transition. Misjudging organizational readiness: Organizations must assess not just the technical aspects of AI integration but also their capacity to adapt. A well-planned AI transition accounts for different learning curves and provides tailored support where needed.
A people-first approach to AI success
Employees value clarity, guidance and a sense of purpose when navigating technological shifts. Organizations can cultivate a culture of continuous learning and innovation by taking a proactive approach to AI transition.
A strong change leadership strategy does more than mitigate challenges—it turns AI adoption into a strategic advantage. With clear communication, employee support and external transparency, businesses can create an environment where AI enhances productivity, strengthens trust and drives long-term success.
With the right approach, AI isn’t just a disruptive force—it’s an opportunity to empower teams and build a more resilient organization for the future.
Strategies to foster an AI transition mindset
Successfully navigating AI adoption requires a thoughtful, structured approach that empowers employees to embrace AI with confidence. By prioritizing communication, training and leadership engagement, organizations can maximize the value of AI investments while fostering a culture of adaptability and innovation. The following strategies will help ensure that employees have the support, skills and engagement they need to thrive in an AI-enhanced work environment.
Strategic foundation
Evaluate investment priorities - Take a hard look at your investments. How much is being invested in AI tools and processes compared to resources allocated to helping people adapt to these changes? Are you investing enough in training, communication and ongoing support? The more significant the change, the more essential these investments become.
Take a hard look at your investments. How much is being invested in AI tools and processes compared to resources allocated to helping people adapt to these changes? Are you investing enough in training, communication and ongoing support? The more significant the change, the more essential these investments become. Focus on the “why” - Employees need clarity on the purpose of AI adoption. Clear and transparent messaging from senior leadership about the business case for AI fosters trust and engagement. Employees also want direct supervisors to articulate how AI will enhance their daily tasks, improve efficiency and create opportunities for professional growth. A well-communicated explanation of why ensures alignment and reduces uncertainty.
Employees need clarity on the purpose of AI adoption. Clear and transparent messaging from senior leadership about the business case for AI fosters trust and engagement. Employees also want direct supervisors to articulate how AI will enhance their daily tasks, improve efficiency and create opportunities for professional growth. A well-communicated explanation of why ensures alignment and reduces uncertainty. Engage senior leadership - When senior leadership actively supports AI initiatives, employees are more likely to follow suit. Senior leadership should go beyond behind-the-scenes decision-making by openly advocating for AI adoption, addressing employee concerns, and reinforcing AI’s role in driving organizational growth. Leadership visibility fosters a sense of direction and purpose, making AI integration a shared journey rather than an imposed change.
Engagement and action
Communicate early and often- AI adoption should not come as a surprise. Communication must be frequent, transparent, and multi-channel to ensure employees stay informed and engaged. A single announcement or presentation is not enough; organizations should employ proactive (push) and responsive (pull) communication strategies to keep messaging clear and accessible. Early communication also prevents rumors and speculation, allowing employees to voice their questions and concerns in a constructive environment. Sharing progress updates, acknowledging uncertainties and providing a forum for dialogue helps build trust and encourages a more positive AI transition.
Encourage and promote training - AI tools require hands-on experience to build confidence. Organizations that foster a learning environment where trial and error are embraced will gain a competitive edge in AI adoption. Provide low-stakes opportunities for employees to experiment with AI, dedicate time and resources to training that goes beyond a basic introduction and ensure that employees are given dedicated time to learn.
Phased implementation - AI adoption is most effective when introduced gradually. A phased rollout allows employees time to adapt, build skills and integrate AI into their workflows in a way that enhances, not disrupts, productivity. This measured approach helps organizations focus on quality and efficiency rather than speed, ensuring employees have the necessary resources to succeed in an AI-powered environment.
Sustained success
Think beyond “go live” - Launching a new AI tool is only the beginning. Organizations need AI champions and change leaders who will continue to drive engagement long after initial implementation. AI should become integral to daily workflows, not a short-lived experiment.
Launching a new AI tool is only the beginning. Organizations need AI champions and change leaders who will continue to drive engagement long after initial implementation. AI should become integral to daily workflows, not a short-lived experiment. Plan and invest in change leadership - Change should never be left to chance. Invest in a structured, consistent approach to change leadership that equips employees with the knowledge and support they need to adopt AI successfully. What percentage of your projected AI benefits are tied to employees adopting and using AI tools? Organizations that proactively invest in training, leadership support and ongoing education will see higher adoption rates and long-term value from their AI investments.
AI is reshaping industries, allowing organizations to drive innovation and efficiency. Success, however, depends on more than technology—it requires a people-first approach that fosters trust, transparency and workforce adaptability.
By embracing an AI transition mindset, organizations can help their workforce confidently navigate change, turning AI adoption into a strategic advantage. Beyond compliance, leadership engagement and clear communication will ensure AI is integrated responsibly, strengthening reputation and long-term success. Businesses that act now will lead the future of AI.
Learn more about CGI’s AI insights and offerings and connect with an AI expert today.
| 2025-06-06T00:00:00 |
https://www.cgi.com/us/en-us/blog/artificial-intelligence/ai-transition-mindset
|
[
{
"date": "2025/06/06",
"position": 14,
"query": "workplace AI adoption"
}
] |
|
Microsoft's Warning Shot: AI Isn't Augmenting Your ...
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Microsoft's Warning Shot: AI Isn't Augmenting Your Healthcare Workforce, It's Becoming It
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https://www.vktr.com
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[
"David Priede",
"About The Author"
] |
AI agents are seen as key to bridging the workforce capacity gap and boosting productivity. Traditional org charts may yield to dynamic "Work Charts" blending ...
|
Key Takeaways:
AI is shifting from personal tools to integrated AI agents acting as digital colleagues.
Future success requires leaders and employees to become "Agent Bosses," managing AI teams.
Top-down strategy, not just bottom-up use, now drives AI adoption in leading firms.
AI agents are seen as key to bridging the workforce capacity gap and boosting productivity.
Traditional org charts may yield to dynamic "Work Charts" blending human and AI talent around specific goals.
Remember last year? When the big "Aha!" was that your people were secretly using ChatGPT behind your back? Quaint, wasn't it? Like discovering your team was using calculators instead of abacuses.
Wake up. That was the prelude. The opening act.
Microsoft just dropped their latest Work Trend Index, and the message is a lightning bolt: The era of timid, bottom-up AI experimentation is over. We're hurtling into the age of the Frontier Firm, where AI isn't just a tool your employees use — it's a fundamental part of the workforce they manage.
Forget optimizing old processes. Forget just giving everyone a Copilot license and calling it a day. Your job, healthcare leaders, is about to change. Are you ready to become an Agent Boss? Because the AI agents are clocking in.
Beyond Augmentation: AI Graduates From Tool to Teammate
Let's cut through the noise. For years, we've talked about technology augmenting human capability. Fine. But what's happening now, confirmed by Microsoft's massive survey of global workers and leaders, is a phase shift. A state change. AI is morphing from a clever assistant into a digital colleague, an agent capable of taking on complex workflows and operating as part of the team.
Last year's story, according to Microsoft's data, was the "secret cyborg" — 75% of knowledge workers using GenAI, often covertly. This year? The narrative has flipped dramatically. It's now top-down. It's strategic. A staggering 81% of business decision-makers report needing to rethink core strategy and operations with AI. It's not about if anymore, but how fundamentally.
Why the urgency? Leaders feel the heat. 53% say productivity needs to jump, yet a crushing 80% of the workforce feels drained, lacking the time and energy for more. The old way of squeezing efficiency isn't working. Enter the AI agent — not just to help individuals be faster, but to expand workforce capacity. Microsoft found 82% of leaders now expect to use AI agents specifically to meet this demand. That’s not tinkering; that's a strategic workforce augmentation plan.
Related Article: How Companies Can Prepare for an AI-Augmented Workforce
The 3 Phases of the Frontier Firm in Healthcare
Microsoft outlines an evolution, and you need to ask yourself honestly where your healthcare organization stands:
Phase 1: Human With Assistant
This is where many are today. Clinicians, researchers, administrators using AI tools (like Copilots) for personal productivity — drafting emails, summarizing documents, maybe basic data queries. It's helpful, sure. But it's table stakes. It's like giving everyone faster horses when the automobile is rolling off the assembly line.
Fact Check: KPMG data cited shows daily AI productivity tool usage jumped from 22% to 58% between Q4 2023 and Q1 2024 — rapid adoption, but still largely assistant-focused.
Phase 2: Human-Agent Teams
This is the bleeding edge for most, but it's coming fast. Here, AI agents become digital colleagues. Imagine an AI agent embedded in a tumor board, analyzing patient data alongside human specialists. Picture an agent managing patient scheduling logistics across a department, interacting with other systems. Think of research agents constantly scanning the literature for relevant breakthroughs for specific projects.
Real-World Glimpse: While full "team members" are nascent, specialized AI in areas like drug discovery (accelerating compound screening) or clinical trial optimization already function like highly specialized, albeit non-sentient, contributors.
Phase 3: Human-Led, Agent-Operated
This is the "Frontier Firm." Humans set the strategy, the goals, the ethical boundaries. Swarms of AI agents then execute complex business processes and workflows, checking in as needed. Imagine a hospital administrator overseeing agents that manage resource allocation, predict patient surges and optimize staffing levels dynamically. Think of a pharma R&D leader directing agents that run complex simulations and manage experimental data pipelines. This isn't science fiction; Microsoft reports 46% of companies are already using agents to fully automate workflows.
Rise of the Agent Boss: Your New Job Description
This evolution demands a new kind of leader, a new kind of employee: the Agent Boss. Defined by Microsoft as "someone who builds, delegates to and manages agents to amplify their impact."
This isn't just about prompt engineering anymore. It's about:
Orchestration: Managing potentially hundreds or thousands of specialized agents. Knowing which agent to deploy for which task. Coordinating their actions.
Managing potentially hundreds or thousands of specialized agents. Knowing which agent to deploy for which task. Coordinating their actions. Delegation Trust: Entrusting agents with high-stakes work (Microsoft found trust in AI for such tasks is a key differentiator).
Entrusting agents with high-stakes work (Microsoft found trust in AI for such tasks is a key differentiator). Workflow Redesign: Not just automating old steps, but fundamentally reimagining how work gets done with agents integrated.
Not just automating old steps, but fundamentally reimagining how work gets done with agents integrated. Strategic Oversight: Guiding the agents, setting their objectives, ensuring alignment with human values and goals.
Essentially, everyone becomes more of a manager, more of a strategist, focused on outcomes rather than just tasks. The report highlights that leaders are already ahead of employees in adopting this "agent boss mindset," feeling the pressure to deliver results and seeing agents as the way forward.
Related Article: The Co-Leadership Challenge: What Healthcare Can Learn from the AI CEO Buzz
The End of the Org Chart as We Know It?
Perhaps one of the most revolutionary ideas reinforced by the WTI is the potential demise of the traditional org chart. Microsoft suggests a move towards a dynamic "Work Chart" — think movie production crews assembling temporarily around specific goals (a patient pathway, a research project, a new service launch), blending human talent with AI agents, then reforming for the next challenge.
This fluidity is essential for the kind of agility healthcare desperately needs. It breaks down silos. It focuses on outcomes. It allows expertise (human and AI) to flow where it's needed most.
Fact Check: The WTI notes that roles like AI Agent Specialists, AI Trainers and ROI Analysts are increasingly in demand, reflecting this shift towards managing and integrating AI, not just using basic tools. 78% of leaders overall (95% in Frontier Firms) are hiring for such roles.
The Healthcare Imperative
For healthcare, the implications are profound:
Addressing Burnout & Capacity: AI agents can take on administrative burdens, data analysis and routine tasks, freeing up clinicians for complex care and human interaction.
AI agents can take on administrative burdens, data analysis and routine tasks, freeing up clinicians for complex care and human interaction. Accelerating Innovation: Agent teams in research can drastically speed up discovery and trials.
Agent teams in research can drastically speed up discovery and trials. Hyper-Personalization: Agents can manage vast patient data streams to enable truly personalized prevention and treatment plans.
Agents can manage vast patient data streams to enable truly personalized prevention and treatment plans. Operational Efficiency: Agent-driven workflows can optimize patient flow, resource management and supply chains in ways previously impossible.
But this requires shedding old management orthodoxies. It demands investment not just in technology, but in new ways of working and new leadership skills. Prioritizing AI-specific skilling (cited by 47% as a top strategy) is signifivantl, but it must go beyond basic tool usage to encompass agent management and workflow redesign. Even the willingness to consider AI for headcount changes (33%) or using AI as digital labor alongside humans (45%) signals a fundamental rethinking of workforce composition.
Microsoft's report isn't just data; it's a map to a rapidly approaching future. A future where AI agents are colleagues, where managing them is a core competency and where organizations are redesigned around human-AI collaboration. Healthcare leaders (and all other enterprise leaders, for that matter) can no longer afford incrementalism. You need to ask: Are we consciously building the capabilities — the mindset, the skills, the structure — to become a Frontier Firm? Or are we clinging to the past, destined to become a case study of obsolescence? The agents are ready. Are you?
Learn how you can join our contributor community.
| 2025-06-06T00:00:00 |
https://www.vktr.com/digital-workplace/microsofts-warning-shot-ai-isnt-augmenting-your-healthcare-workforce-its-becoming-it/
|
[
{
"date": "2025/06/06",
"position": 62,
"query": "workplace AI adoption"
}
] |
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The complete guide to AI safety in the workplace
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The complete guide to AI safety in the workplace
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https://www.protex.ai
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[] |
Organizations need to implement AI systems responsibly, always considering the ethical and social impact of their adoption. This means that companies must ...
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AI in Workplace Safety - The Complete Guide
How can AI help protect your workforce? In this guide, we cover all aspects of workplace safety, and provide insights as to how Health and Safety managers can rely on AI and computer vision to ensure every worker can operate safely.
AI in Workplace Safety Management
AI isn’t lurking in the background anymore. It's actively reshaping how we keep people safe at work.
Health and Safety managers now rely on smart systems that don’t just react - they predict. AI for safety professionals use machine learning to spot patterns in incident reports. Computer vision detects unsafe behavior on factory floors before anyone gets hurt. Real-time analytics turn raw data into early warnings, not post-mortems.
But the tech isn’t doing this alone. It’s working in tandem with people who understand what’s really at stake - human lives, not just compliance checklists. From monitoring noise levels to flagging dangerous machinery usage, AI helps teams act faster and more precisely.
With a focus on prevention, AI-driven safety tools are revolutionizing how potential hazards are identified and mitigated through hazard tracking and hazard reporting processes. They ensure that safety is not just a policy but a cornerstone of the workplace culture.
What We’ll Cover
This guide serves as an essential resource for businesses looking to harness the power of cutting-edge technology to protect their most valuable asset - their employees.
Whether you're a seasoned EHS professional or new to the domain, our insights will equip you with the knowledge to integrate AI into your safety strategy effectively, paving the way for a safer, more innovative, and more resilient workplace.
Section 1 - Introduction to AI Safety
Workplace safety advanced in 2023 - the U.S. Bureau of Labor Statistics (PDF) logged 5,283 fatal work injuries, 3.7 % fewer than in 2022. Transportation incidents still caused 28% of those deaths.
These facts spotlight the promise of AI-powered workplace safety platforms. Computer-vision platforms such as Protex scrutinize live camera feeds, identify unsafe behaviors, and stop serious-injury-and-fatality (SIF) events at the source.
Common Workplace Hazards Across Industries
Depending upon the industry and the nature of work, there can be hundreds of hazards that pose varying levels of risk, including:
Harmful chemicals
Physical hazards like falling objects
Ergonomic hazards
Noxious gasses
Sharp objects
Near misses
As you can imagine, this is a partial list. To improve behavioural safety, many companies are now using artificial intelligence to their advantage.
AI Hazard Detection and Employee Safety Monitoring Tools
The popularity of AI safety is primarily fuelled by significant advances in deep learning algorithms, which are now capable of "learning" by simply processing large volumes of data.
Previously, companies had to hire safety officers to ensure workers on site took safety standards seriously. These safety officers would monitor the use of PPE (personal protective equipment) and alert employees to different dangers in the environment.
However, human error is a genuine possibility. Organizations need help to employ safety officers to carefully monitor hundreds of workers across a larger area, such as a construction site. That's where AI safety comes in. AI safety tools like PPE detection are capable of processing information much quicker.
Section 2 - AI Safety – A Technical Overview
Artificial intelligence, in its fundamental form, is any algorithm or machine that can mimic the workings of the human brain. It uses algorithms and processes to simulate human intelligence in a machine.
However, this can be considered an abstract definition. Practically, AI is regarded as the ability of a machine to perform a simple cognitive function: learning. AI machines can be fed large amounts of data, and by processing it, they learn to recognize patterns.
How AI Learns Through Deep Learning and Machine Learning Algorithms
AI safety tools use deep learning, a subset of machine learning, to analyze hundreds of thousands of images. They do this by breaking the images into millions of pixels and then analyzing subtle differences between each.
Over time, they can detect various objects. For instance, an AI-powered workplace safety software can be "trained" for hard hat detection on a construction site, ensuring worker safety by monitoring for hazardous conditions and alerting potential safety risks.
AI Safety Tools - Hard Hat Detection and Real-Time Video Analytics
Workplace safety AI solutions like these can be connected to a company's existing CCTV network, thus offering real-time monitoring. AI safety tools rely on computer vision and video content analysis to detect PPE usage in real-time.
They can then send alerts, including notifications or even text messages, to employees or the department about safety protocols. Real-time corrective actions follow instantly: each alert auto-generates an action, assigns an owner and launches the preset escalation workflow, keeping the task open until the risk score returns to zero.
While all of this happens within seconds, there's a complex web of technologies that make it happen.
Fairness and Bias in AI Systems for Safety Compliance
Fairness in A.I. systems refers to removing prejudice in the data used to train and build the system. Systems that lack fairness can have a harmful impact on marginalized communities, such as gender, race, and socio-economic status.
When building A.I. models, developers must ensure that their technology is inclusive and does not discriminate against specific demographics. This study supports these claims by examining AI's impact on occupational safety and health equity.
Bias, on the other hand, occurs when the technology is programmed to respond or behave differently towards individuals based on their background or physical characteristics. This bias leads to unfair treatment wherein A.I. systems evaluate and assess individuals differently. This study by EU-OSHA highlights the need for unbiased AI systems in the workplace.
Ensuring Ethical AI Development in Workplace Safety Applications
It is vital to ensure that A.I. systems are designed to protect individuals' privacy, avoid unintended consequences, and promote fairness. Fairness in A.I. systems support human dignity and ethics while eliminating discriminatory behavior.
Furthermore, if bias and fairness issues go unaddressed, it can cause negative impacts on individuals and organizations. This may also result in individuals needing more confidence in the technology.
To understand the full definition of safety in the workplace, our glossary can provide you with comprehensive insights.
Explainability and Interoperability in AI Safety Models
AI safety topics such as explainability are critical in the EHS context, helping teams understand how AI models make decisions and assess their reliability. With explainability, EHS teams can understand the decision-making process behind the AI models, assess their reliability, and identify potential biases.
In contrast, if the decision-making process of AI subsystems is opaque, there will be no way to determine how it arrived at its conclusion. For instance, if an AI model identifies a potential hazard, the EHS team needs to understand how the model arrived at that conclusion.
To aid that effort the vision engine maintains a continuous risk scoring layer - providing 24/7 detection, hidden-risk visibility and a real-time risk score that helps teams triage issues before they escalate.
Interoperability in AI and Safety in the Workplace
AI in safety management also depends on strong interoperability - ensuring that systems communicate and work together seamlessly through standardized Application Programming Interfaces (APIs).
From a workplace safety standpoint, the interoperability of AI models is critical when accessing data from different sources. Interoperability can create a more coherent picture of the organization, allowing EHS teams to access all the data needed to make the right decisions.
Core Technologies Behind AI and Safety in the Workplace
Let’s take a closer look at the essential technologies that support AI for safety in high-risk settings.
Computer Vision
Computer vision involves using artificial intelligence to enable systems and computers to extract critical information from digital imagery and videos, much like a human sees.
Machines that use computer vision can be trained to detect objects with the help of a camera. Once a data source is connected, systems can "learn" by inspecting different images.
They rely on complex technologies, including convolutional neural networks, which allow machines to analyze images. Every pixel is labeled and tagged before the system starts running convolutions to determine if its predictions are accurate.
In the beginning, accuracy is generally low, as the system is only capable of identifying simple shapes and prominent outlines. However, as it continues to evaluate new images, it begins to get more and more accurate until it's capable of recognizing objects with extreme precision.
For a more detailed exploration of how AI promotes a proactive safety culture, see our whitepaper.
Convolutional Neural Networks
A convolutional neural network is an algorithm used for deep learning. It takes an image, assigns specific biases to the objects within, and then learns to distinguish between different input images.
The name is derived from how neurons are connected within the brain, as the architecture of a convolutional neural network follows a similar architecture.
Convolutional neural networks capture temporal and spatial dependencies from an image by applying different filters, allowing them to identify things that might not be obvious to the human eye.
Over time, convolutional neural networks become much faster and more accurate than the human eye, as they can be deployed in larger areas and can focus on many objects at once.
Video Content Analysis
The footage captured by a conventional CCTV camera can be processed through safety video analytics. With the help of VCA, companies can implement specific safety rules, such as identifying if anyone crosses into restricted areas.
Objects in the footage can be detected and tracked through video content analysis, as it can identify spatial and temporal events in real time. VCA can also be used for face recognition and object discovery, classification, and segmentation.
Video content analysis allows companies to gather crucial analytical information about work processes, and it can help safety personnel identify patterns they hadn't previously focused on.
Section 3 - 7 Benefits of Using AI to Improve Workplace Safety
Many companies are already using AI safety tools to make workplaces safer and to reduce the burden on their safety personnel while also being compliant with regulations.
To understand how to convince senior management of the benefits of AI safety software, read our whitepaper.
Here are 7 of the many benefits that AI safety tools offer.
Automation and Predictive Analysis for Accident Prevention
Arguably, the most significant benefit of using AI tools in the workplace is automation. This doesn't just mean automating dangerous tasks that pose a more substantial threat of injury, but also repetitive tasks.
For instance, AI safety tools can monitor all workers and ensure they wear protective equipment, contributing to a safer work environment. AI safety tools can also prevent people from walking into an exclusion zone by observing behavior and sending alerts when someone approaches within a defined limit.
Reducing Human Error with AI-Driven Employee Safety Monitoring
AI safety technologies get more accurate and more innovative as more and more information is fed into the system. There's a risk that a human may miss a minor detail, but AI safety systems aren't prone to human error.
This means your workplace will only get safer as time passes and the system continues to process and analyze new data.
Improved Equipment Control and Safety Regulations Compliance
Safety personnel can define specific rules for taking appropriate steps before using dangerous machinery. Equipment control can ensure that only trained employees can use specialized machines.
More importantly, they can be configured to operate based on specific rules, such as if a qualified individual is present for supervision. This ultimately helps improve safety outcomes and prevents any mishaps.
Predictive Insights with Real-Time Monitoring
AI's role in workplace safety is transformative. It offers predictive insights and real-time monitoring to prevent accidents. AI-driven training tools can also adapt to users' learning styles, enhancing safety protocol compliance.
Real-Time Hazard Detection and Workplace Security Insights
Employers have a responsibility to ensure that they regularly train and educate employees about the importance of using proper safety equipment. However, if these standards aren't enforced, there's a risk that employees may not take it seriously.
This is where workplace safety technology for monitoring like wearable sensors come into play, integrating with existing systems to enhance compliance and safety.
Safety officers in fast-moving environments, such as a construction site, can only do so much. They cannot monitor every employee on the site without causing disruptions. This also increases the risk of human error, as a safety officer may miss critical details. With AI systems, this isn't an issue.
How AI Enhances Real-Time Employee Monitoring
AI safety systems connect with existing CCTV networks. They can process multiple data streams in real-time and send alerts whenever rules are breached. They can be used to monitor:
Employee location
Use of PPE
Presence of environmental hazards
Exclusion zones
Fatigue monitoring
Improved Decision-Making Through AI Safety Technology
Leading indicators tell you what might go wrong, whereas lagging indicators merely confirm what already did.
By streaming real-time safety data, AI safety technology delivers proactive safety metrics that spotlight emerging hazards hours or even days in advance.
Supervisors act on those insights, fine-tune rules and prevent accidents instead of filing reports after the fact.
This allows companies to conduct more effective safety audits, including using video evidence to determine specific trends and patterns. Over time, this information can help businesses determine how safety performance has evolved in the company.
7. SIF prevention
Computer-vision networks recognise the high-energy events that usually precede serious injury and fatality (SIF) incidents. By combining object velocity, contact force and proximity data, platforms produce an on-screen SIF risk-scoring bar that updates every few seconds.
Safety teams receive early warnings, act fast and stop life-altering injuries before they happen - a capability Marks & Spencer credits for a steep fall in unsafe events across its logistics hubs.
Results at a glance
Here's how leading organizations have benefited from AI-powered safety:
Total Recordable Incident Rate (TRIR) - Live sites using AI tools consistently report significant reductions.
Live sites using AI tools consistently report significant reductions. Lost Day Rate (LDR) - Fewer injuries lead to fewer staff sidelined.
Fewer injuries lead to fewer staff sidelined. Cost per recordable event - Declining claims and incident rates result in rapid ROI.
A global manufacturer recorded a 62% drop in all safety events during its first year on the platform, unlocking a rapid ROI in insurance and productivity gains.
Section 4 - Risks and Challenges of AI in Workplace Safety
While AI safety offers many advantages, it's also equally important for companies to analyze the downsides and make sure they mitigate the risks.
These are sophisticated systems, and employers must ensure they understand the risks. Here are three main areas of concern.
1. Human Controlled with Benign Intent
Human-controlled AIs can be configured for specific purposes, such as detecting the use of PPE in the workplace. AI systems with benign intent are primarily used for supervision.
Such AI systems are used primarily for evaluating safety performance, and the data gathered can be used to improve decision-making. These can be further divided into:
Non-robust - This is possible if the AI system works well on test data, but there's a significant difference in performance on other data sets.
This is possible if the AI system works well on test data, but there's a significant difference in performance on other data sets. Privacy violating - AI systems must be designed to ensure that they do not violate the privacy concerns of stakeholders, including exposing any private or identifying information.
AI systems must be designed to ensure that they do not violate the privacy concerns of stakeholders, including exposing any private or identifying information. Biased - The risk of biases is possible where the AI system exhibits bias towards specific objects.
The risk of biases is possible where the AI system exhibits bias towards specific objects. Inability to explain - The algorithm should be easy to interpret, with defined rules that govern its performance.
2. Autonomous AI Learning and Potential Safety Issues
AI safety tools are intelligent and autonomous, learning as more data is fed into the system. It's often difficult to determine how such systems will respond in practice, especially if a supervisor is absent.
In some instances, an interrupting agent may affect the ability of the system to be able to detect objects. It often takes more work to predict how the system might respond in dynamic environments.There's also the risk of the system being hacked and tampered with, affecting its ability to perform tasks.
3. Mitigating the Risks of Malicious AI Intent in Workplace Environments
AI can be used for malicious purposes, so companies must take appropriate steps for data safety and security. Policies must be instituted to ensure that the data gathered is not misused.
Malicious intent, such as mass surveillance, poses a risk as it can be misused in many ways. It's vital to devise specific governance policies and for companies to take steps to prevent this.
5 Tips for Managing and Mitigating Risks Associated With AI in the Workplace
Organizations need to take different steps to manage and mitigate the risks associated with AI systems in the workplace. Here are some critical risks and tips on how to mitigate them:
1. Cybersecurity Risks
One of the most significant risks associated with AI in the workplace is cybersecurity. As AI technologies become more prevalent, cyber attackers increasingly target them as potential entry points to access sensitive data.
To minimize the risk of cyber attacks, it is essential to work with the IT team to implement strong security measures. This includes monitoring access to data, implementing multi-factor authentication, and encrypting sensitive information.
2. Ethical Risks
AI can also create ethical risks in the workplace. For instance, AI tools may be designed to make decisions that impact employees, such as performance evaluations or hiring decisions.
As an EHS professional, it is essential to ensure that AI tools are designed and used in a way that is fair and unbiased. This could involve conducting regular audits of algorithms and making necessary modifications, as well as creating guidelines for the ethical use of AI in the workplace.
3. Health and Safety Risks
Certain types of AI, such as cobots (collaborative robots), have the potential to improve health and safety in the workplace. However, they can also introduce new risks to employees, such as mechanical hazards, ergonomic issues, and exposure to hazardous materials.
It is crucial to conduct a risk assessment before introducing AI into the workplace to determine potential hazards and develop appropriate controls to mitigate them.
4. Privacy Risks
AI technologies often require access to a significant amount of data, which can create privacy risks. Employees may feel uncomfortable with their personal information being gathered and analyzed by AI tools.
To address these concerns, it is essential to create clear policies for the collection, storage, and use of data. This includes obtaining employee consent and implementing robust data security measures to reduce the risk of data breaches.
5. Training and Awareness Risks
Finally, AI in the workplace requires a high level of knowledge and skill to operate effectively. Without proper training, employees may not know how to use AI tools safely and effectively and may inadvertently introduce risks into the workplace.
It is essential to provide ongoing training and awareness programs to ensure employees have the necessary skills to work effectively with AI tools.
Section 5 - How to Integrate AI in the Workplace for Safety Improvements
Companies have various options to integrate artificial intelligence in their workplaces. For instance, they can consider IoT (Internet of Things), which deploys micro-sensors to monitor machines, production lines, and employees.
However, this requires a significant upfront investment and may cause disruptions in work environments. In some instances, workplaces might have to be adapted before these sensors can be fully deployed, ensuring compliance with Occupational Safety and Health Administration (OSHA) guidelines for a safer workplace.
Integrating AI with Existing CCTV for Workforce Monitoring and Compliance
The best way to integrate AI into workplace safety is to connect an AI safety solution with your existing CCTV infrastructure. A video processing box can be connected to the feed, allowing for simple plug-and-play usage.
This ensures secure processing on-premises, allowing companies to take necessary steps to ensure the safety and security of the data. Once integrated, companies can define specific safety rules to start monitoring.
Section 6 - Ethical Considerations and Impacts Of AI In The Workplace
The integration of artificial intelligence and workplace safety requires careful ethical considerations, balancing innovation with accountability and trust. Artificial intelligence in safety and security extends beyond compliance to upholding organizational trust and integrity.
Ethical AI applications span critical issues such as bias, privacy, transparency, job displacement, and reskilling. Addressing these challenges is crucial for responsibly leveraging AI's benefits and promoting a fair and secure workplace.
Bias and Discrimination
One of the significant ethical concerns around AI is the potential for bias and discrimination. AI systems are only as unbiased as the data they are trained on, and if that data is biased, the AI system will be biased as well.
For example, if an AI system is used to screen job applicants and is trained on data biased against certain groups (e.g., women, minorities, etc.), that bias will be reflected in the system's decision-making.
It's vital to ensure that any AI systems used in the workplace are trained on unbiased data and regularly audited to identify and address potential risks.
Data Privacy and Security
Privacy by design sits at the core of responsible AI. Systems should capture only what they need, apply data minimisation, and keep raw video on-prem where possible.
Encryption, strict access control and audit logs ensure GDPR compliance while SOC 2 alignment proves the underlying processes are robust. These guarantees stop sensitive data leaking and maintain employee trust.
Transparency and Explainability
AI grows more complex every quarter, so organisations must strive for transparency and enterprise privacy & security in AI systems. When users can see how models reach conclusions, they interpret results correctly and mitigate health risks tied to occupational hazards.
Job Displacement and Reskilling in the Age of AI
Automation can make some roles obsolete, potentially leaving workers without employment, a concern explored in AI vs EHS managers. Proactive reskilling helps teams transition smoothly, promoting well-being and enabling human–machine collaboration.
Fairness and Accountability
Finally, it's vital to ensure that any AI systems used in the workplace are designed with fairness and accountability in mind. This means ensuring that the system is transparent and explainable, as well as developing appropriate mechanisms for recourse if the system makes a mistake or behaves unfairly.
By ensuring that AI systems are designed and implemented in a responsible, ethical way, companies can ensure that they are maximizing the benefits of these technologies while minimizing the potential harm.
Regulation and compliance issues related to AI in the workplace
Deploying AI in the workplace involves data management and analytic capabilities. It is recommended that organizations conduct an internal assessment of regulatory compliance regarding AI deployment in their facilities to avoid compliance-related risks.
For instance, the EU General Data Protection Regulation (GDPR) and local privacy laws require employers to protect their employees' personal data from disclosure to unauthorized entities.
AI programming and the related procedures must meet the security and privacy requirements of employee data.
Beyond this, the U.S. Equal Employment Opportunity Commission (EEOC) guidelines recommend vigilant scrutiny from an HR perspective when using decision-making algorithms for recruitment, selection, and performance evaluation.
Data Privacy and Security in AI Deployment
AI algorithms use the personal data and behavioral patterns of employees in their decision-making process.
As per GDPR, individuals have the “right to be forgotten,” a theme we cover in our computer-vision privacy guide. Employers must adopt encryption, access control and audit logs to safeguard sensitive data using certified AI safety technologies.
So, data privacy should be addressed while incorporating AI in the workplace. Employers should take the utmost care while implementing AI in their organizations and conduct the necessary privacy assessments to guarantee that the AI system complies with all relevant data privacy regulations.
Addressing the Potential Displacement of Jobs Due to AI
AI forms the core of many technological innovations we see around us, such as chatbots, self-driving cars, and algorithms used in financial trading. These systems improve productivity and reduce the costs of various industries.
However, this also means that AI systems can automate many repetitive and routine tasks humans previously performed. This leads to a significant effect on job displacement, particularly in areas where these tasks are prevalent.
While we need to acknowledge the potential job displacement caused by AI, it must be noted that the impact will depend on how we choose to implement AI technologies.
Promoting Responsible AI Implementation
Organizations need to implement AI systems responsibly, always considering the ethical and social impact of their adoption. This means that companies must be mindful of the potential consequences on their employees and be proactive in finding ways to retrain those employees to work in other areas.
It also means that policymakers must set regulations that promote responsible AI implementation.
Workforce Training
With automation and AI technology becoming increasingly common, organizations must train employees on new and emerging technologies to work alongside them. There is a rapidly increasing demand for workers with the skills to design, maintain, interpret, and improve AI systems.
Therefore, organizations should provide ample opportunities for their workforce to learn and develop new skills that align with their future needs.
Along with this, governments must also create education and training programs that enable people to reskill and upskill appropriately.
Job Enhancement
While the rise of AI does come with the potential for job displacement, it also brings the opportunity for job enhancement.
AI can automate mundane tasks, allowing workers to focus on more critical, creative, and value-adding work.
This means we must shift the focus from job displacement to job enhancement. According to a recent report by the IMF, AI and automation can supplement human labor to make work more efficient.
Incorporating Human Oversight and Decision-Making in AI Systems
One of the main reasons why human oversight is crucial in AI workplace safety systems is the potential for bias. Many AI algorithms are trained on datasets that contain preferences or incomplete information, resulting in decisions that perpetuate those biases, impacting workplace productivity and safety.
For example, facial recognition software is less accurate at identifying people of color and women than white men. Human oversight can help to identify and correct these biases by providing feedback and monitoring the algorithm's performance over time, ensuring safer AI applications in the workplace.
AI systems often need to be recalibrated to ensure accuracy and transparency, which is why human oversight is essential. In case an inherent bias is detected or if the AI system isn't working as intended, human oversight can prove to be critical in identifying and resolving the problem in its initial stages.
Addressing security concerns and protecting against adversarial attacks on AI systems
The use of AI in the workplace involves designing systems to make decisions using complex algorithms and vast data. One of the biggest challenges with AI is the potential for bias that can lead to errors in decision-making, raising potential risks.
As outlined by NIST, the algorithms can be manipulated or attacked by adversaries to exploit these biases, causing inaccurate decisions or, even worse, malicious outcomes.
To address this concern, it's essential to implement a rigorous machine learning process that uses AI risk management to consider potential attack vectors, including data poisoning, model inversion, or evasion attacks.
Implementing Robust Security Measures in AI Systems
You can use adversarial robustness tools, such as TensorFlow, which helps detect and mitigate these attacks and strengthens the security of machine learning models.
Another way to protect against adversarial attacks is to use multi-factor authentication( MFA) methods. These methods require multiple forms of identification, such as a password and fingerprint verification, to access the system. This makes it difficult for attackers to access critical data, even if they can guess passwords.
To further strengthen the system, the biometric information used in MFA must be carefully selected to prevent reconstruction of the authentication database or fake image replication by the adversary.
Strengthening AI System Security with Regular Assessments
Organizations should conduct regular security assessments and cyber drills on their AI systems to identify possible weak points. These assessments should include penetration testing and auditing software codes, network infrastructure, and data storage.
The results of these assessments should be used to improve system configurations and to address vulnerabilities or potential attack areas.
If organizations can identify these risks and address them before an attack occurs, they will be better equipped to prevent or mitigate the damages caused.
Addressing Societal and Economic Impacts of AI in the Workplace
AI is transforming many industries that were previously heavily reliant on human labor, such as manufacturing, logistics, and transportation.
While this transformation might lead to the loss of jobs, it also presents an opportunity for new job creation in other areas, supporting both workplace well-being and productivity. The increased efficiency could also increase quality, leading to better products and services.
The economic impact of AI is significant, with the potential to increase productivity, growth, and employment rates. However, the impact could vary widely between different industries and geographic regions, leading to polarization in the labor market.
It is essential to consider the broader social and economic implications of how AI is being used in the workplace to ensure that benefits are shared equitably in society.
Companies need to make sure that they address any concerns that employees may have and highlight the benefits that AI safety solutions offer.
Section 7 - Choosing the Best AI Safety Solution
Protex AI is a workplace safety solution that leverages the power of artificial intelligence to help safety professionals make effective safety decisions. It connects seamlessly with all modern camera systems. It can be customized based on your requirements, letting you define workplace risk.
Its plug-and-play nature means it can efficiently work with CCTV networks, big or small. Protex AI empowers EHS teams by providing them with essential insights about safety performance.
Safety events or rule breaches are recorded, tagged, and stored for review by teams, offering them evidence-based insights about the performance of safety protocols contributing to a safer environment. It auto-generates safety reports and can automatically tag stakeholders or specific team members.
The storyboard functionality allows EHS teams to create automated email workflows, add documents, or even record commentary to brainstorm and implement corrective actions.
| 2025-06-06T00:00:00 |
https://www.protex.ai/guides/the-complete-guide-to-ai-safety-in-the-workplace
|
[
{
"date": "2025/06/06",
"position": 64,
"query": "workplace AI adoption"
}
] |
|
CEOs think workers are becoming hostile to AI tools, but ...
|
CEOs think workers are becoming hostile to AI tools, but they’re pushing ahead with adoption anyway
|
https://www.itpro.com
|
[
"Nicole Kobie"
] |
Notably, executives disagreed on how to approach workforce readiness when it comes to AI adoption. Tech executives, such as CTOs, are far more focused on ...
|
Nearly half of CEOs believe their employees are becoming openly hostile to AI tools, but it's not slowing down adoption rates.
That's according to a survey by tech services company Kyndryl, which polled 1,000 executives to unpick how ready workforces were for the arrival of AI.
One of the key findings was that 45% of CEOs think that most of their employees are anti-AI — though just 8% of CTOs and CIOs believe employees are resistant to the technology.
"Preparing your workforce for the era of AI is easy to say, hard to do, and an urgent imperative for business leaders," said Maryjo Charbonnier, Chief Human Resources Officer at Kyndryl.
Notably, executives disagreed on how to approach workforce readiness when it comes to AI adoption. Tech executives, such as CTOs, are far more focused on upskilling existing staff, with 80% favoring this strategy.
In contrast, four-in-ten CEOs said they are prioritizing hiring external talent to bolster skills in the technology.
No wonder then that 27% of CEOs believed fears of job displacement was a serious barrier to AI, with the same figure believing resistance to change would also slow AI adoption.
Get the ITPro daily newsletter Sign up today and you will receive a free copy of our Future Focus 2025 report - the leading guidance on AI, cybersecurity and other IT challenges as per 700+ senior executives Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors
The report echoes research by IBM last year that suggested CEOs are pushing adoption of generative AI more quickly than workers are comfortable with.
Nearly two-thirds (64%) of CEOs said they are accelerating AI adoption plans, but only 44% of respondents revealed they had “assessed the impact” of the technology on their workforce. This, the study warned, is creating a divide among executives and frontline staff.
The Kyndryl research found 95% of companies have invested in AI in some way, but 71% of leadership say their workforces aren't ready to make best use of the technology, with 51% believing there's a skills gap.
That suggests that organizations are successfully investing in the technology side of AI, but lack full readiness because they've neglected the people side of the equation, said Michael Bradshaw, Global Practice Leader for Applications, Data and AI at Kyndryl.
"Only a small group of businesses have been able to harness AI successfully for business growth," Bradshaw commented.
"This report shows that while data architecture and technology infrastructure are key pieces of the puzzle, organizations that do not prioritize their workforces and organisations will miss out."
That said, the report noted that workforce readiness varies depending on sector or industry, led by financial services with healthcare trailing.
How businesses are using AI
While most companies surveyed had fully deployed AI in some way, just 35% said it was fully integrated across the organisation. A further 39% said it was in use in some areas while another 21% said AI implementations were still in early stages.
The report found that generative AI tools were the most popular form of the technology in business, used by nearly two-thirds of those surveyed, but they aren't necessarily being used for the biggest impact.
Just four-in-ten are targeting growth and while only 20% are developing new products or services.
Companies doing the most with AI, which the report referred to as AI Pacesetters, are three times more likely to have implemented a change management strategy, and nearly a third less to see concerns from staff about AI.
"The encouraging news is that organisations who can get alignment at the top are not only marching in the same direction, but are seeing the benefits of that alignment," said Kim Basile, Chief Information Officer at Kyndryl.
"This work isn’t easy, but aligning technology strategies with broader business goals is the top action leaders need to take to fully benefit from AI."
| 2025-06-06T00:00:00 |
2025/06/06
|
https://www.itpro.com/business/business-strategy/ai-tools-adoption-ceo-workers
|
[
{
"date": "2025/06/06",
"position": 65,
"query": "workplace AI adoption"
}
] |
How AI may be robbing new college graduates of traditional entry ...
|
How AI may be robbing new college graduates of traditional entry-level jobs
|
https://www.pbs.org
|
[
"John Yang",
"Gerard Edic"
] |
The college class of 2025 is entering one of the most challenging job markets in years, with the unemployment rate the first three months ...
|
Aneesh Raman:
Yeah, we talked about a couple of examples in the piece. KPMG is now giving new grads higher level tax work that used to go to people that had, I think two or three years worth of experience because AI is handling a lot of the grunt work.
McFarland`s this law firm in the UK, they`re training early career lawyers on complex contract interpretation, not just basic document review. If you think about it, a lot of entry level jobs are basic jobs with basic tasks. All we need to do on the employer side is up level the tasks that we give entry level workers and be more deliberately appreciative of the know how they bring.
This generation is incredibly resilient and adaptive. They know AI tools and technology better than probably any other generation. Educators also have to adapt.
And so we also talk about American University, the business school in DC, but also community colleges across the country who are helping students learn more and more AI fluency, AI proficiency. And that just basically means what are these AI tools? How do they help me do the job I`m doing and what does it mean for this sort of up leveling of that job?
We`ve got to have that baked into all education everywhere and then help people understand what is that new type of work they want to do as they go into the workplace.
| 2025-06-07T00:00:00 |
2025/06/07
|
https://www.pbs.org/newshour/show/how-ai-may-be-robbing-new-college-graduates-of-traditional-entry-level-jobs
|
[
{
"date": "2025/06/07",
"position": 87,
"query": "AI unemployment rate"
},
{
"date": "2025/06/07",
"position": 89,
"query": "AI unemployment rate"
},
{
"date": "2025/06/07",
"position": 72,
"query": "AI unemployment rate"
},
{
"date": "2025/06/07",
"position": 5,
"query": "AI unemployment rate"
}
] |
Education and AI
|
Education and AI
|
https://www.adalovelaceinstitute.org
|
[
"Renate Samson",
"Kruakae Pothong"
] |
The Ada Lovelace Institute and the Nuffield Foundation are collaborating on research into the role of AI and data-driven technologies in education.
|
Project background
Data and digital technologies have long played a role in education in the UK. For example, information on students’ learning and attainment is used not only to assess progress, but also to inform school performance rankings and policymaking. Schools’ use of digital technologies, primarily for teaching and learning, spiked due to remote learning during the COVID-19 pandemic.
The use of artificial intelligence (AI)-driven technologies in education is varied. ‘Narrow’ AI –task-specific systems trained with a dataset that is curated for a particular purpose – is used for administration tasks such as analytics, safeguarding, classroom management, SEND education and some personalised learning.
To date, teachers’ use of general-purpose AI or generative AI (such as commercial and non-education specific products like ChatGPT, Microsoft Co-Pilot or Google Gemini) for lesson planning and to support marking and assessment is mostly informal, despite the hype and investment.
The use of these technologies raises questions about their impact on outcomes, not least in relation to the accuracy of their outputs. Meanwhile, the development of AI technologies for use in education is in its infancy, with a handful of products emerging. These are yet to be evaluated for accuracy, efficacy and efficiency in the classroom.
While AI and education-specific AI technologies have the potential to support teachers with their planning, teaching, administration and time, the benefit for pupils and students is yet to be proven clearly.
Furthermore, the risks and potential harms from their use are yet to be fully understood, and many are unique to these new technologies. Previous harms caused by algorithms, narrow AI and the use of data-driven technologies within education – such as the failure of the A-level grading algorithm in 2020, or the data protection and data exploitation risks associated with commercial learning platforms such as Google Classroom and ClassDojo – highlight the need for safeguards to be established to ensure that the benefits can be realised without the negative impacts being experienced by students and staff.
As data-driven and AI technologies develop, and their procurement in education increases, more research is needed to assess their impact on teaching practices and administration, and on students’ development and attainment.
Project overview
The Ada Lovelace Institute and the Nuffield Foundation are collaborating on research into the role of AI and data-driven technologies in education.
In 2023 we submitted a response to the Department for Education’s call for evidence on generative AI in education.
In early 2025, we published A learning curve?, a landscape review of AI in education in UK state-funded primary and secondary schools. This paper focuses on evidencing the opportunities, benefits and risks of AI in relation to teaching and learning, marking and assessment, and careers guidance.
June 2025: Call for expressions of interest As part of the next phase of this project, we are looking to explore teachers’ views and experiences of AI as a tool to support teaching practice and the impact it might have on teaching and learning, and on the profession in general. We are keen to engage both with teachers with experience of using AI as part of their teaching practice and with teachers who have little or no experience of AI. If this research sounds of interest and you would like to be contacted as the project develops (and only for this purpose), please provide your email address via this online form. We will be in touch within the next four months (and will only store your email address for this period).
Image credit: JohnnyGreig
| 2025-06-07T00:00:00 |
https://www.adalovelaceinstitute.org/project/education-ai-uk/
|
[
{
"date": "2025/06/07",
"position": 21,
"query": "AI education"
}
] |
|
Meet the JournalismAI Fellows of 2022
|
Meet the JournalismAI Fellows of 2022 — JournalismAI
|
https://www.journalismai.info
|
[
"Lakshmi Sivadas"
] |
... AI techniques with traditional reporting methods to innovate how journalism is produced. ... We aim to create a multilingual tool for journalists that uses AI ...
|
Their projects will explore how a responsible use of AI can contribute to building more sustainable, inclusive, and independent journalism in all parts of the world. From building tools to support investigative journalists in their research, to automatically detecting hate speech on social media, and helping newsrooms identify underreported topics in their coverage, the JournalismAI Fellows will combine the latest AI techniques with traditional reporting methods to innovate how journalism is produced.
The ten Fellowship teams continue the JournalismAI tradition of fostering cross-border and interdisciplinary collaboration, with data scientists, reporters, product managers, researchers and software engineers working together with peers from news organisations in different continents – including collaborations between legacy brands and digital media from India and South Africa, Spain and Australia, as well as Argentina, Paraguay and the Philippines.
Due to the significant amount of exciting project proposals we received – 61 news organisations applying from 35 countries – we selected ten teams of Fellows rather than five as initially planned. Thanks to the support of the Google News Initiative and of our partners at the Northwestern University | Medill’s Knight Lab, we will guide the ten teams in the development of their projects, leading up to the presentation of their products and findings at the 2022 edition of the JournalismAI Festival.
To stay informed about the work of the fellows over the coming months, you can sign up for the JournalismAI newsletter.
The JournalismAI Fellows of 2022 are:
Attack Detector
Reinaldo Chaves (Project Coordinator) & Schirlei Alves (Data Journalist), Abraji (Brazil)
Fernanda Aguirre Ruiz (Data Analyst and Researcher) & Gibrán Mena (Research and Direction), Data Crítica (Mexico)
Our project aims to train a language model to detect hate speech on social media – in Spanish and Portuguese – directed primarily at journalists and environmental activists. The model will classify the instances of hate speech among their diverse categories and understand why and how they are happening.
Automating Visuals for Machine-Driven Content
Theresa Poulson (Senior Product Manager) & Tyler Dukes (Investigative Reporter), McClatchy (US)
Sean Smith (Product Manager) & Mike Stucka (National Data Solutions Editor), Gannett / USA TODAY Network (US)
One of the biggest challenges with AI-made coverage is the ability to generate images that enrich and compliment stories. Images are also key to successful distribution and reaching new audiences. Our project will explore a solution for automatically creating relevant imagery for content made with natural language generation.
Bad Will Hunting
Alet Law (Audience Development Manager) & Tinashe Munyuki (Retention Manager), Daily Maverick (South Africa)
Luis Flores (Data Scientist) & Chris Moran (Head of Editorial Innovation), The Guardian (UK)
Dimitri Tokmetzis (Senior Investigative Journalist and Data Team Lead) & Heleen Emanuel (Data Journalist and Creative Developer), Follow The Money (Netherlands)
Searching and comparing massive datasets for evidence of graft has become a big part of many investigative journalists’ jobs. Our project will use AI to extract NLP entities based on enriched context from long-form text, to do cross-referencing with preexisting knowledge bases/graph models. In doing so, we hope to cut down the time needed in manual curation.
Claim Check
Gina McKeon (Innovation Editor) & Gareth Seneque (Technical Lead – AI/ML), Australian Broadcasting Corporation
Irene Larraz (Fact-Checking and Data Coordinator) & Rubén Miguez (Chief Technology Officer), Newtral (Spain)
We aim to create a multilingual tool for journalists that uses AI to quickly detect false claims by setting up an alert system through an interface in Teams or Slack. This system will become a central hub for newsrooms to quickly check specific claims, thereby improving accuracy and enhancing the reporting capabilities of newsrooms.
Context Cards
Amanda Strydom (Senior Programme Manager – CivicSignal) & Fadel Thior (Deputy Investigative Manager), Code for Africa / PesaCheck (South Africa)
Ritvvij Parrikh (Director of News Products) & Karn Bhushan (Lead Data Analyst), Times of India
Context Cards is a machine learning model that creates and suggests context — data, bios, summary, location, timeline — to audiences and journalists, alongside an article. It will be trained on newsroom archives, and learn from editors’ feedback. We are building on prior work, including modularjournalism.com, Newscards, and Structured Stories.
Image2Text
Lucila Pinto (Product Manager) & Nicolas Russo (Product Manager), Grupo Octubre (Argentina)
Jaemark Tordecilla (Editor-in-Chief and Head of Digital Media) & Raymund Sarmiento (Chief Technology Officer), GMA News Online (Philippines)
Sara Campos (Product Editor) & Eduardo Ayala (Senior Full-Stack Developer), El Surti (Paraguay)
Image2Text identifies, classifies and describes video and images for newsrooms. Powered by computer vision models, it recognises objects and people in video, images and infographics, and describes them in Spanish and English through natural language. The tool seeks to promote better data governance by including perspectives from the Global South.
Nubia
Joshua Olufemi (Founder and Managing Director) & Emmanuel Alawode (Full-Stack Developer), Dataphyte (Nigeria)
Mads Ommundsen (Journalist & Product Owner) & Frode Norbø (Developer and Designer), Fædrelandsvennen (Norway)
Nubia is an AI-powered reporter that auto-creates development reports and data insights by transforming real time data from satellite/web camera imagery, weather and socioeconomic data into news reports, data insights and advisory that can be distributed directly to the newsroom and general audience.
Parrot
Venetia Menzies (Data and Digital Journalist) & Ademola Bello (Data Journalist), The Times & Sunday Times (UK)
Alessandro Alviani (Product Owner) & Simone Di Stefano (Data Engineer), Ippen Media (Germany)
Parrot is a tool and methodology to help journalists identify and measure the spread of manipulated narratives from state-controlled media. Using AI we will develop an early warning system that clusters and classifies state media generated text and then detects coordinated efforts at its dissemination.
Tracking Influencers
Carmen Aguílar Garcia (Senior Data Journalist) & Przemyslaw Pluta (Head of Platform Solutions), Sky News (UK)
Juliana Fregoso (Project Manager for AI and Special Projects Newsroom) & Matias Contreras (Chief Technology Officer), Infobae (Argentina)
Pier Paolo Bozzano (Journalist and Head of Content Innovation Lab) & Marina Caporlingua (Software Engineer), Il Sole 24 Ore (Italy)
Our project aims to help journalists to investigate influencers on a greater scale using AI techniques and developing a replicable methodology. It will track the brands, products, topics that influencers are sharing, and it will develop a scoring system to flag potential harmful or misleading content for a journalist to investigate further.
What’s there? What’s missing?
Jörg Pfeiffer (Product Manager) & Philipp Gawlik (Language Engineer and Computational Linguist), Bayerischer Rundfunk (Germany)
Martin Paul (Chief of Service, Journalist) & Jaime Avalos Mongil (Junior Data Scientist), MDR / ida (Germany)
BR and MDR are both German public broadcasters with the mandate to provide multifaceted information to different kinds of audiences. We want to use NLP to build a tool that analyses our published content, as well as the reactions of our audiences, to find underreported topics in our publications.
| 2025-06-07T00:00:00 |
https://www.journalismai.info/blog/ytcuy8y1yh0s12asc97ahsiezbw169
|
[
{
"date": "2025/06/07",
"position": 27,
"query": "AI journalism"
}
] |
|
Free Journalism: Using AI for Truth, not Power
|
Free Journalism: Using AI for Truth, not Power
|
https://www.africanliberty.org
|
[
"Aidan Eyakuze",
"Irene Ofori-Agyeman",
"Jude Ayua",
"Abiodun Salako"
] |
Free Journalism: Using AI for Truth, not Power ... Artificial intelligence (AI) is no longer an “emerging” technology. It is here as the new infrastructure of ...
|
Artificial intelligence (AI) is no longer an “emerging” technology. It is here as the new infrastructure of influence, and yet, it is not equally distributed. We live in an era of mutually assured surveillance where states and corporations use AI to facilitate all kinds of repressive actions: monitoring activists, spreading disinformation, and restricting access to public goods, to name a few.
But what if journalists and citizens used AI to watch the watchers as well? To shine light where others prefer shadows? Here are three ways forward to ensure that AI, press freedom, and public power serve democracy and human dignity.
AI must ignite civic engagement
AI’s potential is not abstract. It is already helping citizens hold power to account. Civic engagement doesn’t happen by accident. It’s nurtured when journalists use AI to open doors, not close them.
In Nigeria, civic tech group BudgIT trained a machine learning tool called Bimi to detect irregularities in government budgets. Suddenly, missing funds aren’t hidden—they’re flagged for every citizen to see.
In Kenya, newspapers like The Star and Daily Nation use AI-driven chat tools and data visualisations to make complex stories accessible, sparking public debate and scrutiny.
These are not stories of technology replacing journalists. They are stories of technology amplifying the work of journalists to inform, engage, and empower citizens.
But here’s the thing: AI will only serve accountability if it is fed with good data, governed by independent scrutiny, and backed by institutions that welcome transparency, not fear it. (If you’d like to learn more, the OGP Horizons series covers this idea in more detail.)
Building a shared reality
“Water, water everywhere, [but not a] drop to drink!” This is the famous line from Samuel Taylor Coleridge’s poem The Rime of the Ancient Mariner, about a sailor who can’t drink any of the salt water around him while he drifts in the ocean, shipwrecked.
Just like the sailor, we are drowning in an ocean of information—and thirsting for truth.
Disinformation, deep fakes, and “truth decay” threaten the very foundation of democratic discourse. As Maria Ressa, the fearless Filipino journalist and 2021 Nobel Peace Prize winner, reminds us, “Without facts, there is no truth. Without truth, no trust. Without trust, no shared reality—and without that, democracy dies.”
AI can help us rebuild that shared reality, but only if we wield it wisely.
In Ukraine, open-source investigators are using AI to verify battlefield images and spot coordinated, inauthentic behaviour on social media, countering propaganda in real-time. AI, when guided by journalistic integrity and civic purpose, becomes a shield, not a sword.
But let’s be clear: AI is an amplifier, not a solution. It can filter noise, but it cannot replace human judgment. It can speed up research, but it cannot define truth. For example, Estonia has heavily invested in media literacy education and local media outlets to counter disinformation alongside the creation of AI-powered fact-checking tools. This layered response is essential to build resistance to propaganda attacks.
It is up to us—editors, reporters, fact-checkers, and civil society—to ensure that AI serves public interest journalism, not the interests of those who profit from confusion. In this task, journalists do more than report facts. They defend reality itself.
Democratised not weaponised
We’ve seen this story before. Social media platforms were hailed as a tool of liberation during the Arab Spring and promised to connect us to civic life. But instead of fulfilling this promise, these platforms have become engines of surveillance, division, and exploitation. The reason is simple: when tech companies prioritise profit over people, society suffers.
There’s a real risk that AI can run the same course. If AI remains in the hands of a few powerful corporations and governments, the rest of us risk becoming data points, not decision-makers.
That’s why journalists must not only use AI — they must interrogate it. Investigative reporters should ask: Who built this algorithm? Whose interests does it serve? What biases are hidden beneath the code?
Interrogating AI is the first step to changing its impact as a force for good. This is not science fiction. It is within reach, but only if we insist that AI works for democracy, not against it. That requires more than imagination. It demands independent institutions, robust privacy protections, and unwavering commitment to journalistic confidentiality.
Brave New World
We are living in a brave new world, but all is not lost. We have the power to change course by supporting press freedom and engaging with citizens to give them the tools to fight back against the harms of AI.
Let us choose a future where AI serves truth, not power. Where journalists, civic watchdogs, and citizens alike are equipped to hold the powerful to account.
This is not a task for journalists alone. Nor for civil society organisations, judges, or legislators acting in isolation. It is a task for all of us. If we act with courage, with clarity, and with conviction, AI will not define the future of journalism. We will!
Aidan Eyakuze is the CEO of the Open Government Partnership and a director of the Thomson Reuters Founders Share Company. He’s available at [email protected] or on X as @aeyakuze.
Article first appeared in The Chanzo.
Photo by Markus Winkler via Unsplash.
| 2025-06-07T00:00:00 |
2025/06/07
|
https://www.africanliberty.org/2025/06/07/journalism-in-the-brave-new-world-let-us-choose-a-future-where-ai-serves-truth-not-power/
|
[
{
"date": "2025/06/07",
"position": 80,
"query": "AI journalism"
}
] |
Research: Most newsrooms not officially using AI
|
Research: Most newsrooms not officially using AI
|
https://mediacareerng.org
|
[
"Lekan Otufodunrin",
"Dayo Emmanuel",
"Media Career Development Network",
"Elizabeth Osayande",
"Kehinde Adegboyega",
"Abimbola Oluwakemi"
] |
Most newsrooms in Nigeria have yet to incorporate AI as an official tool in news processing. This is part of the preliminary findings of a research.
|
Most newsrooms in Nigeria have yet to incorporate AI as an official tool in news processing.
This is part of the preliminary findings of a research on the “Use of Artificial Intelligence in Newsrooms” by a group of researchers from the Department of Mass Communication, Plateau State University.
Journalists sampled for the research, however, admitted to using AI in their engagements.
The research also revealed that concerns were raised about the use of AI, especially around manipulating AI algorithms to promote misinformation and disinformation, with responses pointing to deepfakes.
“We also discovered that influential bodies like Nigeria Union of Journalists (NUJ) have not yet developed a clear regulatory policy on using AI in journalism.
“Few newsrooms have a framework in place to guide the use of AI, and most journalists use the free versions of AI tools, reducing their capacity to explore the whole gamut of AI platforms to enhance their tools,” Dr Adeyanju Apejoye, the lead researcher, stated.
ALSO READ: Shifting Battle Fronts: From Guerrilla to AI
Twenty-six journalists from the Nigeria Television Authority (NTA), Daily Trust Newspaper, Plateau Radio and Television (PRTV), Vanguard, Super FM, Benin, TIN City Radio, and The Nation Newspapers were sampled and data collected between March and April 2024.
The researchers recommended that media organisations, media development agencies, and relevant government agencies implement a training programme to train journalists on using AI for news gathering, processing, and dissemination.
” We also recommended that the government and other relevant organisations encourage the development of AI platforms that reflect local nuances, and Nigerian journalists should be involved in training such language models for use in journalism practice,” Dr Apejoye said.
| 2025-06-07T00:00:00 |
2025/06/07
|
https://mediacareerng.org/research-most-newsrooms-not-officially-using-ai/
|
[
{
"date": "2025/06/07",
"position": 47,
"query": "artificial intelligence journalism"
}
] |
100 Beliefs About AI & the Future of Work
|
100 Beliefs About AI & the Future of Work
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https://kobyofek.com
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[] |
AI rearranges work long before it replaces it. · Automation deletes tasks, not humans— unless humans cling to tasks. · Your "job" is really a bundle of micro‑ ...
|
The following are beliefs and understandings about AI and the future of work. They guide me in my research and helped me write Keep Your Day Job. While I see every fact individually as a temporary belief that I hold, together they hold a certain power and give an interesting insight into how I see the future of work.
AI rearranges work long before it replaces it.
Automation deletes tasks, not humans— unless humans cling to tasks.
Your "job" is really a bundle of micro‑tasks; AI eats the low‑hanging ones first.
The biggest career risk is not AI—it’s human inertia.
History’s “job apocalypses” always ended as skills reshuffles: steam, sparks, silicon—repeat.
Robots build the cars; humans build the robots.
In every productivity equation, Human + AI > Human + Human.
Learning to prompt is the new touch‑typing—basic, ubiquitous, non‑negotiable.
AI is a power tool; without skill, it’s still a finger‑remover.
The fastest way to future‑proof is to audit your Task DNA every quarter.
Latency tolerance is the secret moat—when speed kills, humans charge a premium for nuance.
“Co‑pilot” is not a job title; it’s a mindset.
If capital shifts, your calendar must shift with it.
The floodplain of disruption is wide; buy skills insurance, not sandbags.
One hour of AI Shadowing beats nine months of theoretical upskilling.
AI cost curves fall faster than your learning curves rise—start today.
The barbell career—deep human moat + broad AI fluency—outlifts any single heavyweight skill.
Automation anxiety is a feature, not a bug; channel it or drown in it.
Your résumé verbs matter less than your adaptive verbs: learn, test, iterate.
“Prompt engineer” is a temp title; strategic prompters endure.
Trust travels slower than data—humans remain the couriers.
AI makes mediocre faster; only remarkable survives.
Every efficiency gain spawns a demand gain somewhere else.
If AI handles the what, humans must master the why.
Humanoid robots may walk, but plumbers still crawl under sinks.
Ethical judgment scales slowly and expensively—still a human franchise.
An AI‑generated first draft is an empathy test you must pass.
Output without oversight is a liability multiplier.
Your new boss is a dashboard—learn to manage up to metrics.
Historical pattern: panic ➜ diffusion ➜ diversification. Anchor there.
If the algorithm sets quotas, negotiate the metrics, not the feelings.
Curiosity beats certainty in every technological arms race.
AI tutors level playing fields—unless access is gated by privilege.
Digital leverage turns one clever human into ten average ones.
Soft skills were renamed “hard to automate” skills—act accordingly.
Data empathy—reading what the numbers can’t say—is the new storytelling.
Cheaper creation shifts value to curation and orchestration.
Humans remain accountable—ask any malpractice lawyer.
Burnout isn’t inevitable; it’s usually un‑automated busywork.
The grey zone between full automation and manual toil is where margins bloom.
Learning velocity outranks accumulated knowledge after every tech quake.
AI widens capability gaps—your network closes opportunity gaps.
Career APIs—expose your skills as endpoints others (and AIs) can call.
Fear of tinkering is the true FOBO—Fear of Becoming Obsolete.
Adaptive teams beat superstar individuals when the toolset changes weekly.
Metrics monitored by AI become performance art—rehearse wisely.
Augmentation without upskilling is just slower replacement.
Your comparative advantage lives where accountability is high and latency is tolerated.
Brittle ethics statements crumble; living ethical audits endure.
The sooner you fire a task, the later you fire a teammate.
Human latency premium: minutes of reflection worth millions in liabilities.
Resilience stacking—cognitive, emotional, social, financial—beats any single safeguard.
Robots don’t take coffee breaks; humans need them to think.
If an algorithm scores your empathy, learn to game empathy authentically.
First drafts from AI demand second drafts of human judgment.
A portfolio paycheck hedges against single‑employer automation shocks.
“One more tool” thinking is how tech debt colonises workflows.
Scarce attention, not scarce information, defines the new economy.
Prompt libraries are the new trade secrets. Guard or share wisely.
Career ladders dissolve into fog; build way‑finding systems, not rungs.
AI capabilities double; your trust budget with stakeholders halves—communicate twice as much.
If your meeting could be auto‑summarised, it should probably be auto‑cancelled.
When AI turns every lens on productivity, rest becomes rebellion.
Teaching a robot is still teaching—pedagogical skills transfer.
Automation anxiety spikes where accountability meets opacity.
The best defense against hallucinations is domain expertise, not disclaimers.
AI won’t run out of random ideas; only humans decide which are ridiculous.
Prompt once, curate twice, deliver thrice the value.
Historical edge case: the weaver who became a loom mechanic survived the revolution.
Strategic procrastination = waiting for AI cost curves to drop before scaling.
Guardrails beat bans; regulated AI still outruns shadow IT.
Context is expensive to encode; humans provide discount nuance.
Your career moat leaks without continuous dredging—learn or sink.
Complex negotiation remains stubbornly analog.
A classroom without human warmth is a MOOC with desks.
Metrics have halos—once tracked, they overshadow untracked value.
Robotic colleagues need human culture, or they inherit our worst biases.
Surveillance by algorithm rewards performative busyness—choose outputs, not optics.
Decoupling identity from tasks is the first step to reinvention.
In crises, we reach for trusted humans, not trusted interfaces.
Tenure is time‑capped when skills half‑life accelerates.
Your ability to explain AI‑generated insights is itself a moat.
Ethical foresight outranks technical hindsight.
Curated randomness—exposing AI to diverse prompts—fuels breakthrough creativity.
Luddites weren’t anti‑tech; they were pro‑livelihood—context matters.
Algorithmic bosses never sleep; boundaries must.
Data rich, context poor is the new digital poverty line.
Skills compounding beats skills stacking—make each new skill multiply the rest.
Code is no longer king; orchestration is emperor.
Saying “I don’t do prompts” in 2025 is like saying “I don’t do email” in 1995.
The future worker is part technologist, part translator, part therapist.
If no AI model knows your niche, congratulations—monetize the gap.
AI magnifies biases already coded into the budget line.
The lights‑out factory myth ignores the electrician who resets the breakers.
Humor remains stubbornly hard to automate—keep your wit sharpened.
Mental fitness is infrastructure; stress corrodes adaptation capacity.
Most careers fail not from disruption, but from narrative lag. Update yours.
Fear may be inevitable; paralysis is optional.
Augmented teams redeploy talent, not just headcount.
| 2025-06-07T00:00:00 |
https://kobyofek.com/articles/100-beliefs-about-ai-and-the-future-of-work/
|
[
{
"date": "2025/06/07",
"position": 84,
"query": "future of work AI"
}
] |
|
The Role of AI in Finance & Accounting Hiring
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The Role of AI in Finance & Accounting Hiring: What Boston Companies Should Know
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https://www.dewintergroup.com
|
[] |
In Boston, firms are already leveraging AI to: Streamline internal processes: Automated systems can handle the heavy lifting of data aggregation and initial ...
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The Role of AI in Finance & Accounting Hiring: What Boston Companies Should Know
The vibrant finance and accounting landscape in Boston is no stranger to innovation. From established financial institutions to rapidly growing tech startups, the demand for top-tier talent remains consistently high. However, a shift is underway, one that promises to fundamentally reshape how finance and accounting professionals are recruited, trained, and utilized: the rise of Artificial Intelligence (AI).
For Boston-area employers and hiring managers, embracing the AI-driven revolution in hiring is no longer optional—it’s essential to staying competitive. With our finger on the pulse of both candidate expectations and market demands, we understand the stakes firsthand. Located in the heart of Boston, our DeWinter team has built a reputation as a trusted partner in finance, accounting, and technology staffing across Massachusetts and the greater New England region. In this article, we’ll explore how AI is reshaping hiring in finance and accounting, highlighting key automation trends, in-demand skills, and actionable strategies to help your team lead in this evolving landscape.
Automation: Redefining Roles and Routines
AI and Robotic Process Automation (RPA) are rapidly automating many of the repetitive, rule-based tasks that have historically formed the backbone of finance and accounting roles. Think invoice processing, data entry, reconciliations, and even some aspects of financial reporting. These aren't just efficiency gains; they are fundamental shifts that free up team members for higher-value activities.
In Boston, firms are already leveraging AI to:
Streamline internal processes: Automated systems can handle the heavy lifting of data aggregation and initial analysis, leading to faster month-end closes and real-time financial insights. This translates to finance departments operating at faster speeds, enabling quicker decision-making. In fact, some studies find that reporting errors are reduced by 90% when automation is implemented across financial operations.
Enhance accuracy and compliance: AI-powered tools virtually eliminate human error in data handling, ensuring greater accuracy in financial records and significantly improving audit readiness. These automated workflows even create comprehensive audit trails, meeting stringent accounting standards. Reduce operational costs: While there's an upfront investment, the long-term cost savings from reduced labor and fewer errors are substantial. Scalable AI platforms can accommodate significant business growth without a proportional increase in headcount, a major benefit for scaling Boston businesses. Indeed, AI has shown significant potential, with some reports indicating cost reductions of up to 20% in procurement and operational tasks by automating processes and reducing labor expenses.
This automation trend means that the traditional duties of entry-level and even some mid-level finance and accounting professionals are evolving. The emphasis is shifting from transactional processing to analytical interpretation and strategic contribution. As Ginni Rometty, former CEO of IBM, famously put it, "AI will not replace humans, but those who use AI will replace those who don't."
In-Demand Skills for the AI-Powered Finance Professional
As AI takes over the mundane, the skills that will define success for finance and accounting professionals in Boston are shifting dramatically. Employers should look for candidates who aren't just good with numbers, but also comfortable with new tech.
Here are some of the most in-demand skills:
Data Literacy and Analytics: Beyond basic Excel, professionals need to be adept at understanding, interpreting, and even manipulating large datasets. Skills in data mining, advanced analytics, and familiarity with business intelligence (BI) tools are becoming crucial. This includes understanding statistical analysis techniques to extract meaningful insights from data.
AI Literacy and Understanding: It’s not about being an AI developer, but about understanding how AI tools work, their capabilities, and their limitations. This includes knowing how to leverage AI for tasks like forecasting, risk modeling, and generating financial reports. For example, understanding how to interact with Generative AI models to summarize information or analyze complex financial data is invaluable.
Critical Thinking and Problem-Solving: With automation handling routine tasks, finance professionals will spend more time analyzing exceptions, identifying discrepancies, and solving complex financial problems. The ability to think strategically and critically about financial data is extremely important when given these more complex and technical problems.
Communication and Storytelling: Translating complex financial insights, often generated by AI, into understandable and actionable recommendations for non-finance stakeholders is a vital skill. Strong communication, presentation, and collaboration abilities are essential for finance professionals to contribute meaningfully to strategic planning.
Adaptability and Continuous Learning: The pace of technological change means that finance and accounting professionals must embrace a mindset of continuous learning. Staying updated on new AI tools, regulatory changes, and evolving best practices is non-negotiable for career longevity. The World Economic Forum's Future of Jobs Report indicates that "analytical thinking and innovation are among the top skills projected to grow in prominence by 2027," reflecting the increasing value placed on data-driven decision-making in accounting.
Cybersecurity Awareness: As more sensitive financial data is processed and stored by AI systems, a strong understanding of data governance, security, and privacy best practices is crucial to mitigate vulnerabilities.
Risk Management: In a rapidly evolving financial landscape driven by AI, the ability to identify, assess, monitor, and mitigate risks, including those introduced by new technologies, is highly sought after.
For Boston employers, finance and accounting staffing and recruiting efforts should actively seek out candidates who demonstrate these future-proof skills. Investing in upskilling current employees in these areas will also be critical for retaining top talent and maintaining a competitive edge.
Reshaping Recruitment: AI in Finance and Accounting Staffing
The impact of AI isn't limited to the finance department itself; it's also revolutionizing the finance and accounting recruiting process. Staffing agencies and internal HR teams in Boston are increasingly using AI to enhance effectiveness.
Forecasting Talent Needs: AI can analyze market trends, economic indicators, and internal business growth projections to help firms anticipate future hiring needs, allowing for proactive talent acquisition strategies rather than reactive ones.
Chatbots for Candidate Engagement: AI-powered chatbots can answer common candidate questions, schedule interviews, and provide updates, offering a seamless and efficient experience for job seekers.
Bias Reduction (with caution): While AI can introduce new biases if not carefully managed, when properly implemented, it can help reduce human bias in the initial screening process by focusing purely on skills and qualifications. However, continuous monitoring and ethical considerations are crucial.
For Boston-based finance and accounting staffing and recruiting firms, adopting these AI tools is crucial for staying ahead in a competitive market. It allows them to deliver more qualified candidates faster, ultimately providing greater value to their clients. The "global financial automation market is projected to grow at a compound annual growth rate (CAGR) of over 14.2% from 2024 to 2032," highlighting the rapid adoption of these technologies.
How Boston Firms Can Adapt to AI and Stay Ahead
To thrive in this evolving landscape, Boston employers and hiring managers need a proactive strategy
Redefine Job Descriptions: Re-evaluate existing finance and accounting roles. Update job descriptions to reflect the new emphasis on analytical, technological, and strategic skills. Clearly communicate the shift from transactional processing to value-added analysis.
Invest in Upskilling and Reskilling Programs: Look beyond external hiring. Identify current employees with potential and invest in training programs that build AI literacy, data analytics skills, and critical thinking. Partner with local educational institutions or offer internal workshops.
Embrace Hybrid Roles: The integration of AI means many roles will become hybrid, combining traditional finance responsibilities with technology-driven tasks. Foster an environment where professionals are comfortable with both aspects.
Partner with Forward-Thinking Staffing Agencies: Collaborate with finance and accounting staffing agencies in Boston, like DeWinter , that are already embracing AI in their recruitment processes. These partners will have a deeper understanding of the evolving skill sets and access to a future-ready talent pool.
Foster a Culture of Continuous Learning: Encourage curiosity and a growth mindset within your finance and accounting teams. Provide opportunities for experimentation with new technologies and celebrate learning from both successes and failures.
Focus on Soft Skills: While technical skills are vital, never underestimate the importance of soft skills like communication, collaboration, and adaptability. These are inherently human qualities that AI cannot replicate and will become even more valuable. The U.S. Bureau of Labor Statistics highlights "analytical and critical-thinking skills," "communication skills," and "organizational skills" as important qualities for accountants and auditors, emphasizing their continued relevance alongside technological proficiency.
Ethical AI Implementation: As you integrate AI into your hiring and financial operations, prioritize ethical considerations. Ensure fairness, transparency, and accountability in your AI systems, especially when handling sensitive data.
The future of finance and accounting staffing in Boston is deeply linked to the integration of AI technology. For employers and hiring managers, this evolution isn’t something to fear—it’s a powerful chance to build smarter, more strategic finance teams. By staying ahead of these changes, Boston firms can attract top-tier talent equipped to handle the complexities of today’s financial landscape and keep their competitive advantage on a global scale.
That’s where DeWinter comes in, a trusted local partner with deep expertise in finance, accounting, and technology recruiting. DeWinter is uniquely positioned to help your organization connect with the AI-ready professionals who will drive your success in this new era.
| 2025-06-07T00:00:00 |
https://www.dewintergroup.com/the-role-of-ai-in-finance-accounting-hiring-what-boston-companies-should-know
|
[
{
"date": "2025/06/07",
"position": 100,
"query": "job automation statistics"
}
] |
|
AI Job Displacement 2025: Which Jobs Are At Risk? - Final Round AI
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AI Job Displacement 2025: Which Jobs Are At Risk?
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https://www.finalroundai.com
|
[] |
AI has eliminated 77,999 jobs in 2025 alone. See which positions are disappearing fastest, backed by data from Microsoft, IBM, and Google ...
|
The AI job displacement crisis isn't coming. Whether you want to believe it or not, it's already here.
We've watched Microsoft axe 6,000 workers earlier this month. Yesterday, IBM laid off 8,000 more employees as AI agents took over their HR department. Tomorrow, it'll be your company's turn.
While executives talk about "workforce optimization" and "AI integration," the translation is simpler: your job is being automated away. The timeline isn't someday. It's this quarter. I don’t want to scare you with this, but…
The Numbers Don't Lie
So far in 2025, there have been 342 layoffs at tech companies with 77,999 people impacted. That's 491 people losing their jobs to AI every single day.
According to the World Economic Forum's 2025 Future of Jobs Report, 41% of employers worldwide intend to reduce their workforce in the next five years due to AI automation. But here's what the report didn't mention: they're not waiting five years.
The Current Reality:
Microsoft : 6,000 layoffs in May 2025, with software engineers making up over 40% of cuts
: 6,000 layoffs in May 2025, with software engineers making up over 40% of cuts IBM : 8,000 recent layoffs concentrated in HR, plus 9,000 more planned
: 8,000 recent layoffs concentrated in HR, plus 9,000 more planned Meta : 5% workforce reduction targeting "lowest-performing" staff
: 5% workforce reduction targeting "lowest-performing" staff Amazon: Cutting 100 roles in Devices division
Look, I've been covering tech layoffs for years, but this wave feels different. Companies aren't just cutting costs anymore. They're replacing entire job functions with software.
Entry Level Workers: You're First in Line
The AI job displacement data is brutal for new graduates. Research from SignalFire shows Big Tech companies reduced new graduate hiring by 25% in 2024 compared to 2023. These aren't just hiring slowdowns. These are positions that no longer exist.
Bloomberg research reveals AI could replace 53% of market research analyst tasks and 67% of sales representative tasks, while managerial roles face only 9 to 21% automation risk.
Anthropic CEO Dario Amodei's stark prediction: AI could eliminate half of all entry-level white-collar jobs within five years. Most workers won't recognize the danger until their jobs are gone.
The math is simple. Entry level work involves routine tasks. AI excels at routine tasks. Connect the dots.
Jobs Being Eliminated This Week
1. Software Engineers and Developers
Here's what's happening right now: Microsoft CEO Satya Nadella revealed that 30% of company code is now AI-written. Simultaneously, over 40% of their recent layoffs targeted software engineers.
The irony is staggering. Microsoft vice presidents are telling teams of 400 engineers to use AI for half their coding work. Those same engineers are being laid off months later.
2. Human Resources Staff
HR departments are getting hit hard by AI automation. Companies are discovering they can replace most HR workers with AI systems that work faster and cost less.
Most companies force the change overnight. They shut down:
HR phone lines
Email support
Walk-in help desks
Employees must use the AI system or get no help. At first, workers complain. But they adapt when they realize they get instant answers 24/7.
3. Content Writers and Copywriters
81.6% of digital marketers already fear AI will replace content writers, and that fear is becoming reality. Companies are discovering that "good enough" AI writing costs pennies compared to human salaries.
Writers who survive will need skills beyond basic writing - strategy, brand knowledge, and understanding audiences.
4. Customer Service Representatives
AI chatbots reduce telemarketing costs by 80%, making human customer service rapidly obsolete. When did you last speak to a human when calling customer support? Exactly.
5. Financial Analysts
AI can read thousands of financial reports in minutes. It spots trends and makes predictions faster than human analysts. Wall Street loves efficiency, so this change is happening fast.
MIT research shows AI will replace 2 million manufacturing workers by 2025. But finance jobs might disappear even faster because everything is data-based.
6. Data Entry and Administrative Roles
These repetitive task jobs are AI's easiest targets. IBM's AskHR handles 11.5 million interactions annually with minimal human oversight. Why would any company pay humans to do data entry when software does it faster and never takes sick days?
7. Market Research Analysts
AI analytics tools process market data faster and more accurately than humans, spotting trends and predicting behavior with superior precision. The days of humans manually analyzing market reports are ending.
8. Legal Research Staff
AI scans legal databases, identifies relevant statutes, and cross-references case history faster than human researchers. Law firms are discovering they can replace entire research teams with software subscriptions.
9. Medical Transcriptionists
AI speech recognition transcribes doctor-patient conversations with near-perfect accuracy, eliminating manual transcription needs. Why pay humans to type when AI listens and writes simultaneously?
10. Graphic Desingers and Visual creators
AI image tools like DALL-E and Midjourney can make complex designs in seconds. What used to take hours now takes moments. But the real game-changer is Google's new Veo 3.
Veo 3 can make complete videos with voices, music, and sound effects. Just type what you want and it creates professional-looking video clips. It costs $249 per month, which is less than hiring a video team for one project.
Basic design work like logos, social media posts, simple layouts - can now be automated faster than humans can work.
Industry Breakdown
Technology: 92% of IT jobs will be transformed by AI, hitting mid-level (40%) and entry-level (37%) positions hardest.
Retail: 65% of retail jobs face automation by 2025 due to technological advances and cost pressures.
Manufacturing: Up to 30% of jobs could be automatable by mid-2030s, with men more affected due to autonomous vehicles and machinery.
The Job Market Right Now
January 2025 saw the lowest job openings in professional services since 2013. That's a 20% year-over-year drop.
40% of white-collar job seekers in 2024 failed to secure interviews while High-paying positions ($96K+) hit decade-low hiring levels.
The government sees what's happening. The Department of Government Efficiency (DOGE), led by Elon Musk, launched in January 2025 with a mandate to eliminate federal jobs through AI optimization.
Even the government is automating jobs away.
The New Jobs (With a Catch)
While 170 million new roles emerge by 2030, there's a catch: 77% of AI jobs require master's degrees, and 18% require doctoral degrees.
Growing Fields:
AI and Machine Learning Specialists
AI Ethics Officers
AI Product Managers
Data Scientists
Human-AI Collaboration Experts
The new economy rewards those who can work with AI, not against it.
Skills That Keep You Employed
Critical Capabilities:
AI tool mastery and prompt engineering
Data analysis and interpretation
Creative problem-solving
Emotional intelligence
Strategic thinking
The Survival Rule: "AI won't take your job if you're the one best at using it"
Stop fighting AI. Start using it better than everyone else.
What You Need to Do Today
For Workers:
Master AI tools immediately. Learn ChatGPT, Claude, GitHub Copilot, and industry-specific AI tools. 120 million workers need retraining within three years. Don't be last in line.
Focus on human skills AI can't replicate: creativity, empathy, strategic thinking. Find roles combining human judgment with AI capabilities.
For Employers:
77% of employers plan worker upskilling while 41% plan workforce reductions.
Invest in retraining now. Companies plan to retrain 32% of workforces. Redesign roles to create human-AI hybrid positions. 51% of employers will move staff from dying roles to growing ones.
The smart money is on adaptation, not resistance.
The Reality Check
Companies are making AI replacement decisions right now, not in five years. While you're reading this article, 513 people lost their jobs to AI today.
By 2030, 70% of job skills will change. McKinsey projects 30% of work hours could be automated within this decade.
This isn't speculation anymore. It's quarterly earnings reports and SEC filings.
Bottom Line
AI job displacement isn't a future threat. It's this month's reality. The timeline isn't someday. It's this quarter. The companies aren't planning. They're executing.
The survival choice is binary: Master AI or become irrelevant. Adapt immediately or join the 76,440 people who've already lost jobs to AI automation this year.
The replacement began months ago. The question isn't whether AI will affect your job. It's whether you'll evolve fast enough to stay relevant.
The clock isn't ticking. It already rang.
| 2025-06-08T00:00:00 |
https://www.finalroundai.com/blog/ai-replacing-jobs-2025
|
[
{
"date": "2025/06/08",
"position": 69,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/08",
"position": 17,
"query": "AI layoffs"
},
{
"date": "2025/06/08",
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"query": "AI job losses"
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"query": "AI layoffs"
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"query": "AI layoffs"
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{
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"query": "AI job creation vs elimination"
},
{
"date": "2025/06/13",
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"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/13",
"position": 14,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/13",
"position": 73,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/13",
"position": 67,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/13",
"position": 7,
"query": "AI layoffs"
},
{
"date": "2025/06/13",
"position": 89,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/13",
"position": 66,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/13",
"position": 2,
"query": "automation job displacement"
},
{
"date": "2025/06/13",
"position": 10,
"query": "job automation statistics"
}
] |
|
AI compresses labor demand. Productivity gains don't protect ...
|
The heart of the internet
|
https://www.reddit.com
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[] |
AI massively increases individual productivity. If one person can now do the work of ten, companies don't keep all ten but instead they cut headcount and ...
|
Even if every white-collar worker starts using AI, it won’t save most of their jobs - it will still eliminate them.
AI massively increases individual productivity. If one person can now do the work of ten, companies don’t keep all ten but instead they cut headcount and expect more from fewer people.
This isn’t a distant future. It’s already happening. Roles in writing, marketing, sales, support, operations, even design and analysis - all are becoming faster, cheaper, and easier to automate or streamline.
And while many will use AI tools to speed up daily tasks, only a small group will master them: building systems, automating workflows, and delivering results that used to take entire teams. Those few will be rewarded. The rest will be seen as interchangeable.
So yes, widespread AI use may become the norm but it will still eliminate millions of white-collar jobs. The tools don’t equalize the workforce. They collapse it. This doesn’t mean this change is bad, but it does mean this change requires us to be proactive and build with it instead of fighting against it.
| 2025-06-08T00:00:00 |
https://www.reddit.com/r/Futurology/comments/1l6nkun/ai_compresses_labor_demand_productivity_gains/
|
[
{
"date": "2025/06/08",
"position": 26,
"query": "AI labor market trends"
},
{
"date": "2025/06/08",
"position": 31,
"query": "AI labor market trends"
}
] |
|
Reskilling and Upskilling in the AI-Driven Workplace - MyCVCreator
|
Reskilling and Upskilling in the AI-Driven Workplace
|
https://www.mycvcreator.com
|
[] |
The rise of generative AI and automation is reshaping jobs across sectors, creating both opportunities and risks. Globally, it is estimated ...
|
The rise of generative AI and automation is reshaping jobs across sectors, creating both opportunities and risks. Globally, it is estimated that roughly 23% of jobs will change in the next four years and 40% of work-hours are likely to be impacted by generative AI. At the same time, the World Economic Forum projects that by 2030 the net effect will be about 170 million new jobs created versus 92 million displaced. In short, the AI era promises more new roles (and higher-value work) than losses – but different skills will be required. Survey data show employees expect significant AI-driven change: many believe AI could automate about 30% of their tasks, and a sizeable minority (41%) feel apprehensive about it. Notably, workers often want training – McKinsey finds employees are eager to gain AI skills even more than their leaders realize. Together, these findings make clear why reskilling and upskilling are urgent. Organizations that invest in systematic retraining can help their people adapt to AI-powered tools and processes – gaining a competitive edge – while those that do not risk skills gaps and talent shortages.
Key Industries Transformed by AI
AI is affecting virtually every industry. Here are some examples of how major sectors are being reshaped and what it means for workforce skills:
Manufacturing: Manufacturers are adopting AI for quality control, predictive maintenance, and automation of assembly tasks. In fact, a Deloitte study reports that 87% of manufacturers have adopted or plan to adopt AI within two years. Yet there’s a training gap: only about 14% of frontline production workers report having received any AI upskilling (versus 44% of managers). To fill this gap, some firms are using cutting-edge training methods. A factory worker uses augmented-reality tools to learn new AI-driven tasks. For example, companies like UST employ metaverse and AR/VR simulations so workers can practice using AI tools in a safe, immersive environment. Workers might simulate a predictive-maintenance diagnosis or optimize a production line in virtual reality before doing it on the shop floor. Such programs allow hands-on learning of AI concepts (from IoT sensors to robotics) and have been shown to accelerate skills adoption and on-the-job performance. Offering flexible online courses and micro-training (often bundled into mobile apps or digital learning platforms) also helps manufacturing employees build AI literacy while on the job.
Healthcare: In healthcare, AI is powering everything from diagnostic imaging and drug discovery to patient triage and administrative workflows. Hospitals and health systems increasingly use machine-learning algorithms to analyze scans or patient data, while chatbots and virtual assistants handle routine inquiries. Surveyed health organizations say they plan to ramp up AI/ML adoption, and about 75% of leaders recommend upskilling current staff to succeed with these tools. In practice, this means clinicians and support staff need both digital skills (data literacy, basic programming) and new process knowledge (how to work with AI-driven devices or analytics). For example, health-information professionals are learning to use AI systems that sift through records and suggest coding or billing options. Training programs may include online courses on AI fundamentals for medical staff, or bootcamps in healthcare data science. As one expert put it, organizations must support employees in “developing the necessary skills and mindset to thrive amid rapid technological change”. In sum, upskilling in healthcare focuses on blending medical expertise with AI and digital skills, so that professionals can leverage AI to enhance patient care.
Financial Services: Banks and insurers are also racing to equip staff with AI capabilities. Many customer-facing finance tasks (like fraud detection, loan underwriting, and customer advice) are now AI-augmented. A recent study found that about 75% of the world’s 50 largest banks offer AI-specific training to employees. For instance, Bank of America has created an internal “Academy” to teach all employees basic AI concepts and even skills like prompt engineering for generative AI. This training helps tellers and bankers spot which parts of their jobs can be automated (e.g. data lookup, form filling) and which require human judgment. Other banks run “genAI hackathons” or pilot programs so teams can experiment safely. The goal is to build confidence: major banks reassure staff “they won’t be replaced by robots” and instead focus on how AI can boost productivity. Even smaller lenders follow suit: one fintech bank set a goal to save 2,000 staff-hours per month through AI tools, so it is training all employees to use those tools in daily work. The payoff is clear: firms that upskill their finance staff report better innovation and efficiency, as well as higher employee morale.
Logistics and Supply Chain: AI is revolutionizing logistics through route optimization, demand forecasting, warehouse robotics, and more. These changes require new skills in logistics roles. For example, line workers who once sorted packages are now trained to oversee autonomous robots and interpret AI-driven analytics. Consulting experts note that this shift “requires significant upskilling and reskilling” as workers move from manual roles into tech-focused specialties. Companies report that retraining supply-chain staff to use AI platforms (from smart-routing software to automated inventory systems) improves efficiency and creates new high-value roles. Successful strategies include cross-training warehouse staff on data analytics, and hiring data scientists to work alongside operations teams. As one analyst put it, organizations should invest heavily in employee development so their supply-chain professionals have the digital and analytical skills needed in a technology-driven industry.
Customer Service and Support: In customer service, chatbots and virtual assistants handle routine inquiries, pushing human agents into more complex tasks. This trend makes agent upskilling vital. A recent McKinsey survey found two-thirds of customer-care leaders consider upskilling and reskilling critical priorities in an AI-enabled future. Notably, about 21% of companies are already using AI-based tools to train and support their service staff. Effective programs do double duty: they teach employees to use AI (for example, tools that suggest knowledge-base articles or draft email responses) and help them retain empathy and problem-solving skills that AI lacks. One case study describes a construction-equipment firm that gave call-center reps a generative-AI assistant for technical support. The AI tool navigated thousands of documents and identified solutions in seconds, cutting call resolution time from over two hours to mere seconds. This shows how upskilling agents to harness AI can dramatically improve service levels while keeping human oversight on complex issues.
Strategies for Reskilling and Upskilling
To meet these challenges, organizations are experimenting with various training strategies. Common approaches include:
Edtech and institutional partnerships: Many firms partner with online learning platforms and universities to deliver scalable training. For example, AT&T’s $1 billion “Future Ready” program partnered with Coursera, Udacity, and leading universities to retrain 100,000 employees with cutting-edge tech skills. Similarly, tech companies often offer their own AI training: Google’s AI courses and IBM’s data-science certifications are made available to enterprise clients. By subsidizing subscriptions to platforms like LinkedIn Learning or Pluralsight, companies give workers anytime-access to AI and analytics courses. Governments also support such efforts: for instance, U.S. states offer grants or tax incentives to employers that train workers, and organizations can leverage tax credits (e.g. the Work Opportunity Tax Credit) when they invest in employee education.
Internal learning programs: Building in-house training and career pathways is another popular strategy. Large employers often create corporate academies or L&D centers. Bank of America’s in-house “Academy” (mentioned above) is one example. Other examples include apprenticeship models or rotational programs: an employee might spend part of the week learning a new AI-related skill on the job while still handling some of their old duties. Insurance firm Zurich, for instance, ran initiatives like its “Z.Lab” group training and a program for unemployed youth, and reports that 73.4% of job vacancies were filled internally thanks to its focus on continuous learning. In short, firms that prioritize hiring from within reduce talent gaps and raise retention. Companies also often bundle training with real projects – e.g. assigning “AI champions” to pilot projects so the learning is directly applied and employees can see ROI quickly.
Public-private initiatives and government incentives: Many governments and industry consortia promote workforce training. For example, the World Economic Forum’s “Reskilling Revolution” initiative has secured commitments from over 370 companies and multiple governments to reach millions of workers with training and job opportunities. Public funds are also being allocated: Canada’s 2024 budget set aside CAD$50 million to train workers in AI-impacted sectors, and earlier investments (over $48 million) have supported technology upskilling nationwide. In the U.S., agencies like the Department of Energy highlight “thousands of AI training and learning opportunities” through national labs and research programs. Tax policies can help too: employers can deduct training costs and in many regions receive subsidies or credits for workforce development. In short, savvy organizations tap both private and public resources – from grant programs to university partnerships – to amplify their reskilling efforts.
Challenges and Barriers
Even with strong programs, there are hurdles to overcome:
Worker resistance and culture: Employees may fear that AI threatens their jobs, or they may be skeptical about the value of training. One study notes that “some employees may resist upskilling and reskilling measures because they are skeptical about the value of training or … reluctant to learn new skills,” leading to “resistance to change and lower participation”. Overcoming this requires clear communication: emphasizing how new skills protect career relevance, and highlighting personal success stories. Leaders often need to invest in a growth mindset culture, using mentors or “AI champions” (often younger or more tech-savvy managers) to reassure colleagues that AI will augment rather than replace them.
Time and cost constraints: Training employees can be expensive and time-consuming. Pulling staff off their regular duties for courses incurs short-term costs (as one analysis points out, businesses must manage “time spent by employees learning new tools” against productivity). Organizations must budget for courses, instructors, and maybe external certifications, on top of lost labor hours. Tight margins can make this a tough sell. To mitigate this, many firms start with small pilots (e.g. training one team first) to prove ROI before scaling. Blended learning (mixing on-the-job training with online modules) can also reduce downtime.
Skills mismatch and motivation: If training programs are not well aligned to actual job needs, employees may become disengaged. For example, teaching a generic AI course without connecting it to real work tasks can make staff feel it’s irrelevant. Research warns that if “the skills that workers are learning do not align with the needs of the organization,” upskilling efforts can be counterproductive. Careful planning is essential: learning objectives should be tied to clear outcomes (e.g. “how this new data-analysis skill will help your department”), and progress metrics (completion rates, new project pilots) should be tracked.
Digital divide and access: Not all workers have equal access to training resources. A lack of reliable internet or computing equipment can be a barrier, especially for lower-income or rural employees. Older workers may also struggle with digital tools. Studies highlight a significant digital divide (by gender, age, or socio-economic status) that can “negatively affect reskilling” efforts. Companies must address this by providing hardware, scheduling in-person or offline training as needed, and offering extra support for those less familiar with tech. Promoting a culture where any question is welcome (reducing stigma around skill gaps) can help ensure no one is left behind.
Recommendations
To succeed in the AI era, both organizations and individuals should adopt a proactive, collaborative approach:
For organizations: Treat reskilling/upskilling as a strategic priority, not an afterthought. McKinsey advises starting “with business outcomes and how generative AI investments can enable or accelerate them”, then identifying which skills are needed to deliver those outcomes. In practice, this means involving business leaders in defining skill goals and embedding learning into workflows. Leadership should also emphasize the human side – addressing fears and rewarding learning. For example, companies can publicize promotions or role-changes that came from training, or build AI projects into performance reviews. Executives should allocate dedicated budgets for training (even setting targets, as some Fortune 50 companies do by earmarking ~1–2% of payroll for L&D). They should leverage partnerships (with edtech, universities, or government programs) to expand reach and share costs. Companies also need to measure and iterate: track metrics like training participation, skill assessments, and subsequent productivity gains to refine programs. In sum, a culture of continuous learning is key – leaders must reframe AI as a tool for empowerment. As one McKinsey article puts it, organizations should take “a human-centered approach” to L&D, transforming initial fear into curiosity and a mindset of opportunity.
For individuals: Embrace lifelong learning. Workers should seek out both company-offered and external training opportunities to build AI and data skills. This could include online courses, certifications, workshops or even self-study using AI tools. Focus on complementary strengths: for example, develop critical thinking, creativity, communication and problem-solving skills that AI cannot easily replicate. Learning how to use AI tools (like prompt-writing for chatbots, or basic data analytics) is practical and will soon be expected in many roles. Employees should also stay informed about their industry’s AI trends and be ready to pivot to new roles or tasks. Networking with peers (e.g. internal tech champions, or industry learning communities) can provide support. Ultimately, individuals who are adaptable and eager to reskill will find themselves in high demand.
Across industries and roles, the message is clear: change is coming, and preparation is voluntary. Those who act now to build skills — by partnering with educational programs, fostering an AI-positive culture, and leveraging available incentives — will position themselves to thrive in the AI-driven future. By prioritizing strategic training, companies can turn a disruptive technology into a source of innovation and growth. Workers who stay curious and keep learning will ensure that AI becomes a powerful partner, not a threat, in their careers.
| 2025-06-08T00:00:00 |
https://www.mycvcreator.com/blog/reskilling-and-upskilling-in-the-ai-driven-workplace
|
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What Is an AI Employee? A Guide to the 2025 Digital Workforce | Lindy
|
What Is an AI Employee? A Guide to the 2025 Digital Workforce
|
https://www.lindy.ai
|
[
"Flo Crivello",
"Lindy Drope",
"Written By",
"Founding Gtm At Lindy",
"Reviewed By",
"Last Updated",
"June",
"Expert Verified",
"About The Editorial Team",
"Founder"
] |
AI employees are advanced digital systems designed to perform tasks autonomously, boosting efficiency and collaboration in workplaces.
|
As we enter 2025, AI employees are no longer a futuristic fantasy; they're rapidly becoming key members of high-performing teams. These intelligent digital workers use large language models and advanced tech to automate tasks, enhance collaboration, and help make decisions.
In this article, you'll learn:
What AI employees are and how they differ from traditional bots
Core functionalities and use cases
How Lindy helps businesses integrate AI employees
What is an AI employee?
AI employees are advanced digital systems designed to perform tasks autonomously, boosting efficiency and collaboration in workplaces.
Unlike traditional bots that follow simple rules, AI employees are adaptable and capable of human-like decision-making. They can understand your business needs and even adapt to changing goals.
This is because AI employees leverage machine learning and processing to "think" and offer innovative solutions.
Are AI agents and AI employees the same?
Yes, AI agents and AI employees are essentially the same thing. They both refer to these digital helpers powered by artificial intelligence.
For example, Lindy is a leader in creating intelligent and scalable AI workforce solutions. Our AI digital workers (which we call “Lindies”) don't just use one kind of artificial intelligence to get the job done.
They combine generative AI (designed to generate new content or data) with large language models or LLMs (designed to understand, create, and work with human language). This means that Lindy's AI employees can do far more than just generate language.
What industries can benefit most from AI employees?
AI employees can be valuable assets in various industries, but some sectors can particularly benefit from their unique capabilities.
Here are a few examples:
Healthcare: Imagine AI employees helping doctors and nurses with administrative tasks, like scheduling appointments, managing medical records, and even assisting with diagnoses. This frees up healthcare professionals to focus on patient care.
Imagine AI employees helping doctors and nurses with administrative tasks, like scheduling appointments, managing medical records, and even assisting with diagnoses. This frees up healthcare professionals to focus on patient care. Finance: In the fast-paced world of finance, AI employees can analyze market trends, manage risk, and even detect fraud. They can also assist with customer service, providing quick and accurate responses to inquiries.
In the fast-paced world of finance, AI employees can analyze market trends, manage risk, and even detect fraud. They can also assist with customer service, providing quick and accurate responses to inquiries. Customer service: AI employees can provide 24/7 customer support, answering questions, resolving issues, and even offering personalized recommendations. This can lead to happier customers and higher sales.
AI employees can provide 24/7 customer support, answering questions, resolving issues, and even offering personalized recommendations. This can lead to happier customers and higher sales. Logistics: From managing inventory to optimizing delivery routes, AI employees can help businesses simplify their supply chains and make them as efficient as they can be.
Our AI employees can be easily integrated into existing workflows and systems, and they can be trained to perform a wide range of tasks. This makes them a valuable asset for businesses of all sizes.
4 ways that AI employees operate
So far, we’ve talked about what AI employees are and where they’re most useful. Now, let's explore the key operational aspects of these digital dynamos:
1. Delegating tasks with ease
AI employees take on routine tasks like data entry, scheduling, and email responses, reducing the manual workload for your team. But don't worry, they're not here to take over the world (yet!).
Complex tasks that require human judgment, like decision-making or strategizing, are escalated to human counterparts. This guarantees that critical decisions are guided by human expertise, while AI employees handle the day-to-day grind.
2. Integrating with existing workflows
AI employees integrate directly with your existing tools, systems, and workflows to boost operational efficiency without disruption. It's like adding a new team member who already knows the ropes from the get-go.
Lindy, for instance, offers plug-and-play deployment — you can use pre-existing Lindies or create your own from scratch. We make sure businesses can see immediate benefits without technical barriers.
3. Collaborating with human teams
Think of AI employees as the Robin to your Batman. Lindies are designed for human-in-the-loop collaboration, where humans provide oversight and feedback to fine-tune processes.
They can take team productivity through the roof by working alongside human employees, allowing them to focus on strategic priorities. It's a win-win situation for everyone.
4. Deployment without the hassle
Forget about lengthy onboarding processes. With Lindy's low-code platform, businesses can deploy AI employees quickly and customize workflows without having to be a technical wiz.
The best part? AI employees are operational within minutes, making the transition to an AI-first workforce swift and easy.
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Core features of AI employees
Let's now dive into the core features that make these AI employees so remarkable:
Automation and accuracy experts
AI employees can tackle time-consuming tasks such as data processing, document handling, and report generation with lightning speed.
They're also sticklers for accuracy, reducing human errors, and improving consistency in task execution. Think of them as your team's secret weapon against inefficiency and inconsistency.
Multifunctionality across roles
AI employees are capable of handling various tasks in customer service, HR, finance, and more. Lindies are designed to be cross-functional, supporting teams across different departments.
They're like the ultimate utility players ready to step in and assist wherever needed and you’re the coach — ready to pull them from the bench and tell them, “Go score that 3-pointer.”
24/7 availability
AI employees operate 24/7 without fatigue, providing constant support for business operations. If we had to throw another analogy into the mix, we’d say they're like the Energizer Bunnies of the workforce, always ready to tackle the next task.
But that’s not all. They can also handle high volumes of tasks simultaneously, scaling with your business needs.
Human-like interaction
Natural language processing enables AI employees to communicate with customers and team members effectively. They can understand and respond to context, guaranteeing accurate and relevant interactions.
Use cases of AI employees
AI employees are versatile and can be applied in various scenarios to take your business operations to the next level.
Let's explore some of the most common use cases:
Customer support
AI employees can manage inquiries, resolve issues, and shorten response times. They can provide 24/7 support, guaranteeing that customers always have access to assistance.
Lindy's AI employees can be integrated with various platforms, such as Slack, or email to make a Support Ticket Dispatcher. You can then personalize customer service at scale. This allows human agents to focus on more complex issues while AI employees handle routine inquiries.
HR and recruitment
AI employees can streamline HR and recruitment processes, including onboarding, interview scheduling, and payroll processing. They can also help reduce bias in recruitment decisions by objectively evaluating candidates based on their qualifications.
Lindy's AI employees can assist with various HR tasks, such as screening resumes, scheduling interviews, and generating performance reviews.
Data analysis and reporting
AI employees can aggregate data, generate reports, and provide actionable insights. They can analyze large datasets to identify trends and patterns that may not be apparent to humans.
Lindy can integrate with all your favorite sales tools like Salesforce to get more insights from the data you’re collecting. They can also automate report generation, freeing up human analysts to focus on broader strategic tasks.
How Lindy overcomes AI challenges
Implementing AI employees may seem daunting. Fortunately, Lindy is here to make the process as smooth as it can be. We address common challenges head-on.
Let’s take a closer look at some common AI concerns and how Lindy helps:
Tackling initial implementation hurdles
Many businesses perceive AI deployment as complex and costly. This perception stems from the technical expertise often required to integrate AI into existing workflows. It also comes from the fact that AI is closely associated with hefty upfront investments.
How Lindy solves it: Lindy offers user-friendly onboarding and a complete Academy with tutorials on how to set up different types of AI employees in minutes. Or you can use one of the pre-made AI employees.
Providing data privacy and remaining compliant
If you’ve been following AI’s evolution closely, you’ll know that there are lots of concerns about the ethical use of AI and its handling of sensitive data.
The truth is that businesses need assurance that their data is secure and compliant with industry regulations. This is especially true given the increasing prevalence of data breaches and the possibility of regulatory penalties.
How Lindy solves it: Lindy prioritizes data privacy and compliance. We employ robust security measures and adhere to compliance standards like SOC 2, HIPAA, and AES-256 encryption. Your data is encrypted both at rest and in transit, securing its confidentiality and integrity.
Overcoming employee resistance
Fear of job displacement or a lack of understanding of AI roles can create resistance among employees. It's important to foster a culture of collaboration between human and AI workers to alleviate concerns and confirm a smooth integration of AI into the workforce.
How Lindy solves it: Lindy’s Academy and educational resources help teams embrace AI as a collaborative tool. Once employees learn to build their own Lindies and see how they can work alongside AI they’ll worry less about them taking their promotion!
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FAQs about AI employees
How do AI employees differ from bots?
AI employees are more adaptable and capable of human-like decision-making than traditional bots. Unlike bots that follow simple rules, AI employees can adapt to changing goals or understand more context to make a more accurate decision.
Are AI employees expensive to implement?
The short answer is they don’t have to be. The cost of implementing AI employees can vary depending on the complexity and scale of the project. Low-code platforms like Lindy make it easier and more affordable for businesses to deploy AI employees.
Can AI employees make decisions on their own?
AI employees can make decisions based on the data and algorithms they are trained on. However, they are typically designed to escalate complex decisions to human counterparts. For instance, Lindy's AI employees are designed for human-in-the-loop collaboration, where humans provide oversight and feedback to fine-tune processes.
How secure is the data handled by AI employees?
Data security is a top priority for AI employee developers. Lindy, for instance, employs robust security measures and adheres to compliance standards like SOC 2, HIPAA, and AES-256 encryption to protect sensitive data.
Will AI employees replace human employees?
AI employees are designed to support and augment human capabilities. They handle repetitive and time-consuming tasks, freeing up human employees to focus on more strategic and creative work.
For instance, Lindy's AI employees are designed to collaborate with human teams — so no I, Robot-levels of sentience, fortunately!
Next step: Choosing Lindy for your AI employees
Lindies are designed to integrate with your team’s tools, boost productivity, and transform your business operations.
Here's how Lindy's AI employees can improve your workplace operations with zero hassle:
Effortless automation: Lindy's AI employees automate repetitive processes, freeing up your human team to focus on high-level strategizing and creative problem-solving.
Lindy's AI employees automate repetitive processes, freeing up your human team to focus on high-level strategizing and creative problem-solving. Human-like interaction: Our AI employees communicate effectively with your team and customers, understanding context and responding accurately.
Our AI employees communicate effectively with your team and customers, understanding context and responding accurately. 24/7 availability: Never miss a beat. Lindy's AI employees work around the clock, providing constant support and making sure your business operations run smoothly, even during peak hours.
Never miss a beat. Lindy's AI employees work around the clock, providing constant support and making sure your business operations run smoothly, even during peak hours. Cross-functional expertise: From customer service to HR and finance, Lindy's AI employees are multi-talented and can assist teams across various departments. Check out our full list of integrations to learn more.
From customer service to HR and finance, Lindy's AI employees are multi-talented and can assist teams across various departments. Check out our full list of integrations to learn more. Societies of Lindies: Create a network of AI employees that can delegate tasks to other AI employees to collaborate This allows for efficient task distribution and completion, maximizing productivity and efficiency.
Create a network of AI employees that can delegate tasks to other AI employees to collaborate This allows for efficient task distribution and completion, maximizing productivity and efficiency. Swift deployment: Get your AI employees up and running in no time. Lindy's low-code platform provides quick and easy deployment, even without extensive technical expertise.
Ready to experience the future of work today? Try Lindy's AI employees for free.
| 2025-06-08T00:00:00 |
https://www.lindy.ai/blog/ai-employee
|
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|
Reskilling and Upskilling for AI in the Workplace - MyCVCreator
|
Reskilling and Upskilling for AI in the Workplace: Why It Matters and How to Get Started
|
https://www.mycvcreator.com
|
[] |
The rise of Artificial Intelligence (AI) is transforming the modern workplace at lightning speed. From automating repetitive tasks to ...
|
The rise of Artificial Intelligence (AI) is transforming the modern workplace at lightning speed. From automating repetitive tasks to enhancing decision-making with predictive analytics, AI is now embedded across nearly every industry — healthcare, finance, education, manufacturing, and beyond. While this evolution brings immense opportunities, it also poses a challenge: how do professionals stay relevant in a workforce increasingly shaped by AI?
The answer lies in reskilling and upskilling.
What is Reskilling vs. Upskilling?
Reskilling refers to learning new skills to transition into a different job or industry. For instance, a customer service representative might reskill to become a data analyst.
Upskilling means enhancing your current abilities to stay competitive in your existing role. For example, a marketing specialist might upskill by learning how to use AI-driven analytics tools.
Both strategies are essential in a future of work that is dynamic, digital, and data-driven.
Why AI Demands New Skills in the Workplace
1. AI is Replacing Routine Tasks
AI-powered automation is increasingly taking over repetitive, rule-based activities — from data entry and scheduling to customer queries. Employees who rely heavily on these tasks must pivot to value-driven roles requiring creativity, strategy, and emotional intelligence.
2. Human-AI Collaboration is the New Norm
Rather than replacing humans entirely, AI is becoming a co-pilot in many roles. This shift demands digital literacy, AI fluency, and adaptability — skills that most traditional education paths haven’t focused on until recently.
3. The Talent Gap is Growing
According to the World Economic Forum, 50% of all employees will need reskilling by 2025. Organizations now view employee learning not as a perk but as a critical investment in sustainability and innovation.
Key Skills Needed for the AI Era
While technical skills are valuable, soft skills remain indispensable. Here’s a breakdown of what professionals should focus on:
Technical Skills
Data literacy : Understanding how data is collected, cleaned, and interpreted
AI and machine learning basics : Even non-tech roles can benefit from foundational knowledge
Coding and automation tools : Languages like Python or tools like Power Automate
Cybersecurity awareness: Essential as digital processes increase
Human-Centric Skills
Critical thinking and problem solving
Emotional intelligence
Communication and collaboration
Adaptability and growth mindset
How to Start Reskilling or Upskilling for AI
1. Evaluate Your Current Skill Set
Start by identifying the gaps between your current role and the direction your industry is heading. Tools like AI-readiness assessments or LinkedIn’s skill analysis can help.
2. Set a Learning Path
Choose between reskilling (for a career shift) or upskilling (to advance in your current path). Then select a specific domain of AI or tech — e.g., automation, data analysis, prompt engineering, etc.
3. Leverage Learning Platforms
There’s no shortage of affordable (even free) resources:
Coursera, edX, and Udemy
Google’s AI and machine learning courses
Microsoft Learn and IBM SkillsBuild
4. Practice Through Projects
Apply your learning in real-world scenarios. For example, use ChatGPT to streamline daily reports or create a chatbot for customer service. Portfolio-based evidence is increasingly as valuable as certificates.
5. Network and Collaborate
Join AI communities, attend webinars, and collaborate on open-source or internal projects. Learning through peer interaction often accelerates growth.
For Employers: Investing in Employee AI Readiness
Forward-thinking organizations should build a culture of continuous learning:
Offer on-the-job training
Create internal bootcamps and certifications
Recognize and reward learning milestones
Provide time during work hours for skill development
Companies that invest in AI upskilling are more agile and better prepared to harness innovation.
Final Thoughts
AI is not here to replace us — it’s here to redefine how we work. Those who embrace reskilling and upskilling today are the leaders, creators, and problem-solvers of tomorrow. Whether you're a seasoned executive or just starting your career, investing in AI-driven capabilities isn’t optional anymore — it’s essential.
The future belongs to the adaptable.
| 2025-06-08T00:00:00 |
https://www.mycvcreator.com/blog/reskilling-and-upskilling-for-ai-in-the-workplace-why-it-matters-and-how-to-get-started
|
[
{
"date": "2025/06/08",
"position": 96,
"query": "reskilling AI automation"
},
{
"date": "2025/06/08",
"position": 97,
"query": "reskilling AI automation"
},
{
"date": "2025/06/08",
"position": 87,
"query": "reskilling AI automation"
},
{
"date": "2025/06/08",
"position": 88,
"query": "reskilling AI automation"
},
{
"date": "2025/06/08",
"position": 84,
"query": "reskilling AI automation"
}
] |
|
Artists who got almost $1,500 a month under a basic income pilot ...
|
Artists who got almost $1,500 a month under a basic income pilot say their work improved
|
https://www.aol.com
|
[
"Aol Staff",
"Lauren Edmonds",
"June",
"At Pm"
] |
New developments in AI are reshaping the job market, replacing some entry-level positions. Tech industry leaders like Elon Musk and OpenAI CEO ...
|
A basic income program for the arts in Ireland ends in August after three years. Brian Lawless - PA Images/PA Images via Getty Images
Ireland's basic income pilot program for the arts ends in August.
For three years, 2,000 artists and creative arts workers received about $370 a week.
Recipients said the stipend overall improved their daily lives.
For about 2,000 artists and creative arts workers in Ireland, a weekly stipend provided through a basic income program has been a lifeline for years.
Now, it's almost over.
The pilot program began in 2022 under Catherine Martin, Ireland's former minister for tourism and culture. Martin allocated about $28 million to the arts sector following the COVID-19 pandemic.
Participants were randomly chosen and given an unconditional stipend of €325, or about $370, weekly for three years. During that time, participants met periodically via Zoom to discuss how the additional income had affected their livelihoods, careers, and ability to meet basic needs.
The final session was held this month before the program's conclusion in August.
Artists and cultural workers who attended the session grappled with what their lives would look like after August, but they hoped government officials would extend the program.
"We need no further pilots. People need a UBI now to face and deal with the many social, economic, and ecological crises of our world," Reinhard Huss, the organizer of UBI Lab Leeds, which sponsored the event alongside Basic Income Ireland, UBI Lab Arts, and UBI Lab Network, told Business Insider.
New developments in AI are reshaping the job market, replacing some entry-level positions. Tech industry leaders like Elon Musk and OpenAI CEO Sam Altman have said implementing a universal basic income will be essential in the near future when AI supplants jobs in most industries.
A universal basic income offers an entire population recurring, unconditional payments regardless of an individual's socioeconomic status. Ireland's program, like many others in the United States, is a guaranteed basic income, which targets certain segments of the population for a set period of time.
Impact of Ireland's basic income program for artists
Jenny Dagg, a sociologist lecturing at Ireland's Maynooth University, authored a new report that provides insights into participants' reactions to the program. She gathered data from over 50 of the 2,000 recipients.
Although the report outlined nearly a dozen key impacts reported by program recipients, Dagg highlighted five major takeaways during the Zoom session.
Dagg said that recipients who received money from the program reported more stability and "significantly reduced" financial stress. It relieved their anxiety about fulfilling their basic needs.
Participating in the pilot program also allowed artists to re-prioritize how they spend their time and what they choose to focus on. "The opportunity to focus more on their specific creative interests opened new possibilities and career trajectories," the report said.
Artists said the added income allowed them to spend more time "researching, experimenting, taking risks, and failing," which has improved the quality of their work.
Artists, the report said, also felt more confident in themselves and their work during the program. "Many recipients talk of feeling empowered, of being in control of the choices within their lives, and envisioning a viable career path longer-term," the report said.
Recipients even reported better mental health, which led to improved sleep quality and lowered stress levels.
What's next for Ireland's basic income program
With the end of the program fast approaching, recipients of the weekly payment are reckoning with what how their lives might change.
"Across art forms, recipients report concerns about financial stability and sustaining the momentum of their careers when, or if, the basic income scheme ends," Dagg's report said.
This month, Basic Income Ireland called on the government to immediately implement a universal and unconditional basic income for the country. A spokesperson for the UBI Lab Network said the pilot program's success shows that basic income is a viable option. The campaign group shared a proposal for introducing a universal basic income to Ireland.
"As the pilot shows, basic income works and people need a UBI now to face and deal with the many social, economic, and ecological crises of our world. The Network will continue to help demonstrate basic income within communities and show how it is a sustainable policy," the statement said.
Patrick O'Donovan, Ireland's minister for arts and culture, said he would evaluate the data collected throughout the pilot program and create proposals for the government regarding the next steps.
"I am heartened by the responses of the Basic Income recipients in this paper," O'Donovan said in the May report. "This research will add to the evaluation being conducted by my department, which to date clearly shows that the Basic Income Pilot has been an effective support for the artists in receipt of it."
Read the original article on Business Insider
| 2025-06-08T00:00:00 |
https://www.aol.com/news/artists-got-almost-1-500-205113800.html
|
[
{
"date": "2025/06/08",
"position": 79,
"query": "universal basic income AI"
},
{
"date": "2025/06/08",
"position": 79,
"query": "universal basic income AI"
}
] |
|
Is Ai taking jobs not going to decimate the economy? : r/AskEconomics
|
The heart of the internet
|
https://www.reddit.com
|
[] |
Ai replaces a huge amount of the labour force, saving money for big buisnesses, increasing profit margin. Subsequently, people who were laid off ...
|
This might sound like a pretty stupid question, but here's my general thought process. Ai replaces a huge amount of the labour force, saving money for big buisnesses, increasing profit margin. Subsequently, people who were laid off, ie the general population, have less moeny to spend. Since they have less money to spend, less items are being bought. The companies employing these ai strategies then get less revenue, since people have no money to spend. Kind of like how brands like trojan prevent sales from future customers by selling their product. I'm very curious as to how this seems to be of no concern to anyone.
| 2025-06-08T00:00:00 |
https://www.reddit.com/r/AskEconomics/comments/1l60f49/is_ai_taking_jobs_not_going_to_decimate_the/
|
[
{
"date": "2025/06/08",
"position": 33,
"query": "AI economic disruption"
},
{
"date": "2025/06/08",
"position": 34,
"query": "AI economic disruption"
}
] |
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