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A comprehensive list of 2025 tech layoffs \| TechCrunch	A comprehensive list of 2025 tech layoffs	https://techcrunch.com	[ "Cody Corrall", "Alyssa Stringer", "Kate Park", "Audience Development Manager", "Reporter", "Anthony Ha", "Maxwell Zeff", "Jagmeet Singh", "Sarah Perez", "--C-Author-Card-Image-Size Align-Items Center Display Flex Gap Var" ]	Will cut 22 jobs, affecting nearly a quarter of its total workforce, following the announcement of the AI startup's strategic partnership with ...	The tech layoff wave is still kicking in 2025. Last year saw more than 150,000 job cuts across 549 companies, according to independent layoffs tracker Layoffs.fyi. So far this year, more than 22,000 workers have been the victim of reductions across the tech industry, with a staggering 16,084 cuts taking place in February alone. We’re tracking layoffs in the tech industry in 2025 so you can see the trajectory of the cutbacks and understand the impact on innovation across all types of companies. As businesses continue to embrace AI and automation, this tracker serves as a reminder of the human impact of layoffs — and what could be at stake with increased innovation. Below you’ll find a comprehensive list of all the known tech layoffs that have occurred in 2025, which will be updated regularly. If you have a tip on a layoff, contact us here. If you prefer to remain anonymous, you can contact us here. June Rivian Has reduced its headcount by approximately 140 employees, accounting for roughly 1% of its total workforce. The recent layoffs mostly affected Rivian’s manufacturing team. Bumble Announced in an SEC filing that it will cut approximately 240 jobs, or 30% of its workforce, to enhance operational efficiency and allocate the resulting savings to the development of new products and technologies, according to a CNBC report. The layoff will help the online dating app save $40 million annually, per the report. Klue Has reportedly laid off 85 employees, which accounts for approximately 40% of its workforce. The Vancouver-based startup sells software products that use artificial intelligence for business intelligence. It helps sales professionals at tech companies gather information on competitors to improve their sales. Techcrunch event Save up to $475 on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Save $450 on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Boston, MA \| REGISTER NOW Google Has downsized its smart TV division by 25% of its 300-member team to adjust its strategy, per reports. Funding for the smart TV division, including Google TV and Android TV, has been cut by 10%, but investment in AI projects has been raised. Intel Says that it plans to lay off 15% to 20% of workers in its Intel Foundry division starting in July. Intel Foundry designs, manufactures, and packages semiconductors for external clients. Intel’s total workforce was 108,900 people as of December 2024, according to the company’s annual regulatory filing. It also confirmed to TechCrunch that it plans to wind down its auto business. Playtika Announced that it is letting go of around 90 employees, with 40 in Israel and 50 in Poland. The most recent round of job cuts comes after the Israel-based gaming company laid off 50 employees a few weeks ago. Airtime Has let go of around 25 employees from the 58-person team, the company confirmed to TechCrunch. Evernote’s founder Phil Libin launched the video startup in 2020, offering Airtime Creator and Airtime Camera. Microsoft Is laying off more employees, just a few weeks after announcing a job cut of over 6,500 in May, which was around 3% of its global workforce. The most recent layoffs affected software engineers, product managers, technical program managers, marketers, and legal counsels. May Hims & Hers Plans to downsize its workforce by letting go of 68 employees, approximately 4% of its total staff, per Reuters. The San Francisco telehealth platform said that its layoffs were unrelated to a U.S. ban on producing large quantities of the weight-loss drug Wegovy. The startup said it intends to keep on recruiting employees who fit in with its long-term expansion plans. Amazon Is reportedly laying off around 100 employees from its devices and services division, which encompasses various businesses like the Alexa voice assistant, Echo smart speakers, Ring video doorbells, and Zoox robotaxis. The company has reduced its workforce by approximately 27,000 since the start of 2022 to cut costs. Microsoft Will cut over 6,500 jobs, affecting 3% of its worldwide workforce. As of June, the Seattle-headquartered company had a total of 228,000 employees globally. It would be one of the company’s biggest layoffs since it cut 10,000 employees in 2023. Chegg Reportedly plans to let go of 248 employees, or about 22% of its workforce, to reduce expenses and improve efficiency, it said. The San Francisco-based edtech startup, which offers textbook rentals and tutoring services, has seen a drop in web traffic for months as students opt for AI tools instead of traditional edtech platforms. Match Is reducing its workforce by 13% as part of a reorganization that aims to reduce costs, shore up margins, and streamline its organizational structure. CrowdStrike Is laying off 5% of its global workforce, or around 500 people. The company said the layoffs were part of “a strategic plan (the ‘Plan’) to evolve its operations to yield greater efficiencies as the Company continues to scale its business with focus and discipline to meet its goal of $10 billion in ending [Annual Recurring Revenue]” in its 8-K filing. General Fusion Has cut roughly 25% of its current workforce. The Vancouver-based company, which is developing a technology to generate fusion energy, has raised $440 million from investors, including Jeff Bezos, Temasek, and BDC Capital. Deep Instinct Reduced its headcount by 20 employees, accounting for 10% of its total workforce. In April 2023, the Israeli cybersecurity startup had previously laid off a similar number of employees during a round of layoffs. Beam Has shut down its operations months after announcing major expansion plans, per Sifted. The British climate startup has let go of approximately 200 employees, according to a LinkedIn post by James Reynolds, the head of talent. April NetApp Is reportedly eliminating 700 jobs, affecting 6% of its total workforce, as it reorganizes for its operational efficiency. The company, based in San Francisco, provides data storage, cloud services, and CloudOps solutions for businesses. Electronic Arts Is reportedly letting go of approximately 300 to 400 employees, including around 100 at Respawn Entertainment, to focus on its “long-term strategic priorities,” according to Bloomberg. Expedia Is laying off around 3% of its employees as part of its restructuring. The job cuts will mainly affect midlevel positions in the product and technology teams. The latest round of layoffs comes after the company let go of hundreds of employees from its marketing team globally in early March. Cars24 Has reduced its workforce by about 200 employees in its product and technology divisions as part of a restructuring measure. The India-based e-commerce platform for pre-owned vehicles provides a range of services like buying and selling pre-owned cars, financing, insurance, driver-on-demand, and more. In 2023, the SoftBank-backed startup raised $450 million at a valuation of $3.3 billion. Is letting go of over 100 employees in its Reality Labs division, which manages virtual reality and wearable technology, according to The Verge. The job cuts affect employees developing VR experiences for Meta’s Quest headsets and staff working on hardware operations to streamline similar work between the two teams. Intel Announced its plan to lay off more than 21,000 employees, or roughly 20% of its workforce, in April. The move comes ahead of Intel’s Q1 earnings call helmed by recently appointed CEO Lip-Bu Tan, who took over from longtime chief Pat Gelsinger last year. GM Is laying off 200 people at its Factory Zero in Detroit and Hamtramck facility in Michigan, which produces GM’s electric vehicles. The cuts come amid the EV slowdown and is not caused by tariffs, according to a report. Zopper Has reportedly let go of around 100 employees since the start of 2025. Earlier this week, about 50 employees from the tech and product teams were let go in the latest round of job cuts. The India-based insurtech startup has raised a total of $125 million to date. Turo Will reduce its workforce by 150 positions following its decision not to proceed with its IPO, per Bloomberg. The San Francisco-based car rental startup, which had about 1,000 staff in 2024, said the layoffs will bolster its long-term growth plans during economic uncertainty. GupShup Laid off roughly 200 employees to improve efficiency and profitability. It’s the startup’s second round of layoffs in five months, following the job cuts of around 300 employees in December. The conversational AI company, backed by Tiger Global and Fidelity, was last valued at $1.4 billion in 2021. The startup is based in San Francisco and operates in India. Forto Has reportedly eliminated 200 jobs, affecting around one-third of its employees. The German logistics startup reduced a significant number of sales staff. Wicresoft Will stop its operations in China, affecting around 2,000 employees. The move came after Microsoft decided to end outsourcing after-sales support to Wicresoft amid increasing trade tensions. Wicresoft, Microsoft’s first joint venture in China, was founded in 2022 and operates in the U.S., Europe, and Japan. It has over 10,000 employees. Five9 Plans to cut 123 jobs, affecting about 4% of its workforce, according to a report by MarketWatch. The software company prioritizes key strategic areas like artificial intelligence for profitable growth. Google Has laid off hundreds of employees in its platforms and devices division, which covers Android, Pixel phones, the Chrome browser, and more, according to The Information. Microsoft Is contemplating additional layoffs that could happen by May, Business Insider reported, citing anonymous sources. The company is said to be discussing reducing the number of middle managers and non-coders in a bid to increase the ratio of programmers to product managers. Automattic The WordPress.com developer is laying off 16% of its workforce across departments. Before the layoffs, the company’s website showed it had 1,744 employees, so more than 270 staff may have been laid off. Canva Has let go of 10 to 12 technical writers approximately nine months after telling its employees to use generative AI tools wherever possible. The company, which had around 5,500 staff in 2024, was valued at $26 billion after a secondary stock sale in 2024. March Northvolt Has laid off 2,800 employees, affecting 62% of its total staff. The layoffs come weeks after the embattled Swedish battery maker filed for bankruptcy. Block Let go of 931 employees, around 8% of its workforce, as part of a reorganization, according to an internal email seen by TechCrunch. Jack Dorsey, the co-founder and CEO of the fintech company, wrote in the email that the layoffs were not for financial reasons or to replace workers with AI. Brightcove Has laid off 198 employees, who make up about two-thirds of its U.S. workforce, per a media report. The layoff comes a month after the company was acquired by Bending Spoons, an Italian app developer, for $233 million. Brightcove had 600 employees worldwide, with 300 in the U.S., as of December 2023. Acxiom Has reportedly laid off 130 employees, or 3.5% of its total workforce of 3,700 people. Acxiom is owned by IPG, and the news comes just a day after IPG and Omnicom Group shareholders approved the companies’ potential merger. Sequoia Capital Plans to close its office in Washington, D.C., and let go of its policy team there by the end of March, TechCrunch has confirmed. Sequoia opened its Washington office five years ago to deepen its relationship with policymakers. Three full-time employees are expected to be affected, per Forbes. Siemens Announced plans to let go of approximately 5,600 jobs globally in its automation and electric-vehicle charging businesses as part of efforts to improve competitiveness. HelloFresh Is reportedly laying off 273 employees, closing its distribution center in Grand Prairie, Texas, and consolidating to another site in Irving to manage the volume in the region. Otorio Has cut 45 employees, more than half of its workforce, after being acquired by cybersecurity company Armis for $120 million in March. ActiveFence Will reportedly reduce 22 employees, representing 7% of its workforce. Most of those affected are based in Israel as the company undergoes a streamlining process. The New York- and Tel Aviv-headquartered cybersecurity firm has raised $100 million at a valuation of about $500 million in 2021. D-ID Will cut 22 jobs, affecting nearly a quarter of its total workforce, following the announcement of the AI startup’s strategic partnership with Microsoft. NASA Announced it will be shutting down several of its offices in accordance with Elon Musk’s DOGE, including its Office of Technology, Policy, and Strategy and the DEI branch in the Office of Diversity and Equal Opportunity. Zonar Systems Has reportedly laid off some staff, according to LinkedIn posts from ex-employees. The company has not confirmed the layoffs, and it is currently unknown how many workers were affected. Wayfair Announced plans to let go of 340 employees in its technology division as part of a new restructuring effort. HPE Will cut 2,500 employees, or 5% of its total staff, in response to its shares sliding 19% in the first fiscal quarter. TikTok Will cut up to 300 workers in Dublin, accounting for roughly 10% of the company’s workforce in Ireland. LiveRamp Announced it will lay off 65 employees, affecting 5% of its total workforce. Ola Electric Is reportedly set to lay off over 1,000 employees and contractors in a cost-cutting effort. It’s the second round of cuts for the company in just five months. Rec Room Reduced its total headcount by 16% as the gaming startup shifts its focus to be “scrappier” and “more efficient.” ANS Commerce Was shut down just three years after it was acquired by Flipkart. It is currently unknown how many employees were affected. February HP Will cut up to 2,000 jobs as part of its “Future Now” restructuring plan that hopes to save the company $300 million before the end of its fiscal year. GrubHub Announced 500 job cuts after it was sold to Wonder Group for $650 million. The number of cuts affected more than 20% of its previous workforce. Autodesk Announced plans to lay off 1,350 employees, affecting 9% of its total workforce, in an attempt to reshape its GTM model. The company is also making reductions in its facilities, though it does not plan to close any offices. Google Is planning to cut employees in its People Operations and cloud organizations teams in a new reorganization effort. The company is offering a voluntary exit program to U.S.-based People Operations employees. Nautilus Reduced its headcount by 25 employees, accounting for 16% of its total workforce. The company is planning to release a commercial version of its proteome analysis platform in 2026. eBay Will reportedly cut a few dozen employees in Israel, potentially affecting 10% of its 250-person workforce in the country. Starbucks Cut 1,100 jobs in a reorganizing effort that affected its tech workers. The coffee chain will now outsource some tech work to third-party employees. Laid off dozens of employees over the last few weeks, including around 10% of staff in one day, after failing to meet its sales growth targets. The “headless commerce” platform raised money at a $1.9 billion valuation just a few years ago. Dayforce Will cut roughly 5% of its current workforce in a new efficiency drive to increase profitability and growth. Expedia Laid off more employees in a new effort to cut costs, though the total number is unknown. Last year, the travel giant cut about 1,500 roles in its Product & Technology division. Skybox Security Has ceased operations and has laid off its employees after selling its business and technology to Israeli cybersecurity company Tufin. The cuts affect roughly 300 people. HerMD Is shutting down its operations amid “ongoing challenges in healthcare.” It’s unclear the number of employees affected. In 2023, the women’s healthcare startup raised $18 million to fund its expansion. Zendesk Cut 51 jobs in its San Francisco headquarters, according to state filings with the Employment Development Department. The SaaS startup previously reduced its headcount by 8% in 2023. Vendease Has cut 120 employees, affecting 44% of its total staff. It’s the Y Combinator-backed Nigerian startup’s second layoff round in just five months. Logically Reportedly laid off dozens of employees as part of a new cost-cutting effort that aims to ensure “long-term success” in the startup’s mission to curb misinformation online. Blue Origin Will lay off about 10% of its workforce, affecting more than 1,000 employees. According to an email to staff obtained by CNN, the cuts will largely have an impact on positions in engineering and program management. Redfin Announced in an SEC filing that it will cut around 450 positions between February and July 2025, with a complete restructuring set to be completed in the fall, following its new partnership with Zillow. Sophos Is laying off 6% of its total workforce, the cybersecurity firm confirmed to TechCrunch. The cuts come less than two weeks after Sophos acquired Secureworks for $859 million. Zepz Will cut nearly 200 employees as it introduces redundancy measures and closes down its operations in Poland and Kenya. Unity Reportedly conducted another round of layoffs. It’s unknown how many employees were affected. JustWorks Cut nearly 200 employees, CEO Mike Seckler announced in a note to employees, citing “potential adverse events” like a recession or rising interest rates. Bird Cut 120 jobs, affecting roughly one-third of its total workforce, TechCrunch exclusively learned. The move comes just a year after the Dutch startup cut 90 employees following its rebrand. Sprinklr Laid off about 500 employees, affecting 15% of its workforce, citing poor business performance. The new cuts follow two earlier layoff rounds for the company that affected roughly 200 employees. Sonos Reportedly let go of approximately 200 employees, according to The Verge. The company previously cut 100 employees as part of a layoff round in August 2024. Workday Laid off 1,750 employees, as originally reported by Bloomberg and confirmed independently by TechCrunch. The cuts affect roughly 8.5% of the enterprise HR platform’s total headcount. Okta Laid off 180 employees, the company confirmed to TechCrunch. The cuts come just over one year after the access and identity management giant let go of 400 workers. Cruise Is laying off 50% of its workforce, including CEO Marc Whitten and several other top executives, as it prepares to shut down operations. What remains of the autonomous vehicle company will move under General Motors. Salesforce Is reportedly eliminating more than 1,000 jobs. The cuts come as the giant is actively recruiting and hiring workers to sell new AI products. January Cushion Has shut down operations, CEO Paul Kesserwani announced on LinkedIn. The fintech startup’s post-money valuation in 2022 was $82.4 million, according to PitchBook. Placer.ai Laid off 150 employees based in the U.S., affecting roughly 18% of its total workforce, in an effort to reach profitability. Amazon Laid off dozens of workers in its communications department in order to help the company “move faster, increase ownership, strengthen our culture, and bring teams closer to customers.” Stripe Is laying off 300 people, according to a leaked memo reported by Business Insider. However, according to the memo, the fintech giant is planning to grow its total headcount by 17%. Textio Laid off 15 employees as the augmented writing startup undergoes a restructuring effort. Pocket FM Is cutting 75 employees in an effort to “ensure the long-term sustainability and success” of the company. The audio company last cut 200 writers in July 2024 months after partnering with ElevenLabs. Aurora Solar Is planning to cut 58 employees in response to an “ongoing macroeconomic challenges and continued uncertainty in the solar industry.” Meta Announced in an internal memo that it will cut 5% of its staff targeting “low performers” as the company prepares for “an intense year.” As of its latest quarterly report, Meta currently has more than 72,000 employees. Wayfair Will cut up to 730 jobs, affecting 3% of its total workforce, as it plans to exit operations in Germany and focus on physical retailers. Pandion Is shutting down its operations, affecting 63 employees. The delivery startup said employees will be paid through January 15 without severance. Icon Is laying off 114 employees as part of a team realignment, per a new WARN notice filing, focusing its efforts on a robotic printing system. Altruist Eliminated 37 jobs, affecting roughly 10% of its total workforce, even as the company pursues “aggressive” hiring. Aqua Security Is cutting dozens of employees across its global markets as part of a strategic reorganization to increase profitability. SolarEdge Technologies Plans to lay off 400 employees globally. It’s the company’s fourth layoff round since January 2024 as the solar industry as a whole faces a downturn. Level The fintech startup, founded in 2018, abruptly shut down earlier this year. Per an email from CEO Paul Aaron, the closure follows an unsuccessful attempt to find a buyer, though Employer.com has a new offer under consideration to acquire the company post-shutdown. This list updates regularly. 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A Complete Guide to Using AI as a Graphic Designer \| AND Academy	A Complete Guide to Using AI as a Graphic Designer	https://www.andacademy.com	[ "Aniket Adarsh" ]	At its most immediate level, AI assists in design tasks by automating repetitive or time-consuming tasks. Background removal, object detection, ...	Read to know how AI is reshaping creativity and ways in which designers can harness it without losing originality. Artificial Intelligence (AI) is not new anymore. It has now embedded itself in almost every visual communication process, and designers are showing an increased acceptance of it. According to a survey done by Canva, 69% of global marketing and creative leaders believe it’s enhancing their team’s creativity. However, 17% still feel that generative AI tools are limiting their team’s creativity, citing that they prevent the development of original ideas. Why is it that most designers are comfortable with the rising use of Gen AI, but some disregard its potential? What kind of work is AI being used for? How can designers benefit from using AI? These are important questions that one might venture to ask, and so, we have tried to answer them in this article. Read along to find out. Here are the topics that we have covered: AI in Modern Graphic Design In today’s world, where design is digital first and print later, graphic design has evolved beyond static print media. The tools designers use daily, for branding, UI/UX, illustration, or marketing, are increasingly powered by artificial intelligence. Canva, Figma, Adobe Creative Suite, Sketch, Flowmapp, UXPin, and Miro- nearly every major design platform now integrates AI features as part of their creative toolkit. At its most immediate level, AI assists in design tasks by automating repetitive or time-consuming tasks. Background removal, object detection, color palette generation, font suggestions, auto-layout adjustments, and content resizing have become standard operations instead of extras. AI models trained on large visual datasets can now even make probabilistic guesses about design intent based on input and give suggestions that align with the user’s goals. The influence of AI extends beyond being efficient and moves towards ideation. By using models such as OpenAI’s DALL·E or Midjourney, designers explore hypothetical juxtapositions, visual metaphors, or unconventional styles. What this does is change the nature of what it means to brainstorm. Instead of laboriously mocking up design variations by hand, designers can rely on an AI system that returns dozens or even hundreds of visual options, among which human judgment can choose. This allows the designer to act more like a creative director. As a result, design goes from the mastery of tools to the curation of machine-generated stimuli, a shift that raises both exciting potentials and serious questions about authorship, originality, and the future role of the human in the design loop. All in all, AI is definitely changing how the creative process works. AI and the Creative Process The idea of a singular, standard creative process would not be very accurate, since creativity, by its very nature, resists formalization. Trying to define a universal creative method would be reductive. Instead, it is more productive to understand the context under which a designer forms their creative process, and then explore how artificial intelligence interacts within that specific context. In current practice, one can observe a sort of divergence in the design community. This division occurred with the availability of design tools with respect to changing times. On one end of the spectrum are designers (let’s call them Cohort-1) who entered the field when software like CorelDRAW and Microsoft PowerPoint represented the mainstream digital design tools. Those designers today are at a senior or executive level. On the other end are those whose introduction to design coincided with the rise of platforms such as Canva and Figma (let’s call them Cohort-2), which assume a different philosophy of using a tool and interaction. Designers who began their careers with earlier graphic design software were required to manually construct visual compositions. Creating basic shapes, paths, elements, and adjusting alignment were actions that demanded methodical input. These tools were traditional design methods programmed in a digital format. They prioritized precision and had no automation. As such, the creative process involved much technical execution. Every design began with a blank canvas and a set of digital drawing tools. For this group, the change that artificial intelligence brought was automating the repetitive, time-consuming aspects of design work, such as resizing images, removing backgrounds, typographic hierarchies, filters, etc. By doing so, AI created room for creative tasks. In contrast, Cohort- 2 is habituated to a fundamentally different design culture. The way tools such as Canva and Figma are used does not emulate manual drawing or start from scratch design to the extent comparable to the tools used by Cohort-1. Instead, they provide accessible and visual environments with pre-designed templates, modular components, and drag-and-drop elements, where the emphasis shifts to curation, composition, and iteration. For Cohort 2, the creative process is less about building visual elements from raw materials and more about configuring existing visual elements. Design work begins with a gallery of templates that serve as starting points, and in such a framework, AI becomes an essential graphic design tool that saves time and effort. Here, AI is used to ideate, to experiment with style variations, or generate visual concepts in response to text prompts. For Cohort‑1, AI is a quiet assistant automating repetitive tasks. For Cohort‑2, AI feels more like a co-creator. But no matter the entry point, both cohorts face the same challenge of balancing AI’s speed with human intent. And, even with such power, AI is not a complete replacement for human thinking. The Limitations of AI in Graphic Design While it can mimic styles and streamline workflows, AI doesn’t truly understand the emotional, cultural, or strategic layers behind a design decision. The human element of awareness, doubt, and critical thinking is still essential to design, and this is where limitations of AI become extremely clear. Read on to understand these in detail. 1. Lack of Self-Doubt At first glance, artificial intelligence appears confident. It processes data, identifies patterns, and produces polished results. But beneath this efficiency lies a flaw: AI does not doubt. It cannot second-guess its outputs. Unlike human designers, who are attuned to the subtleties of discomfort, contradiction, or moral tension in communication, AI simply combines data without questioning the patterns it detects. For Cohort‑2 especially, accustomed to starting with templates or AI-generated ideas, there’s a risk of over-trusting what appears ‘finished’. The illusion of certainty grows stronger when one doesn’t wrestle with the idea from scratch. 2. Misdirected Notions of the World Experienced designers understand meaning. They notice when a message feels off, when a color miscommunicates emotion, or when the layout contradicts cultural nuance. This sensitivity is what brings integrity to design. Doubt is the tool they use to pause, reflect, and correct. They ask: Is this really the right solution, or the most convenient one? AI, in contrast, does not sense when two ideas are contextually incompatible. 3. Limited Contextual Understanding AI does not actually ‘understand’ anything; instead, it looks for statistical relatability between symbols. In doing so, it builds arguments and generates options based on assumptions that might not be grounded in the problem's context. This makes AI a master of giving good answers. However, without awareness of the assumptions it’s making, it can confidently offer solutions that are fundamentally disconnected from reality. It relates things that shouldn't ideally be related. 4. Wrong Starting Point When designers begin with AI suggestions, say, for color palettes, layout styles, or even conceptual framing, they risk starting from assumptions that are statistically common but contextually false. This leads to an architectural flaw: ideas that look structurally sound but are, in essence, built on sand. So, the higher one builds on that base, the further one drifts from solving the real design problem. While Cohort‑1 might use AI as a polish or validation, Cohort‑2 uses it as a springboard. That sort of change narrows exploration before it even begins, and one runs the risk of coming up with designs that don’t do justice to the audience’s context. None of this warrants a rejection of AI. It means designers must understand the way their inputs are processed and also know when to question the output. Thankfully, AI tools, if used judiciously, can assist creativity without dictating it. Popular AI Design Tools There are various tools and features that designers can use to automate certain tasks and employ AI to their advantage. Read on for a few types below. 1. Layout & Design Assistants Figma recently introduced a suite of AI tools that speed up the design process. Its Visual Search feature helps designers find similar visuals using images or text, and Semantic Asset Search interprets vague terms like ‘primary button’ to search for the right components. With its ‘Make Designs’ feature, users can generate UI drafts from plain text prompts. The platform also has prompt-based text rewriting, translation, and content generation. Tools such as Fontjoy and Typescale use AI to recommend font pairings based on aesthetic and functional compatibility. Instead of testing dozens of combinations manually, a designer can receive suggestions based on hierarchy, readability, and genre. Branding is another domain increasingly influenced by AI. Platforms like Looka or Brandmark use AI to generate brand kits, complete with logos, color schemes, and typographic combinations based on a user’s input about their business identity. While the outcomes might lack the nuance of custom design work, these tools make visual identity systems accessible for startups and small businesses, which then can later be refined by professional designers. 3. UX Analytics UI/UX design platforms have integrated AI for wireframing, prototyping, and user behavior prediction. AI can analyze user flows to predict friction points or recommend changes for better usability. For instance, AI in Hotjar or FullStory can interpret heatmaps and click-tracking data to identify design elements that users find confusing or inaccessible, which can inform future design decisions. The takeaway here is that AI tools excel at handling the mechanical, data-driven, and iterative aspects of the design process, in turn enabling designers to focus more on conceptual thinking, experimentation, and crafting. The Evolving Role of Graphic Designers As AI for graphic design grows more capable, the responsibilities and required skill sets of graphic designers are also changing fundamentally. The traditional role of a designer is being reshaped into that of a creative director, design strategist, and system thinker. Some aspects that are evolving are: 1. Increased Focus on Ideas Designers today are not expected to draw every icon or develop every gradient from scratch. Instead, their value lies in how they conceptualize problems, frame narratives, and make design choices that align with brand strategy, consumer psychology, and cultural trends. 2. Speaking the Language of AI A broader understanding of disciplines beyond visual aesthetics is desired. Designers must learn the language of data and algorithms, as AI systems rely on input quality and semantic clarity. Knowing how to describe a visual idea to a machine in terms of style, mood, composition, and color can determine whether the output is useful or not. 3. Mindfulness around Ethics Modern-day designers are also being asked to make judgments about fairness, representation, and authenticity, which are tasks that AI cannot handle reliably. For instance, an AI might inadvertently generate biased imagery that reinforces stereotypes if its training data is unbalanced. The designer must recognize and correct this. When using AI, it’s the designer’s role to audit, verify, and ensure the integrity of outputs. 4. Empathy in Design Soft skills such as empathy, storytelling, and conceptual thinking are growing in importance. For example, while an AI can generate a logo based on a set of prompts, it cannot understand the emotions and psychological associations that the logo needs to evoke for a specific audience. A human designer, through research and lived experience, can establish meaning in ways AI cannot. As AI continues to evolve, the designers who embrace its possibilities while mastering its limitations will shape the future of the creative industry. Final Thoughts AI is changing graphic design, but its real power lies in enhancing and not replacing human creativity. The best designers will use AI as a smart assistant, combining its speed with their unique intuition, cultural insights, and strategic thinking. The key here will be knowledge and being able to think like a designer. We recommend you check out this project by AND Learner, Bibin S, for inspiration for your next project. While AI can generate options, only designers can choose the right one. It can suggest colors, but only designers can know if they evoke the right emotions. The future belongs to those who balance AI's capabilities with human creativity and use it to handle repetitive tasks while focusing on storytelling and innovation. FAQs Q1. Will AI replace graphic designers? AI is unlikely to replace graphic designers entirely. AI excels at automation and generating design options, but it lacks human intuition, emotional intelligence, and strategic decision-making. Designers who adapt by using AI as a tool rather than relying on it as a replacement will remain essential for refining ideas. Q2. How can designers maintain originality when using AI? Originality requires conscious effort when working with AI. Rather than accepting AI's first suggestions as final solutions, designers should use them as ideas to be challenged and refined. Ask why certain suggestions emerged, whether they truly fit the project context, and how they might be subverted or reframed in different ways. Q3. Which AI tools are best for graphic designers? Many AI tools solve different aspects of design problems. For concept generation, Midjourney and DALL·E are popular. Figma AI and Canva’s Magic Design assist with layout and UI, and Fontjoy helps with typography. Branding and AI logo design tools like Looka automate logo creation, and UX analytics platforms such as Hotjar provide user behavior insights. Next Steps In case you need further assistance, here are some of our resources you can consider: Watch this session by design veteran and AND’s Academic Head, Prachi Mittal, and our Course Lead, Soumya Tiwari. Talk to a course advisor to discuss how you can transform your career with one of our courses. Pursue our Graphic Design courses - all courses are taught through live, interactive classes by industry experts, and some even offer a Job Guarantee. Take advantage of the scholarship and funding options that come with our courses to overcome any financial hurdle on the path to your career transformation. Note: All information and/or data from external sources is believed to be accurate as of the date of publication.	2025-06-30T00:00:00	2025/06/30	https://www.andacademy.com/resources/blog/graphic-design/ai-for-graphic-designers/	[ { "date": "2025/06/30", "position": 25, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 41, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 33, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 33, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 37, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 40, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 39, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 21, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 33, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 34, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 33, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 32, "query": "artificial intelligence graphic design" }, { "date": "2025/06/30", "position": 32, "query": "artificial intelligence graphic design" } ]
Jasper Sleet: North Korean remote IT workers' evolving tactics to ...	Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations	https://www.microsoft.com	[ "Microsoft Threat Intelligence", "See Microsoft Threat Intelligence Posts" ]	Since 2024, Microsoft Threat Intelligence has observed remote information technology (IT) workers deployed by North Korea leveraging AI to ...	Since 2024, Microsoft Threat Intelligence has observed remote information technology (IT) workers deployed by North Korea leveraging AI to improve the scale and sophistication of their operations, steal data, and generate revenue for the Democratic People’s Republic of Korea (DPRK). Among the changes noted in the North Korean remote IT worker tactics, techniques, and procedures (TTPs) include the use of AI tools to replace images in stolen employment and identity documents and enhance North Korean IT worker photos to make them appear more professional. We’ve also observed that they’ve been utilizing voice-changing software. North Korea has deployed thousands of remote IT workers to assume jobs in software and web development as part of a revenue generation scheme for the North Korean government. These highly skilled workers are most often located in North Korea, China, and Russia, and use tools such as virtual private networks (VPNs) and remote monitoring and management (RMM) tools together with witting accomplices to conceal their locations and identities. Historically, North Korea’s fraudulent remote worker scheme has focused on targeting United States (US) companies in the technology, critical manufacturing, and transportation sectors. However, we’ve observed North Korean remote workers evolving to broaden their scope to target various industries globally that offer technology-related roles. Since 2020, the US government and cybersecurity community have identified thousands of North Korean workers infiltrating companies across various industries. Organizations can protect themselves from this threat by implementing stricter pre-employment vetting measures and creating policies to block unapproved IT management tools. For example, when evaluating potential employees, employers and recruiters should ensure that the candidates’ social media and professional accounts are unique and verify their contact information and digital footprint. Organizations should also be particularly cautious with staffing company employees, check for consistency in resumes, and use video calls to confirm a worker’s identity. Microsoft Threat Intelligence tracks North Korean IT remote worker activity as Jasper Sleet (formerly known as Storm-0287). We also track several other North Korean activity clusters that pursue fraudulent employment using similar techniques and tools, including Storm-1877 and Moonstone Sleet. To disrupt this activity and protect our customers, we’ve suspended 3,000 known Microsoft consumer accounts (Outlook/Hotmail) created by North Korean IT workers. We have also implemented several detections to alert our customers of this activity through Microsoft Entra ID Protection and Microsoft Defender XDR as noted at the end of this blog. As with any observed nation-state threat actor activity, Microsoft has directly notified targeted or compromised customers, providing them with important information needed to secure their environments. As we continue to observe more attempts by threat actors to leverage AI, not only do we report on them, but we also have principles in place to take action against them. This blog provides additional information on the North Korean remote IT worker operations we published previously, including Jasper Sleet’s usual TTPs to secure employment, such as using fraudulent identities and facilitators. We also provide recent observations regarding their use of AI tools. Finally, we share detailed guidance on how to investigate, monitor, and remediate possible North Korean remote IT worker activity, as well as detections and hunting capabilities to surface this threat. From North Korea to the world: The remote IT workforce Since at least early 2020, Microsoft has tracked a global operation conducted by North Korea in which skilled IT workers apply for remote job opportunities to generate revenue and support state interests. These workers present themselves as foreign (non-North Korean) or domestic-based teleworkers and use a variety of fraudulent means to bypass employment verification controls. North Korea’s fraudulent remote worker scheme has since evolved, establishing itself as a well-developed operation that has allowed North Korean remote workers to infiltrate technology-related roles across various industries. In some cases, victim organizations have even reported that remote IT workers were some of their most talented employees. Historically, this operation has focused on applying for IT, software development, and administrator positions in the technology sector. Such positions provide North Korean threat actors access to highly sensitive information to conduct information theft and extortion, among other operations. North Korean IT workers are a multifaceted threat because not only do they generate revenue for the North Korean regime, which violates international sanctions, they also use their access to steal sensitive intellectual property, source code, or trade secrets. In some cases, these North Korean workers even extort their employer into paying them in exchange for not publicly disclosing the company’s data. Between 2020 and 2022, the US government found that over 300 US companies in multiple industries, including several Fortune 500 companies, had unknowingly employed these workers, indicating the magnitude of this threat. The workers also attempted to gain access to information at two government agencies. Since then, the cybersecurity community has continued to detect thousands of North Korean workers. On January 3, 2025, the Justice Department released an indictment identifying two North Korean nationals and three facilitators responsible for conducting fraudulent work between 2018 and 2024. The indicted individuals generated a revenue of at least US$866,255 from only ten of the at least 64 infiltrated US companies. North Korean threat actors are evolving across the threat landscape to incorporate more sophisticated tactics and tools to conduct malicious employment-related activity, including the use of custom and AI-enabled software. Tactics and techniques The tactics and techniques employed by North Korean remote IT workers involve a sophisticated ecosystem of crafting fake personas, performing remote work, and securing payments. North Korean IT workers apply for remote roles, in various sectors, at organizations across the globe. They create, rent, or procure stolen identities that match the geo-location of their target organizations (for example, they would establish a US-based identity to apply for roles at US-based companies), create email accounts and social media profiles, and establish legitimacy through fake portfolios and profiles on developer platforms like GitHub and LinkedIn. Additionally, they leverage AI tools to enhance their operations, including image creation and voice-changing software. Facilitators play a crucial role in validating fraudulent identities and managing logistics, such as forwarding company hardware and creating accounts on freelance job websites. To evade detection, these workers use VPNs, virtual private servers (VPSs), and proxy services as well as RMM tools to connect to a device housed at a facilitator’s laptop farm located in the country of the job. Figure 1. The North Korean IT worker ecosystem Crafting fake personas and profiles The North Korean remote IT worker fraud scheme begins with the procurement of identities for the workers. These identities, which can be stolen or “rented” from witting individuals, include names, national identification numbers, and dates of birth. The workers might also leverage services that generate fraudulent identities, complete with seemingly legitimate documentation, to fabricate their personas. They then create email accounts and social media pages they use to apply for jobs, often indirectly through staffing or contracting companies. They also apply for freelance opportunities through freelancer sites as an additional avenue for revenue generation. Notably, they often use the same names/profiles repeatedly rather than creating unique personas for each successful infiltration. Additionally, the North Korean IT workers have used fake profiles on LinkedIn to communicate with recruiters and apply for jobs. Figure 2. An example of a North Korean IT worker LinkedIn profile that has since been taken down. The workers tailor their fake resumes and profiles to match the requirements for specific remote IT positions, thus increasing their chances of getting selected. Over time, we’ve observed these fake resumes and employee documents noticeably improving in quality, now appearing more polished and lacking grammatical errors facilitated by AI. After creating their fake personas, the North Korean IT workers then attempt to establish legitimacy by creating digital footprints for these fake personas. They typically leverage communication, networking, and developer platforms, (for example, GitHub) to showcase their supposed portfolio of previous work samples: Figure 3. Example profile used by a North Korean IT worker that has since been taken down. Using AI to improve operations Microsoft Threat intelligence has observed North Korean remote IT workers leveraging AI to improve the quantity and quality of their operations. For example, in October 2024, we found a public repository containing actual and AI-enhanced images of suspected North Korean IT workers: Figure 4. Photos of potential North Korean IT workers The repository also contained the resumes and email accounts used by the said workers, along with the following tools and resources they can use to secure employment and to do their work: VPS and VPN accounts, along with specific VPS IP addresses Playbooks on conducting identity theft and creating and bidding jobs on freelancer websites Wallet information and suspected payments made to facilitators LinkedIn, GitHub, Upwork, TeamViewer, Telegram, and Skype accounts Tracking sheet of work performed, and payments received by the IT workers Image creation Based on our review of the repository mentioned previously, North Korean IT workers appear to conduct identity theft and then use AI tools like Faceswap to move their pictures over to the stolen employment and identity documents. The attackers also use these AI tools to take pictures of the workers and move them to more professional looking settings. The workers then use these AI-generated pictures on one or more resumes or profiles when applying for jobs. Figure 5. Use of AI apps to modify photos used for North Korean IT workers’ resumes and profiles Figure 6. Examples of resumes for North Korean IT workers. These two resumes use different versions of the same photo. Communications Microsoft Threat Intelligence has observed that North Korean IT workers are also experimenting with other AI technologies such as voice-changing software. While we haven’t observed threat actors using combined AI voice and video products as a tactic first hand, we do recognize that combining these technologies could allow future threat actor campaigns to trick interviewers into thinking they aren’t communicating with a North Korean IT worker. If successful, this tactic could allow the North Korean IT workers to do interviews directly and no longer rely on facilitators standing in for them on interviews or selling them account access. Facilitators for initial access North Korean remote IT workers require assistance from a witting facilitator to help find jobs, pass the employment verification process, and once hired, successfully work remotely. We’ve observed Jasper Sleet advertising job opportunities for facilitator roles under the guise of partnering with a remote job candidate to help secure an IT role in a competitive market: Figure 7. Example of a job opportunity for a facilitator role The IT workers may have the facilitators assist in creating accounts on remote and freelance job websites. They might also ask the facilitator to perform the following tasks as their relationship builds: Create a bank account for the North Korean IT worker, or lend their (the facilitator’s) own account to the worker Purchase mobile phone numbers or SIM cards During the employment verification process, the witting accomplice helps the North Korean IT workers validate the latter’s fraudulent identities using online background check service providers. The documents submitted by the workers include fake or stolen drivers’ licenses, social security cards, passports, and permanent resident identification cards. Workers train using interview scripts, which include a justification for why the employee must work remotely. Once hired, the remote workers direct company laptops and hardware to be sent to the address of the accomplice. The accomplice then either runs a laptop farm that provides the laptops with an internet connection at the geo-location of the role or forwards the items internationally. For hardware that remain in the country of the role, the accomplice signs into the computers and installs software that enables the workers to connect remotely. Remote IT workers might also access devices remotely using IP-based KVM devices, like PiKVM or TinyPilot. Defense evasion and persistence To conceal their physical location as well as maintain persistence and blend into the target organization’s environment, the workers typically use VPNs (particularly Astrill VPN), VPSs, proxy services, and RMM tools. Microsoft Threat Intelligence has observed the persistent use of JumpConnect, TinyPilot, Rust Desk, TeamViewer, AnyViewer, and Anydesk. When an in-person presence or face-to-face meeting is required, for example to confirm banking information or attend a meeting, the workers have been known to pay accomplices to stand in for them. When possible, however, the workers eliminate all face-to-face contact, offering fraudulent excuses for why they are not on camera during video teleconferencing calls or speaking. Attribution Microsoft Threat Intelligence uses the name Jasper Sleet (formerly known as Storm-0287) to represent activity associated with North Korean’s remote IT worker program. These workers are primarily focused on revenue generation, use remote access tools, and likely fall under a particular leadership structure in North Korea. We also track several other North Korean activity clusters that pursue fraudulent employment using similar techniques and tools, including Storm-1877 and Moonstone Sleet. How Microsoft disrupts North Korean remote IT worker operations with machine learning Microsoft has successfully scaled analyst tradecraft to accelerate the identification and disruption of North Korean IT workers in customer environments by developing a custom machine learning solution. This has been achieved by leveraging Microsoft’s existing threat intelligence and weak signals generated by monitoring for many of the red flags listed in this blog, among others. For example, this solution uses impossible time travel risk detections, most commonly between a Western nation and China or Russia. The machine learning workflow uses these features to surface suspect accounts most likely to be North Korean IT workers for assessment by Microsoft Threat Intelligence analysts. Once Microsoft Threat Intelligence reviews and confirms that an account is indeed associated with a North Korean IT worker, customers are then notified with a Microsoft Entra ID Protection risk detection warning of a risky sign-in based on Microsoft’s threat intelligence. Microsoft Defender XDR customers also receive the alert Sign-in activity by a suspected North Korean entity in the Microsoft Defender portal. Defending against North Korean remote IT worker infiltration Defending against the threats from North Korean remote IT workers involves a threefold strategy: Ensuring a proper vetting approach is in place for freelance workers and vendors Monitoring for anomalous user activity Responding to suspected Jasper Sleet signals in close coordination with your insider risk team Investigate How can you identify a North Korean remote IT worker in the hiring process? To protect your organization against a potential North Korean insider threat, it is important for your organization to prioritize a process for verifying employees to identify potential risks. The following can be used to assess potential employees: Confirm the potential employee has a digital footprint and look for signs of authenticity. This includes a real phone number (not VoIP), a residential address, and social media accounts. Ensure the potential employee’s social media/professional accounts are not highly similar to the accounts of other individuals. In addition, check that the contact phone number listed on the potential employee’s account is unique and not also used by other accounts. Scrutinize resumes and background checks for consistency of names, addresses, and dates. Consider contacting references by phone or video-teleconference rather than email only. Exercise greater scrutiny for employees of staffing companies, since this is the easiest avenue for North Korean workers to infiltrate target companies. Search whether a potential employee is employed at multiple companies using the same persona. Ensure the potential employee is seen on camera during multiple video telecommunication sessions. If the potential employee reports video and/or microphone issues that prohibit participation, this should be considered a red flag. During video verification, request individuals to physically hold driver’s licenses, passports, or identity documents up to camera. Keep records, including recordings of video interviews, of all interactions with potential employees. Require notarized proof of identity. Monitor How can your organization prevent falling victim to the North Korean remote IT worker technique? To prevent the risks associated with North Korean insider threats, it’s vital to monitor for activity typically associated with this fraudulent scheme. Monitor for identifiable characteristics of North Korean remote workers Microsoft has identified the following characteristics of a North Korean remote worker. Note that not all the criteria are necessarily required, and further, a positive identification of a remote worker doesn’t guarantee that the worker is North Korean. The employee lists a Chinese phone number on social media accounts that is used by other accounts. The worker’s work-issued laptop authenticates from an IP address of a known North Korean IT worker laptop farm, or from foreign—most commonly Chinese or Russian—IP addresses even though the worker is supposed to have a different work location. The worker is employed at multiple companies using the same persona. Employees of staffing companies require heightened scrutiny, given this is the easiest way for North Korean workers to infiltrate target companies. Once a laptop is issued to the worker, RMM software is immediately downloaded onto it and used in combination with a VPN. The worker has never been seen on camera during a video telecommunication session or is only seen a few times. The worker may also report video and/or microphone issues that prohibit participation from the start. The worker’s online activity doesn’t align with routine co-worker hours, with limited engagement across approved communication platforms. Monitor for activity associated with Jasper Sleet access If RMM tools are used in your environment, enforce security settings where possible, to implement MFA: Use Windows Defender Application Control or AppLocker to create policies to block unapproved IT management tools. Consider hunting for unapproved RMM software installations and creating custom detections ( Investigation & response > Hunting > Advanced hunting > Manage rules > Create custom detection ) for any advanced hunting queries that are useful indicators of anomalous or unapproved activity in your environment. If an unapproved installation is discovered, reset passwords for accounts used to install the RMM services. If a system-level account was used to install the software, further investigation may be warranted. Monitor for impossible travel—for example, a supposedly US-based employee signing in from China or Russia. Monitor for use of public VPNs such as Astrill. For example, IP addresses associated with VPNs known to be used by Jasper Sleet can be added to Sentinel watchlists. Or, Microsoft Defender for Identity can integrate with your VPN solution to provide more information about user activity, such as extra detection for abnormal VPN connections. Monitor for signals of insider threats in your environment. Microsoft Purview Insider Risk Management can help identify potentially malicious or inadvertent insider risks. Monitor for consistent user activity outside of typical working hours. Remediate What are the next steps if you positively identify a North Korean remote IT worker employed at your company? Because Jasper Sleet activity follows legitimate job offers and authorized access, Microsoft recommends approaching confirmed or suspected Jasper Sleet intrusions with an insider risk approach using your organization’s insider risk response plan or incident response provider like Microsoft Incident Response. Some steps might include: Restrict response efforts to a small, trusted insider risk working group, trained in operational security (OPSEC) to avoid tipping off subjects and potential collaborators. Rapidly evaluate the subject’s proximity to critical assets, such as: Leadership or sensitive teams Direct reports or vendor staff the subject has influence over Suppliers or vendors People/non-people accounts, production/pre-production environments, shared accounts, security groups, third-party accounts, security groups, distribution groups, data clusters, and more Conduct preliminary link analysis to: Detect relationships with potential collaborators, supporters, or other potential aliases operated by the same actor Identify shared indicators (for example, shared IP addresses, behavioral overlap) Avoid premature action that might alert other Jasper Sleet operators Conduct a risk-based prioritization of efforts, informed by: Placement and access to critical assets (not necessarily where you identified them)Stakeholder insight from potentially impacted business units Business impact considerations of containment (which might support additional collection/analysis) or mitigation (for example, eviction) Conduct open-source intelligence (OSINT) collection and analysis to: Determine if the identity associated with the threat actor is associated with a real person. For example, North Korean IT workers have leveraged stolen identities of real US persons to facilitate their fraud. Conduct OSINT on all available personally identifiable information (PII) provided by the actor (name, date of birth, SSN, home of record, phone number, emergency contact, and others) and determine if these items are linked to additional North Korean actors, and/or real persons’ identities. Gather all known external accounts operated by the alias/persona (for example, LinkedIn, GitHub, freelance working sites, bug bounty programs). Perform analysis on account images using open-source tools such as FaceForensics++ to determine prevalence of AI-generated content. Detection opportunities within video and imagery include: Temporal consistency issues: Rapid movements cause noticeable artifacts in video deepfakes as the tracking system struggles to maintain accurate landmark positioning. Occlusion handling: When objects pass over the AI-generated content such as the face, deepfake systems tend to fail at properly reconstructing the partially obscured face. Lighting adaptation: Changes in lighting conditions might reveal inconsistencies in the rendering of the face Audio-visual synchronization: Slight delays between lip movements and speech are detectable under careful observation Exaggerated facial expressions. Duplicative or improperly placed appendages. Pixelation or tearing at edges of face, eyes, ears, and glasses. Engage counterintelligence or insider risk/threat teams to: Understand tradecraft and likely next steps Gain national-level threat context, if applicable Make incremental, risk-based investigative and response decisions with the support of your insider threat working group and your insider threat stakeholder group; one providing tactical feedback and the other providing risk tolerance feedback. Preserve evidence and document findings. Share lessons learned and increase awareness. Educate employees on the risks associated with insider threats and provide regular security training for employees to recognize and respond to threats, including a section on the unique threat posed by North Korean IT workers. After an insider risk response to Jasper Sleet, it might be necessary to also conduct a thorough forensic investigation of all systems that the employee had access to for indicators of persistence, such as RMM tools or system/resource modifications. For additional resources, refer to CISA’s Insider Threat Mitigation Guide. If you suspect your organization is being targeted by nation-state cyber activity, report it to the appropriate national authority. For US-based organizations, the Federal Bureau of Investigation (FBI) recommends reporting North Korean remote IT worker activity to the Internet Crime Complaint Center (IC3). Microsoft Defender XDR detections Microsoft Defender XDR customers can refer to the list of applicable detections below. Microsoft Defender XDR coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog. Customers with provisioned access can also use Microsoft Security Copilot in Microsoft Defender to investigate and respond to incidents, hunt for threats, and protect their organization with relevant threat intelligence. Microsoft Defender XDR Alerts with the following title in the security center can indicate threat activity on your network: Sign-in activity by a suspected North Korean entity Microsoft Defender for Endpoint Alerts with the following titles in the security center can indicate Jasper Sleet RMM activity on your network. These alerts, however, can be triggered by unrelated threat activity. Suspicious usage of remote management software Suspicious connection to remote access software Microsoft Defender for Identity Alerts with the following titles in the security center can indicate atypical identity access on your network. These alerts, however, can be triggered by unrelated threat activity. Atypical travel Suspicious behavior: Impossible travel activity Microsoft Entra ID Protection Microsoft Entra ID Protection risk detections inform Entra ID user risk events and can indicate associated threat activity, including unusual user activity consistent with known patterns identified by Microsoft Threat Intelligence research. Note, however, that these alerts can be also triggered by unrelated threat activity. Microsoft Entra threat intelligence (sign-in): (RiskEventType: investigationsThreatIntelligence) Microsoft Defender for Cloud Apps Alerts with the following titles in the security center can indicate atypical identity access on your network. These alerts, however, can be triggered by unrelated threat activity. Impossible travel activity Microsoft Security Copilot Security Copilot customers can use the standalone experience to create their own prompts or run the following prebuilt promptbooks to automate incident response or investigation tasks related to this threat: Incident investigation Microsoft User analysis Threat actor profile Note that some promptbooks require access to plugins for Microsoft products such as Microsoft Defender XDR or Microsoft Sentinel. Hunting queries Microsoft Defender XDR Because organizations might have legitimate and frequent uses for RMM software, we recommend using the Microsoft Defender XDR advanced hunting queries available on GitHub to locate RMM software that hasn’t been endorsed by your organization for further investigation. In some cases, these results might include benign activity from legitimate users. Regardless of use case, all newly installed RMM instances should be scrutinized and investigated. If any queries have high fidelity for discovering unsanctioned RMM instances in your environment, and don’t detect benign activity, you can create a custom detection rule from the advanced hunting query in the Microsoft Defender portal. Microsoft Sentinel The alert Insider Risk Sensitive Data Access Outside Organizational Geo-locationjoins Azure Information Protection logs (InformationProtectionLogs_CL) with Microsoft Entra ID sign-in logs (SigninLogs) to provide a correlation of sensitive data access by geo-location. Results include: User principal name Label name Activity City State Country/Region Time generated The recommended configuration is to include (or exclude) sign-in geo-locations (city, state, country and/or region) for trusted organizational locations. There is an option for configuration of correlations against Microsoft Sentinel watchlists. Accessing sensitive data from a new or unauthorized geo-location warrants further review. References Acknowledgments For more information on North Korean remote IT worker operations, we recommend reviewing DTEX’s in-depth analysis in the report Exposing DPRK’s Cyber Syndicate and IT Workforce. Learn more Meet the experts behind Microsoft Threat Intelligence, Incident Response, and the Microsoft Security Response Center at our VIP Mixer at Black Hat 2025. Discover how our end-to-end platform can help you strengthen resilience and elevate your security posture. For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog. To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky. To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.	2025-06-30T00:00:00	2025/06/30	https://www.microsoft.com/en-us/security/blog/2025/06/30/jasper-sleet-north-korean-remote-it-workers-evolving-tactics-to-infiltrate-organizations/	[ { "date": "2025/06/30", "position": 71, "query": "AI workers" }, { "date": "2025/06/30", "position": 68, "query": "AI workers" }, { "date": "2025/06/30", "position": 67, "query": "AI workers" }, { "date": "2025/06/30", "position": 65, "query": "AI workers" }, { "date": "2025/06/30", "position": 64, "query": "AI workers" }, { "date": "2025/06/30", "position": 66, "query": "AI workers" }, { "date": "2025/06/30", "position": 80, "query": "AI workers" }, { "date": "2025/06/30", "position": 64, "query": "AI workers" }, { "date": "2025/06/30", "position": 66, "query": "AI workers" }, { "date": "2025/06/30", "position": 62, "query": "AI workers" }, { "date": "2025/06/30", "position": 64, "query": "AI workers" }, { "date": "2025/06/30", "position": 64, "query": "AI workers" }, { "date": "2025/06/30", "position": 78, "query": "AI workers" }, { "date": "2025/06/30", "position": 65, "query": "AI workers" }, { "date": "2025/06/30", "position": 64, "query": "AI workers" } ]
Meta shares hit all-time high as Zuckerberg goes on AI hiring blitz	Meta shares hit all-time high as Mark Zuckerberg goes on AI hiring blitz	https://www.cnbc.com	[ "Jonathan Vanian", "In" ]	Meta CEO Mark Zuckerberg has been on an AI hiring blitz amid fierce competition with rivals such as OpenAI and Google parent Alphabet. In this ...	Mark Zuckerberg, chief executive officer of Meta Platforms Inc., during the Meta Connect event on Wednesday, Sept. 25, 2024. Meta shares hit a record high on Monday, underscoring investor interest in the company's new AI superintelligence group. The company's shares reached $747.90 during midday trading, topping Meta's previous stock market record in February when it began laying off the 5% of its workforce that it deemed "low performers." Meta joins Microsoft and Nvidia among tech megacaps that have reached new highs of late, all closing at or near records Monday. Apple, Amazon, Alphabet and Tesla remain below their all-time highs reached late last year or early this year. Meta CEO Mark Zuckerberg has been on an AI hiring blitz amid fierce competition with rivals such as OpenAI and Google parent Alphabet . Earlier in June, Meta said it would hire Scale AI CEO Alexandr Wang and some of his colleagues as part of a $14.3 billion investment into the executive's data labeling and annotation startup. The social media company also hired Nat Friedman and his business partner, Daniel Gross, the chief of Safe Superintelligence, an AI startup with a valuation of $32 billion, CNBC reported on June 19. Meta's attempts to buy Safe Superintelligence were rebuffed by the startup's founder and AI expert Ilya Sutskever, the report noted. Wang and Friedman are the leaders of Meta's new Superintelligence Labs, tasked with overseeing the company's artificial intelligence foundation models, projects and research, a person familiar with the matter told CNBC. The term superintelligence refers to technology that exceeds human capability. Bloomberg News first reported about the new superintelligence unit. Meta has also snatched AI researchers from OpenAI. Sam Altman, OpenAI's CEO, said during a podcast that Meta was offering signing bonuses as high as $100 million. Andrew Bosworth, Meta's technology chief, spoke about the social media company's AI hiring spree during a June 20 interview with CNBC's "Closing Bell Overtime," saying that the talent market is "really incredible and kind of unprecedented in my 20-year career as a technology executive." WATCH: Meta's AI talent spending spree	2025-06-30T00:00:00	2025/06/30	https://www.cnbc.com/2025/06/30/meta-hits-all-time-mark-zuckerberg-ai-blitz.html	[ { "date": "2025/06/30", "position": 97, "query": "AI hiring" }, { "date": "2025/06/30", "position": 98, "query": "AI hiring" }, { "date": "2025/06/30", "position": 98, "query": "AI hiring" }, { "date": "2025/06/30", "position": 98, "query": "AI hiring" }, { "date": "2025/06/30", "position": 95, "query": "AI hiring" } ]
The Path to Medical Superintelligence - Microsoft AI	The Path to Medical Superintelligence	https://microsoft.ai	[]	Our findings also suggest that AI reduce unnecessary healthcare costs. U.S. health spending is nearing 20% of US GDP, with up to 25% of that ...	The Microsoft AI team shares research that demonstrates how AI can sequentially investigate and solve medicine’s most complex diagnostic challenges—cases that expert physicians struggle to answer. Benchmarked against real-world case records published each week in the New England Journal of Medicine, we show that the Microsoft AI Diagnostic Orchestrator (MAI-DxO) correctly diagnoses up to 85% of NEJM case proceedings, a rate more than four times higher than a group of experienced physicians. MAI-DxO also gets to the correct diagnosis more cost-effectively than physicians. — As demand for healthcare continues to grow, costs are rising at an unsustainable pace, and billions of people face multiple barriers to better health – including inaccurate and delayed diagnoses. Increasingly, people are turning to digital tools for medical advice and support. Across Microsoft’s AI consumer products like Bing and Copilot, we see over 50 million health-related sessions every day. From a first-time knee-pain query to a late-night search for an urgent-care clinic, search engines and AI companions are quickly becoming the new front line in healthcare. We want to do more to help -and believe generative AI can be transformational. That’s why, at the end of 2024, we launched a dedicated consumer health effort at Microsoft AI, led by clinicians, designers, engineers, and AI scientists. This effort complements Microsoft’s broader health initiatives and builds on our longstanding commitment to partnership and innovation. Existing solutions include RAD-DINO which helps accelerate and improve radiology workflows and Microsoft Dragon Copilot, our pioneering voice-first AI assistant for clinicians. For AI to make a difference, clinicians and patients alike must be able to trust its performance. That’s where our new benchmarks and AI orchestrator come in. Medical Case Challenges and Benchmarks To practice medicine in the United States, physicians need to pass the United States Medical Licensing Examination (USMLE), a rigorous and standardized assessment of clinical knowledge and decision making. USMLE questions were among the earliest benchmarks used to evaluate AI systems in medicine, offering a structured way to compare model performance – both against each other and against human clinicians. In just three years, generative AI has advanced to the point of scoring near-perfect scores on the USMLE and similar exams. But these tests primarily rely on multiple-choice questions, which favor memorization over deep understanding. By reducing medicine to one-shot answers on multiple-choice questions, such benchmarks overstate the apparent competence of AI systems and obscure their limitations. At Microsoft AI, we’re working to advance and evaluate clinical reasoning capabilities. To move beyond the limitations of multiple-choice questions, we’ve focused on sequential diagnosis, a cornerstone of real-world medical decision making. In this process, a clinician begins with an initial patient presentation and then iteratively selects questions and diagnostic tests to arrive at a final diagnosis. For example, a patient presenting with cough and fever may lead the clinician to order and review blood tests and a chest X-ray before they feel confident about diagnosing pneumonia. Each week, the New England Journal of Medicine (NEJM) – one of the world’s leading medical journals – publishes a Case Record of the Massachusetts General Hospital, presenting a patient’s care journey in a detailed, narrative format. These cases are among the most diagnostically complex and intellectually demanding in clinical medicine, often requiring multiple specialists and diagnostic tests to reach a definitive diagnosis. How does AI perform? To answer this, we created interactive case challenges drawn from the NEJM case series – what we call the Sequential Diagnosis Benchmark (SD Bench). This benchmark transforms 304 recent NEJM cases into stepwise diagnostic encounters where models – or human physicians – can iteratively ask questions and order tests. As new information becomes available, the model or clinician updates their reasoning, gradually narrowing toward a final diagnosis. This diagnosis can then be compared to the gold-standard outcome published in the NEJM. Each requested investigation also incurs a (virtual) cost, reflecting real-world healthcare expenditures. This allows us to evaluate performance across two key dimensions: diagnostic accuracy and resource expenditure. You can watch how an AI system progresses through one of these challenges in this short video.	2025-06-30T00:00:00		https://microsoft.ai/new/the-path-to-medical-superintelligence/	[ { "date": "2025/06/30", "position": 31, "query": "AI healthcare" }, { "date": "2025/06/30", "position": 29, "query": "AI healthcare" }, { "date": "2025/06/30", "position": 23, "query": "AI healthcare" }, { "date": "2025/06/30", "position": 16, "query": "AI healthcare" }, { "date": "2025/06/30", "position": 48, "query": "artificial intelligence healthcare" }, { "date": "2025/06/30", "position": 50, "query": "artificial intelligence healthcare" }, { "date": "2025/06/30", "position": 14, "query": "AI healthcare" }, { "date": "2025/06/30", "position": 49, "query": "artificial intelligence healthcare" }, { "date": "2025/06/30", "position": 16, "query": "AI healthcare" } ]
Revolutionizing Healthcare with Digital Health - Number Analytics	Revolutionizing Healthcare with Digital Health	https://www.numberanalytics.com	[ "Sarah Lee" ]	Artificial intelligence (AI) and machine learning (ML) are being increasingly used in healthcare to improve diagnosis, treatment, and patient ...	Harnessing the Power of Biomedical Informatics for Better Health Outcomes Revolutionizing Healthcare with Digital Health The healthcare industry is undergoing a significant transformation with the advent of digital health technologies. Digital health is revolutionizing the way healthcare is delivered, making it more accessible, efficient, and personalized. Biomedical informatics is playing a crucial role in driving this revolution by providing the tools and techniques necessary to analyze and interpret the vast amounts of healthcare data being generated. Digital Health Trends and Innovations The digital health landscape is rapidly evolving, with several trends and innovations emerging as key drivers of change. Some of the most significant developments include: Artificial Intelligence and Machine Learning in Healthcare Artificial intelligence (AI) and machine learning (ML) are being increasingly used in healthcare to improve diagnosis, treatment, and patient outcomes. AI-powered algorithms can analyze large datasets to identify patterns and predict patient outcomes, while ML can help personalize treatment plans. AI-powered chatbots are being used to improve patient engagement and provide personalized support[^1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749333/). ML algorithms are being used to analyze medical images and diagnose diseases more accurately[^2](https://www.nature.com/articles/s41746-020-00376-2). Internet of Things (IoT) and Wearable Devices The Internet of Things (IoT) and wearable devices are enabling the collection of real-time data on patient health and behavior. This data can be used to improve disease management and prevention. Wearable devices can track patient activity levels, sleep patterns, and other health metrics[^3](https://www.sciencedirect.com/science/article/pii/B9780128126113000125). IoT devices can be used to monitor patient vital signs and detect anomalies[^4](https://ieeexplore.ieee.org/document/9351603). Blockchain and Cybersecurity in Healthcare Blockchain technology is being explored for its potential to improve healthcare data security and interoperability. Blockchain can enable secure sharing of medical records and facilitate seamless communication between healthcare providers. Blockchain-based systems can secure medical records and protect patient data[^5](https://www.sciencedirect.com/science/article/pii/B9780128166387000458). Blockchain can enable secure sharing of medical research data[^6](https://www.nature.com/articles/s41467-020-19656-1). graph LR; A["Healthcare Data"] -->\|"Blockchain"\| B["Secure Sharing"]; B --> C["Interoperability"]; C --> D["Improved Patient Care"]; Biomedical Informatics Tools and Techniques Biomedical informatics is providing the tools and techniques necessary to analyze and interpret the vast amounts of healthcare data being generated. Some of the key tools and techniques include: Data Analytics and Visualization Data analytics and visualization are being used to gain insights into healthcare data and identify trends and patterns. Data analytics can help identify high-risk patients and predict patient outcomes[^7](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478244/). Data visualization can help communicate complex data insights to healthcare providers[^8](https://www.sciencedirect.com/science/article/pii/B9780128120383000139). Clinical Decision Support Systems Clinical decision support systems (CDSSs) are being used to provide healthcare providers with real-time guidance and support. CDSSs can help healthcare providers diagnose diseases more accurately[^9](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366454/). CDSSs can help personalize treatment plans[^10](https://www.sciencedirect.com/science/article/pii/B978012816638700046X). Health Information Exchange and Interoperability Health information exchange (HIE) and interoperability are critical for enabling seamless communication between healthcare providers. HIE can enable secure sharing of medical records[^11](https://www.healthit.gov/topic/interoperability/health-information-exchange). Interoperability can facilitate coordination of care between healthcare providers[^12](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7104633/). Future Directions of Digital Health The future of digital health is exciting and rapidly evolving. Some of the key areas of focus include: Personalized Medicine and Precision Health Personalized medicine and precision health are being enabled by advances in genomics and data analytics. Personalized medicine can help tailor treatment plans to individual patients[^13](https://www.nature.com/articles/s41588-020-00695-1). Precision health can help prevent diseases before they occur[^14](https://www.sciencedirect.com/science/article/pii/B9780128166387000471). Virtual and Augmented Reality in Healthcare Virtual and augmented reality (VR/AR) are being explored for their potential to improve patient outcomes and enhance the healthcare experience. VR/AR can be used to improve patient education and engagement[^15](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749334/). VR/AR can be used to enhance therapy and treatment plans[^16](https://ieeexplore.ieee.org/document/9351604). Addressing the Challenges and Limitations of Digital Health While digital health has the potential to revolutionize healthcare, there are several challenges and limitations that need to be addressed. Data security and privacy are major concerns in digital health[^17](https://www.sciencedirect.com/science/article/pii/B9780128166387000483). Interoperability and data standardization are critical for enabling seamless communication between healthcare providers[^18](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7104634/). The following table summarizes the key challenges and limitations of digital health: Challenge/Limitation Description Data Security and Privacy Protecting patient data from unauthorized access and breaches Interoperability and Data Standardization Enabling seamless communication between healthcare providers Regulatory Compliance Ensuring compliance with regulations such as HIPAA User Adoption and Engagement Encouraging healthcare providers and patients to adopt digital health technologies To address these challenges, it is essential to develop robust data security measures, promote interoperability and data standardization, and ensure regulatory compliance. Additionally, user-centered design and education can help promote user adoption and engagement. The following flowchart illustrates the key steps involved in addressing the challenges and limitations of digital health: graph LR; A["Identify Challenges"] -->\|"Data Security"\| B["Implement Robust Security Measures"]; A -->\|"Interoperability"\| C["Promote Data Standardization"]; A -->\|"Regulatory Compliance"\| D["Ensure HIPAA Compliance"]; A -->\|"User Adoption"\| E["User-Centered Design and Education"]; In conclusion, digital health is revolutionizing the healthcare landscape, and biomedical informatics is playing a crucial role in driving this revolution. By understanding the trends, tools, and techniques involved in digital health, we can unlock its full potential and improve patient outcomes. References FAQs What is digital health? Digital health refers to the use of digital technologies to improve healthcare delivery, patient outcomes, and healthcare efficiency. What is biomedical informatics? Biomedical informatics is the application of computational and informational techniques to understand and manage healthcare data. What are some examples of digital health technologies? Examples of digital health technologies include AI-powered chatbots, wearable devices, and telehealth platforms. What are the benefits of digital health? The benefits of digital health include improved patient outcomes, enhanced patient engagement, and increased healthcare efficiency. What are the challenges and limitations of digital health? The challenges and limitations of digital health include data security and privacy concerns, interoperability and data standardization issues, and regulatory compliance challenges.	2025-06-30T00:00:00		https://www.numberanalytics.com/blog/revolutionizing-healthcare-digital-health	[ { "date": "2025/06/30", "position": 93, "query": "artificial intelligence healthcare" } ]
Amazon CEO says AI will mean 'fewer people' do jobs that get ...	Amazon CEO Jassy says AI will lead to 'fewer people doing some of the jobs' that get automated	https://www.cnbc.com	[ "Annie Palmer", "In Annierpalmer" ]	Amazon CEO Andy Jassy said the rapid rollout of generative AI means the company will one day require fewer employees to do some of the jobs ...	Amazon CEO Andy Jassy said the rapid rollout of generative artificial intelligence means the company will one day require fewer employees to do some of the work that computers can handle. "Like with every technical transformation, there will be fewer people doing some of the jobs that the technology actually starts to automate," Jassy told CNBC's Jim Cramer in an interview Monday. "But there's going to be other jobs." Even as artificial intelligence eliminates the need for some roles, Amazon will continue to hire more employees in AI, robotics and elsewhere, Jassy said. Earlier this month, Jassy admitted that he expects the company's workforce to decline in the next few years as Amazon embraces generative AI and AI-powered software agents. He told staffers in a memo that it will be "hard to know exactly where this nets out over time" but that the corporate workforce will shrink as Amazon wrings more efficiencies out of the technology. It's a message that's making its way across the tech sector. Salesforce CEO Marc Benioff last week claimed AI is doing 30% to 50% of the work at his software vendor. Other companies such as Shopify and Microsoft have urged employees to adopt the technology in their daily work. The CEO of Klarna said in May that the online lender has managed to shrink its headcount by about 40%, in part due to investments in AI and natural attrition in its workforce. Jassy said Monday that AI will free employees from "rote work" and "make all our jobs more interesting," while enabling staffers to invent better services more quickly than before. Amazon and other tech companies have also been shrinking their workforces through rolling layoffs over the past several years. Amazon has cut more than 27,000 jobs since the start of 2022, and it's announced smaller, more targeted layoffs in its retail and devices units in recent months. Amazon shares are flat so far this year, underperforming the Nasdaq, which has gained 5.5%. The stock is about 10% below its record reached in February, while fellow megacaps Meta , Microsoft and Nvidia are all trading at or very near record highs.	2025-06-30T00:00:00	2025/06/30	https://www.cnbc.com/2025/06/30/amazon-ceo-says-ai-will-mean-fewer-people-do-jobs-that-get-automated.html	[ { "date": "2025/06/30", "position": 76, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 45, "query": "AI layoffs" }, { "date": "2025/06/30", "position": 78, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 81, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 81, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 80, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 76, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 81, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 81, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 79, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 81, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 83, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 80, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 81, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 83, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 84, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 84, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 82, "query": "generative AI jobs" }, { "date": "2025/06/30", "position": 11, "query": "AI layoffs" }, { "date": "2025/06/30", "position": 48, "query": "artificial intelligence layoffs" } ]
The tough job market for new college grads probably isn't all due to AI	The tough job market for new college grads probably isn't all due to AI	https://www.marketplace.org	[]	Unemployment for degree-holders age 22 to 27 is almost 6%, the highest it's been since the pandemic. And crucially, it's significantly worse ...	Last month the Anthropic’s CEO Dario Amodei made an alarming prediction: Artificial intelligence could wipe out half of entry-level white-collar jobs in the next one to five years. A look at the current job market for recent college graduates isn’t exactly reassuring. Unemployment for degree-holders age 22 to 27 is almost 6%, the highest it’s been since the pandemic. And crucially, it’s significantly worse than the unemployment rate for all workers, which hovers around 4%. That kind of inversion has very rarely been seen over the last three decades the Federal Reserve has been tracking. But it doesn’t necessarily mean we’re at the beginning of a white-collar apocalypse. It’s cold comfort to recent grads, like Yael Grimaldi, who just earned a bachelor's degree with honors from Santa Clara University Leavey School of Business. “I thought I would have a job lined up by graduation,” he said. He’s been looking for a job or internship in digital marketing, putting in about two applications a day at big companies and small ones, up and down the state of California. He’s had a few interviews, but no offers yet. “As a first generation student, I feel like there's a lot of pressure,” said Grimaldi. “I'm the first in my in my family to get a degree, and you know, it has a lot of value, but not as much as I thought it would freshman year.” The labor market advantages of a college degree have been eroding for at least 10 years, said economist David Deming at Harvard’s Project on the Workforce. “A college degree, for most young people who are thinking about it, is still a very good investment, but it's no longer the absolute guarantee that it once was,” he said, noting the wage premium commanded by college-educated workers has plateau’d since the 2010s. And the edge new grads had finding work began to dissipate in the mid-2010s partially because there are more of them. “The share of young people graduating from college has increased by about a third in the last two decades,” said Deming, “so there’s just many, many more people graduating, and that's a very good thing.” Meanwhile, he said we’re now seeing a slowdown in hiring that is cyclical. “You want to sort of think about a young college graduate like a capital investment,” he said. “When businesses are feeling confident about investments overall, they tend to hire more college graduates and when they’re less confident, they hire fewer.” Right now things are definitely uncertain. “Even if it's not a technical hiring freeze, I think a lot of companies are just kind of taking a step back,” said Rosella Graham who graduated from Middlebury College in Vermont in May. She studied International Politics, Economics and Spanish and interned last summer for the State Department. She’s looking for government jobs, which have become less numerous. She wonders if she’ll end up waiting tables or making lattes for now, like some of her friends have. “Thinking about a lot of friends that are going to wait out the kind of tumultuous job market right now by taking those other jobs — it just kind of frightens me that that is a reality,” she said. AI could be contributing but only about 6% of firms across the economy have adopted the technology according to Goldman Sachs. In tech, though it’s a different story. A report from venture capital firm SignalFire found the number of new grads hired by Big Tech fell 25% since just 2023 and UC Berkeley computer science professor James O’Brien believes AI is the driving force. Take a junior developer role, which he said is mostly tedious coding: “People call it boiler plate code, or, you know, drudge work or something. But it's also a really great way to learn.” Large language models can now handle that and do it a lot faster. O’Brien said Big Tech companies brag about how much of their code is written by AI at the same time they announce thousands of layoffs. Companies he advises, which used to ask him to recruit students, no longer need the help. And startups are getting smaller and smaller. “How many times do you have to get the same message for at some point you say, hey, maybe that message is the message,” O’Brien said. New grad Yael Grimaldi is still optimistic he’ll get a message about a job at some point. In the meantime, he’s using AI to build a website for his photography side hustle, and, just in case, applying to the Peace Corp.	2025-06-30T00:00:00	2025/06/30	https://www.marketplace.org/story/2025/06/30/why-college-grads-are-struggling-to-find-work	[ { "date": "2025/06/30", "position": 65, "query": "AI unemployment rate" }, { "date": "2025/06/30", "position": 90, "query": "AI unemployment rate" }, { "date": "2025/06/30", "position": 92, "query": "AI unemployment rate" }, { "date": "2025/06/30", "position": 92, "query": "AI unemployment rate" }, { "date": "2025/06/30", "position": 89, "query": "AI unemployment rate" }, { "date": "2025/06/30", "position": 91, "query": "AI unemployment rate" }, { "date": "2025/06/30", "position": 90, "query": "AI unemployment rate" }, { "date": "2025/06/30", "position": 86, "query": "AI unemployment rate" }, { "date": "2025/06/30", "position": 89, "query": "AI unemployment rate" }, { "date": "2025/06/30", "position": 87, "query": "AI unemployment rate" } ]
Which skill do you believe will take the longest to be replaced by AI?	Ask HN: Which skill do you believe will take the longest to be replaced by AI?	https://news.ycombinator.com	[]	There is a lot of debate whether AI will surpass humans in all economically viable skills (AGI, by one definition).	There is a lot of debate whether AI will surpass humans in all economically viable skills (AGI, by one definition). Regardless of whether this will happen, or when, many people already have lost their jobs in part due to the emerging capabilities of AI models, including writing, document analysis, design, art, etc. This leaves many in a position where they fear they will be next on the chopping block. Many assume physical tasks will take longer since it will take longer to build up, verify and test humanoid robots vs. some virtual AI agent. However, many believe the writing is on the wall either way, and those in domains involving using their hands or bodies will only have a few more years than the formerly employed white-collar class. Which skills then, or combinations of skills, do you believe will be safest for staying employed and useful if AI continues improving at the rate it has been for the past few years?	2025-06-30T00:00:00		https://news.ycombinator.com/item?id=44428788	[ { "date": "2025/06/30", "position": 95, "query": "AI skills gap" }, { "date": "2025/06/30", "position": 96, "query": "AI skills gap" }, { "date": "2025/06/30", "position": 96, "query": "AI skills gap" }, { "date": "2025/06/30", "position": 96, "query": "AI skills gap" }, { "date": "2025/06/30", "position": 95, "query": "AI skills gap" }, { "date": "2025/06/30", "position": 94, "query": "AI skills gap" }, { "date": "2025/06/30", "position": 98, "query": "AI skills gap" }, { "date": "2025/06/30", "position": 96, "query": "AI skills gap" } ]
Scientist Says Humans Will Reach the Singularity Within 20 Years	A Scientist Says Humans Will Reach the Singularity Within 20 Years	https://www.popularmechanics.com	[]	In that same interview with The Guardian, Kurzweil highlights the idea of a Universal Basic Income as a necessity rather than a fringe idea ...	Gear-obsessed editors choose every product we review. We may earn commission if you buy from a link. Why Trust Us? Here’s what you’ll learn when you read this story: Futurists have long debated the arrival of the singularity, when human and artificial intelligence will merge, a concept borrowed from the world of quantum physics. American computer scientist and futurist Ray Kurzweil has long argued that the singularity would likely occur around the middle of the 21st century, and with the rise of AI, his predictions are gaining more credence. In his book, The Singularity is Nearer, Kurzweil doubles down on those predictions and details how humanity’s intelligence will increase a millionfold via nanobots (among other things). You don’t exactly become a world-renowned futurist by making safe predictions. And while some of these past predictions haven’t exactly come to pass (Back to the Future Part II, specifically), these ideas help expand our thoughts on what exactly the future might look like. And no one makes futuristic predictions quite like Ray Kurzweil. An American computer scientist-turned-futurist, Kurzweil that humanity is headed toward what’s known as “the singularity,” when man and machine merge. In 1999, Kurzweil theorized that artificial general intelligence would be achieved once humanity could achieve a technology capable of a trillion calculations per second, which he pegged to occur in 2029. Experts at the time scoffed at the idea, figuring it’d be at least a century or more, but with Kurzweil’s timeline only a few years off—and talk of AGI spreading—that decades-old prediction is beginning to loom large. In his 2024 book, (a play on his 2005 book of the same name minus an “er”), Kurzweil doubles down on these ideas in the modern era of artificial intelligence. Not only is he "sticking with [his] five years” prediction, as he said in a TED Talk, Kurzweil also believes that humans will achieve a millionfold intelligence by 2045, aided by brain interfaces formed with nanobots non-invasively inserted into our capillaries. “We’re going to be a combination of our natural intelligence and our cybernetic intelligence,” Kurzweil said in an interview with The Guardian, “and it’s all going to be rolled into one. We are going to expand intelligence a millionfold by 2045, and it is going to deepen our awareness and consciousness.” While this idea subscribes to a merger more akin to physical intervention to bridge the gap between man and machine, other philosophers and AI experts agree that some form of merger is likely inevitable, and in some ways, is already beginning. In July 2024, Oxford’s Marcus du Sautoy and Nick Bostrom both expounded on the hopeful and harrowing possibilities of our AI future, and for both of them, a kind of synthesis appeared inevitable. “I think that we are headed toward a hybrid future,” Sautoy told Popular Mechanics. “We still believe that we are the only beings with a high level of consciousness. This is part of the whole Copernican journey that we are not unique. We’re not at the center.” Related Story Humans Could Acquire a New Form of Consciousness Of course, this “Brave New World” of a hybrid AI-human existence brings with it a plethora of issues both political and personal. What will humans do for jobs? Could we possibly live forever? Would that change the very idea of what it means to be human? Kurzweil, like many other futurists, is relatively optimistic on this front. In that same interview with The Guardian, Kurzweil highlights the idea of a Universal Basic Income as a necessity rather than a fringe idea currently supported in more progressive circles, and AI will bring unprecedented advancements in medicine, meaning the very idea of immortality isn’t out of the realm of possibility. “In the early 2030s we can expect to reach longevity escape velocity where every year of life we lose through aging we get back from scientific progress,” Kurzweil told The Guardian. “And as we move past that, we’ll actually get back more years. It isn’t a solid guarantee of living forever—there are still accidents—but your probability of dying won’t increase year to year.” Just like Back to the Future Part II predicted flying cars, so too could these technology-fueled utopias crumble to dust as these dates inch closer and closer. But 25 years ago, Kurzweil predicted we’d be rapidly approaching a major moment in humanity’s technological history at the tail end of this decade. Currently, no evidence suggests the contrary.	2025-06-30T00:00:00	2025/06/30	https://www.popularmechanics.com/science/a65253231/2045-singularity-ray-kurzweil-prediction/	[ { "date": "2025/06/30", "position": 97, "query": "universal basic income AI" }, { "date": "2025/06/30", "position": 98, "query": "universal basic income AI" }, { "date": "2025/06/30", "position": 97, "query": "universal basic income AI" }, { "date": "2025/06/30", "position": 96, "query": "universal basic income AI" }, { "date": "2025/06/30", "position": 97, "query": "universal basic income AI" }, { "date": "2025/06/30", "position": 95, "query": "universal basic income AI" }, { "date": "2025/06/30", "position": 94, "query": "universal basic income AI" }, { "date": "2025/06/30", "position": 97, "query": "universal basic income AI" } ]
87% of business leaders think AI agents will replace human ...	87% of business leaders think AI agents will force companies to redefine performance and upskill their human workers	https://finance.yahoo.com	[ "Brit Morse", "Mon", "Jun", "Min Read" ]	... employees if companies don't make big moves to upskill their workforce. Business leaders get real about the risk of AI replacing human workers.	Good morning! Companies are scrambling to introduce AI agents into their workflow at a rapid clip. But workers are afraid that this tech revolution may actually lead to their own professional demise, and a new study shows that they have good reason to be worried. Around 87% of business leaders believe that AI agents will force organizations to redefine performance metrics and upskill their employees in roles that AI could displace, according to management consulting firm KPMG’s latest AI Quarterly Pulse Survey. That includes providing additional training, creating new goals, or even changing their roles. “Our clients are no longer asking ‘if’ AI will transform their business, they’re asking ‘how fast’ it can be deployed,” notes Todd Lohr, head of ecosystems at KPMG. “This isn’t just about technology adoption, it’s about fundamental business transformation that requires reimagining how work gets done and how it is measured.” The deployment of AI agents across organizations has tripled since the fourth quarter of last year, according to the report. Around 82% of business leaders believe that AI agents will become valuable contributors within the next year, and the same number believe these agents will completely change the business landscape in the next two years. CEOs have recently become bolder about saying that AI could lead to leaner human workforces. The CEO of Anthropic said earlier this year that AI could eliminate half of entry level roles. The CEO of language learning app Duolingo told staff in April that they could only hire a new person if they first proved the task couldn’t be done with AI. And Meta recently announced plans to replace up to 90% of its human employees who review the platform’s privacy and societal risks with AI. Upskilling employees might be easier said than done, though. While two-thirds of leaders expect employees to update their AI skills, only a third say the companies they work for are providing policies around how the technology should be used, according to recent research from talent advisory The Adecco Group. A separate study from management consulting firm Oliver Wyman found that while 79% of workers want AI training, only 57% say such upskilling efforts made by their company have been inadequate. “As employers, we have a responsibility to help prepare current and future workers for the transition to a new era of work,” writes Edwige Sacco, head of workforce innovation at KPMG. “Investments in human-centric change management, modern ways of learning, proactive upskilling, and new human-AI collaboration models are essential for unlocking the long-term return on AI investments.”	2025-06-30T00:00:00		https://finance.yahoo.com/news/87-business-leaders-think-ai-124002076.html	[ { "date": "2025/06/30", "position": 97, "query": "AI workers" }, { "date": "2025/06/30", "position": 96, "query": "AI workers" }, { "date": "2025/06/30", "position": 96, "query": "AI workers" }, { "date": "2025/06/30", "position": 97, "query": "AI workers" }, { "date": "2025/06/30", "position": 95, "query": "AI workers" } ]
How much (little) are the AI companies making? \| by Cory Doctorow	How much (little) are the AI companies making?	https://doctorow.medium.com	[ "Cory Doctorow" ]	And AI is the greatest innovator of all (when it comes to accounting gimmicks). Since the dotcom era, tech companies have boasted about giving ...	If there’s one area where tech has shown a consistent aptitude for innovation, it’s in accounting tricks that make money-losing companies appear wildly profitable. And AI is the greatest innovator of all (when it comes to accounting gimmicks). Since the dotcom era, tech companies have boasted about giving stuff away but “making it up in volume,” inventing an ever-sweatier collection of shell-games that let them hide the business’s true profit and loss. The all-time world champeen of this kind of finance fraud is Masayoshi Son, the founder of Softbank, who acts as the bagman for the Saudi royals’ personal investments. Remember last decade when the tech press was all abuzz about “unicorns” — startups that were worth $1b? That was Son: he would take a startup like Wework, declare its brand to be worth $1b, invest an infinitesimal fraction of $1b in the company based on that valuation (sometimes with a rube co-investor) and declare the valuation to be “market-based.” A whole string of garbage companies achieved unicornhood by means of this unbelievably stupid trick: https://pluralistic.net/2022/05/27/voluntary-carbon-market/#trust-me Of course, every finance bro is familiar with Stein’s Law: “anything that can’t go on forever eventually stops.” Sure, the Saudi royals could be tapped to piss away $31b on Uber, losing $0.41 on every dollar for 13 years, but eventually they’re going to turn off the money spigot and attempt to flog their shares to retail and institutional suckers. To make that work, they have to invent new accounting tricks, like when Uber “sold” its failing overseas ride-hailing businesses to international rivals in exchange for stock, then declared that these companies’ illiquid stock had skyrocketed in value, tipping Uber into the black: https://pluralistic.net/2022/08/05/a-lousy-taxi/#a-giant-asterisk Even companies that are actually profitable (in the sense of bringing in more revenue than it costs to keep the business’s lights on) love to juice their stats, and the worst offenders are the Big Tech companies, who reap a vast commercial reward from creating the illusion that they are continuing to grow, even after they’ve dominated their sector. Take Google: once the company attained a 90% global search market-share, there were no more immediate prospects for growth. I mean, sure, they could raise a billion new humans to maturity and train them to be Google customers (e.g., the business plan for Google Classroom), but that takes more than a decade, and Google needed growth right away. So the company hatched a plan to make search worse, so that its existing users would have to search multiple times to get the information they sought, and each additional search would give Google another chance to show you an ad: https://pluralistic.net/2024/04/24/naming-names/#prabhakar-raghavan But that was small potatoes. What Google — and the rest of the tech sector — needed was a massive growth story, a story about how their companies, worth trillions of dollars, could double or triple in size in the coming years. There’s a kind of reflexive anti-capitalist critique that locates the drive to tell growth stories in ideology: “endless growth is the ideology of a tumor,” right? But spinning an endless growth story isn’t merely ideological. It’s a firmly materialistic undertaking. Companies that appear to be growing have market caps that are an order of magnitude larger than companies that are considered “mature” and at the end of their growth phase. For every dollar that Ford brings in, the market is willing to spend $8.60 on its stock. For every dollar Tesla brings in, the market is willing to spend $118 on its stock. That means that when Tesla and Ford compete to buy something — like another company, or the labor of highly sought after technical specialists — Tesla has a nearly unbeatable advantage. Rather than raiding its precious cash reserves to fund its offer, Tesla can offer stock. Ford can only spend as many dollars as it brings in through sales, but Tesla can make more stock, on demand, simply by typing numbers into a spreadsheet. So when Tesla bids against Ford, Ford has to use dollars, and Tesla can use shares. And even if the acquisition target — a key employee or a startup that’s on the acquisitions market — wants dollars instead of shares, Tesla can stake its shares as collateral for loans at a rate that’s 1,463% better than the rate Ford gets when it collateralizes a loan based on its own equity: https://pluralistic.net/2025/05/07/rah-rah-rasputin/#credulous-dolts In other words, if you can tell a convincing growth story, it’s much easier to grow. The corollary, though, is that when a growth company stops growing, when it becomes “mature,” it experiences a massive sell-off of its stock, as its share price plummets to a tenth or less of the old “growth” valuation. That’s why the biggest tech companies in the world have spent the past decade — the decade after they monopolized their sectors and conquered the world — pumping a series of progressively stupider bubbles: metaverse, cryptocurrency, and now, AI. Tech companies don’t need these ventures to be successful — they just need them to seem to be plausibly successful for long enough to keep the share price high until the next growth story heaves over the horizon. So long as Mister Market thinks tech is a “growth” sector and not a “mature” sector, tech bosses will be able to continue to pay for things with stock rather than cash, and their own stockholdings will continue to be valued at sky-high rates. That’s why AI is being crammed into absofuckingloutely everything. it’s why the button you used to tap to start a new chat summons up an AI that takes seven taps to banish again — it’s so tech companies can tell Wall Street that people are “using AI” which means that their companies are still part of a growth industry and thus entitled to gigantic price-to-earnings ratios: https://pluralistic.net/2025/05/02/kpis-off/#principal-agentic-ai-problem The reality, of course, is that people hate AI. Telling people that your product is “AI enabled” makes less likely to use it: https://www.tandfonline.com/doi/full/10.1080/19368623.2024.2368040#d1e1096 People — who have had an infinitude of AI crammed into down their throats — are already sick of AI. Policymakers and financiers — credulous dolts who fall for tech marketing hype every! fucking! time — are convinced that AI Is The Future. This presents a dilemma for tech companies, who research the hell out of how people actually use their products and thus must be extremely aware of how hated AI is, but whose leadership is desperate to show investors that they are about to experience explosive growth through the miracle of AI. The reality is that AI is a very bad business. It has dogshit unit economics. Unlike all the successful tech of the 21st century, each generation of AI is more expensive to make, not cheaper. And unlike the most profitable tech services of this century, AI gets more costly to operate the more users it has. You can be forgiven for not knowing this, though. As Ed Zitron points out in a long, excellent article about the credulity and impuissance of the tech press, the actual numbers suuuuuck: https://www.wheresyoured.at/make-fun-of-them/ Microsoft Spending: $80b in 2025 Projecting: $13b in 2025 Actually: $10b comes from Openai giving back compute credits Microsoft gave to Openai, bringing the true total to $3b. Meta Spending: $72b in 2025 Receiving: At most $600m in gross revenue from selling “smart” Raybans, which might not actually be loss-leaders, meaning it’s possible that they’re making less than $0.00. Amazon Spending: $100b in 2025 Projecting: $5b in revenue in 2025 Google Spending: $75b in 2025 Projecting: They won’t say, possibly zero. As Zitron points out: this industry is projecting $327b in spending this year, with $18b in revenue and zero profits. For comparison: smart watches are a $32b/year industry. Now, what about Openai? Well, they’re one of Masoyoshi Son’s special children, of a piece with Wework and Uber. Openai is projecting $12.7b in revenue this year, with losses of $14b. Add in a bunch of also-rans like Perplexity and Surge, and the revenue rises to $32.3b. But…if you chuck them in, you also get total exenditure of $370.8b. These are by no means the only funny numbers in the AI industry. Take “Stargate,” a data-center initiative with a price tag of $500b. Actual funds committed? $40b. These are terrible numbers, but also, these are some genuinely impressive accounting gimmicks. They are certain to keep the bubble pumping for months or perhaps years, convincing gullible bosses to fire talented employees and replace them with bumbling chatbots that will linger for years or decades, the asbestos in the walls of our high-tech civilization. If you’d like an essay-formatted version of this post to read or share, here’s a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog: https://pluralistic.net/2025/06/30/accounting-gaffs/#artificial-income	2025-06-30T00:00:00	2025/06/30	https://doctorow.medium.com/https-pluralistic-net-2025-06-30-accounting-gaffs-artificial-income-aff55b5655bf	[ { "date": "2025/06/30", "position": 81, "query": "AI employers" }, { "date": "2025/06/30", "position": 82, "query": "AI employers" }, { "date": "2025/06/30", "position": 80, "query": "AI employers" }, { "date": "2025/06/30", "position": 80, "query": "AI employers" }, { "date": "2025/06/30", "position": 84, "query": "AI employers" }, { "date": "2025/06/30", "position": 83, "query": "AI employers" } ]
87% of business leaders think AI agents will replace human ...	87% of business leaders think AI agents will force companies to redefine performance and upskill their human workers	https://fortune.com	[ "Brit Morse" ]	A separate study from management consulting firm Oliver Wyman found that while 79% of workers want AI training, only 57% say such upskilling ...	Good morning! Companies are scrambling to introduce AI agents into their workflow at a rapid clip. But workers are afraid that this tech revolution may actually lead to their own professional demise, and a new study shows that they have good reason to be worried. Around 87% of business leaders believe that AI agents will force organizations to redefine performance metrics and upskill their employees in roles that AI could displace, according to management consulting firm KPMG’s latest AI Quarterly Pulse Survey. That includes providing additional training, creating new goals, or even changing their roles. “Our clients are no longer asking ‘if’ AI will transform their business, they’re asking ‘how fast’ it can be deployed,” notes Todd Lohr, head of ecosystems at KPMG. “This isn’t just about technology adoption, it’s about fundamental business transformation that requires reimagining how work gets done and how it is measured.” The deployment of AI agents across organizations has tripled since the fourth quarter of last year, according to the report. Around 82% of business leaders believe that AI agents will become valuable contributors within the next year, and the same number believe these agents will completely change the business landscape in the next two years. CEOs have recently become bolder about saying that AI could lead to leaner human workforces. The CEO of Anthropic said earlier this year that AI could eliminate half of entry level roles. The CEO of language learning app Duolingo told staff in April that they could only hire a new person if they first proved the task couldn’t be done with AI. And Meta recently announced plans to replace up to 90% of its human employees who review the platform’s privacy and societal risks with AI. Upskilling employees might be easier said than done, though. While two-thirds of leaders expect employees to update their AI skills, only a third say the companies they work for are providing policies around how the technology should be used, according to recent research from talent advisory The Adecco Group. A separate study from management consulting firm Oliver Wyman found that while 79% of workers want AI training, only 57% say such upskilling efforts made by their company have been inadequate. “As employers, we have a responsibility to help prepare current and future workers for the transition to a new era of work,” writes Edwige Sacco, head of workforce innovation at KPMG. “Investments in human-centric change management, modern ways of learning, proactive upskilling, and new human-AI collaboration models are essential for unlocking the long-term return on AI investments.” Brit Morse [email protected] Around the Table A round-up of the most important HR headlines. Some users of AI coaches are finding them to be better than the professional human ones because they’re able to open up more easily. Wall Street Journal The AI frenzy is back once again as companies like Amazon and Meta are upgrading their spending budgets to prioritize the latest technology. New York Times California labor groups are pushing for legislation that would require businesses to notify workers when they use AI in the workplace. Bloomberg Watercooler Everything you need to know from Fortune. Keeping up with tech. Generative AI and AI agents are disrupting online shopping, and large e-commerce powerhouses like Walmart and Amazon may be impacted. —Jason Del Rey Career paths. For some executives, the road to success is a rather straightforward one, but the CEO of David’s Bridal has a much rockier start. —Emma Burleigh The impacts of RIFs. While job openings have broadly remained steady, opportunities in private-sector government contractors have plummeted, according to new data. —Sasha Rogelberg	2025-06-30T00:00:00	2025/06/30	https://fortune.com/2025/06/30/87-of-business-leaders-think-ai-agents-will-replace-human-employees-if-companies-dont-make-big-moves-to-upskill-their-workforce/	[ { "date": "2025/06/30", "position": 81, "query": "AI replacing workers" } ]
AI blamed for 80% increase in US layoffs - TechCentral.ie	AI blamed for 80% increase in US layoffs	https://www.techcentral.ie	[ "Niall Kitson" ]	This year, 696,309 layoffs have already been announced, an increase of 80% compared to 2024. This is according to data from Challenger, Gray & ...	AI blamed for 80% increase in US layoffs Amazon, Microsoft, and Google lead the way in headcount reduction in 2025 Trade The American labour market is undergoing major changes as the impact of artificial intelligence of the size of organisations becomes known. This year, 696,309 layoffs have already been announced, an increase of 80% compared to 2024. This is according to data from Challenger, Gray & Christmas, an international consulting firm specialising in labour market research and personnel strategy. The technology sector is being hit the hardest. So far, more than 74,000 jobs have been lost in that sector. This increase is mainly due to AI-driven automation. Companies like Amazon, Google, and Microsoft are using artificial intelligence to make their operations more efficient, reducing the need for staff. advertisement AI-related changes have already led to 20,000 layoffs in 2025, according to the report. The tech sector is feeling the impact of generative AI deeply and profoundly. In May alone, 10,598 layoffs were announced, bringing the total for 2025 to 74,716. That’s 35% more than in the same period last year. Companies are striving for greater efficiency and are increasingly using AI actively and purposefully. Amazon CEO Andy Jassy (pictured) admitted that his company needs fewer employees due to the integration of generative AI. Microsoft carried out several rounds of layoffs in May and June, resulting in about 6,000 job losses. Google also cut about a quarter of its Google TV team in April. Business AM	2025-06-30T00:00:00	2025/06/30	https://www.techcentral.ie/ai-blamed-for-80-increase-in-us-layoffs/	[ { "date": "2025/06/30", "position": 94, "query": "artificial intelligence layoffs" }, { "date": "2025/06/30", "position": 97, "query": "artificial intelligence layoffs" } ]
How is AI Changing the Hiring and Application Process for K-12?	How is AI Changing the Hiring and Application Process for K-12?	https://www.govtech.com	[ "Elizabeth Heubeck", "Education Week", "Bethesda" ]	Fisher suggests that K-12 recruiters and hiring managers experimenting with AI start with internal processes such as job descriptions, job ...	START INTERNALLY WITH LOW-STAKES TASKS THE SECRET TO USEFUL AI? BETTER PROMPTS WATCH FOR AI TRICKS IN APPLICANT MATERIALS HUMAN JUDGMENT STILL MATTERS MOST (TNS) — K-12 recruiters and administrators are racing throughout the summer to hire qualified candidates by the start of the upcoming academic year. Some may turn to a new tool to help them in the process: artificial intelligence.While current data show that only a small percentage of recruiters from various industries are tapping into AI, recent year-over-year growth suggests that's about to change. About a quarter of companies globally use AI for hiring or talent management — up from just 12 percent in 2023 — according to the 2024-25 Criteria Hiring Benchmarking Report.Recruiters in the K-12 space have joined the ranks of those interested in learning how AI can expedite the recruiting process. This March, 75 members of the American Association of School Personnel completed an online microcredential in AI, according to AASPA's executive director Kelly Coash Johnson, and more cohorts are planned. AI also is slated to be the focus of a professional learning session at the association's annual meeting in the fall.It's good timing, as job applicants have started to rely on AI to help them get ahead in the hiring process.Dale Fisher, assistant superintendent for human resources at Deerfield Public Schools District 109 in Illinois, has spent the last year or so researching best practices and dabbling in AI to support his district's recruitment efforts, and will be presenting his findings at AASPA's upcoming session on the subject. He shared with Education Week what he sees as some of AI's recruiting capabilities, and warned would-be users how to avoid its potential pitfalls.Fisher suggests that K-12 recruiters and hiring managers experimenting with AI start with internal processes such as job descriptions, job responsibilities, and interview questions — either by updating existing and potentially out-of-date documents or creating new ones. Fisher considers using AI to create these types of documents "low risk," largely because it allows the user a fair amount of control over the content being generated.But ultimately, district employees have to take responsibility over the content that AI produces, Fisher cautions."You still have to look at the final product and ask yourself: Is this something that I'm going to put my name on? Does this match what we really want as a system and as a team and as a district?" he said. "If you're blindly throwing your weight behind any [AI-generated] document, that's dangerous."How a district or school presents itself online can be the difference between someone clicking on one of its job descriptions or moving on in a competitive hiring market.As Fisher's district started to use LinkedIn to promote job postings, AI helped them stand out, he said."We went from no presence [on LinkedIn] at all to, in the last six months, putting up our job postings using a lot of great colorful graphics that AI helped generate," he said.Just as AI can generate eye-popping images, it can also craft messages to be used in job postings and other aspects of recruiting. But district employees taking an active role in prompting AI during this process — or any involving generating recruiting-oriented content — is critical to getting the intended results, Fisher said.Such prompts can influence all aspects of messaging, from the target audience to the tone, said Fisher, offering this example: If you're creating a job posting for a middle school teaching position, you can ask AI to consider warmth, empathy, and an inviting tone."If you're not good at prompting AI, that leads to bad data going in, and bad data coming out. You actually have to practice how you ask [AI] the questions," Fisher said. "Once you get good at asking the questions, the output suddenly makes exponential leaps in credibility."AI advertisers tout its far-reaching powers, from scanning "millions of resumes" in real-time to pinpointing the perfect job candidate for an open position. But users should exercise caution, Fisher advises.For starters, "millions of candidates" seeking K-12 positions likely don't exist these days. In fact, in a National Center for Education Statistics' School Pulse Panel that collected data from 1,392 public schools in August 2024, 62 percent of respondents said "too few candidates applying" was a top challenge.Even if there were a healthy number of job candidates vying for positions, Fisher warns against allowing AI to be the sole vetting source. One of his main concerns? Bias."Bias is, to me, one of the scariest parts about being in HR," Fisher said. "And if you're solely reliant on AI to screen out candidates, that could be dangerous."If, for example, a district historically hired candidates mostly from a limited pool — say, from local universities or a certain racial/ethnic background — the AI tool might learn to prefer similar profiles and deprioritize more diverse candidates, Fisher said.District employees can minimize this potential for bias by vigilantly interjecting "prompting" questions throughout the process: "We teach people as they start to use AI to continually ask it, as it generates a result, 'Is there potentially any bias in your response?'" Fisher said.District human resources should also keep in mind that some of the resumes or cover letters applicants are submitting are generated by AI.And some of that AI-generated content is designed to slip through the cracks. Some job seekers purportedly are embedding "hidden language" into resumes that AI can detect, but the human eye won't — for instance, adding phrases such as "I'm the best candidate for the position" in white font, which AI takes at face value.Fisher said he's not sure whether this example of hidden language has actually happened or is, rather, the stuff of modern-day recruiting myths. But there are still ways that recruiters can avoid falling into such traps, he said. Again, it comes down to prompting."You could ask AI to look at the formatting of the document and tell you if there's something that stands out as hidden," Fisher said. "Ask AI: Are there any font color changes? Is there any language that you would perceive to be hidden?"Recruiters can enlist AI for just about every aspect of the hiring process — even assessing job candidates. Whether it actually saves (human) recruiters time and effort in the long run, as advertisers suggest it does, remains to be seen. But for now, even AI enthusiasts like Fisher plan to keep interactions between job candidates and recruiters limited to humans."Our ability to do a phone interview based on questions where we're identifying specific things that we're trying to hone in on is not going to be something that AI can produce on the fly during my career," Fisher said. "Phone interviews matter. It still comes down to human interaction, in my opinion."	2025-06-30T00:00:00	2025/06/30	https://www.govtech.com/education/k-12/how-is-ai-changing-the-hiring-and-application-process-for-k-12	[ { "date": "2025/06/30", "position": 46, "query": "AI hiring" } ]
The AI skills gap is real. Sort of. - LinkedIn	The AI skills gap is real. Sort of.	https://www.linkedin.com	[]	Here's what the data actually reveals: the AI skills gap isn't technical - it's cognitive. The World Economic Forum's latest Skills Report ...	I've been having the same conversation on repeat lately: everyone's panicking about AI taking jobs, while completely missing the actual problem staring us in the face. So naturally, I did what I always do when my feelz get overwhelmed by the noise - I turned to the research. Microsoft's 2024 Work Trend Index shows 75% of knowledge workers are already using generative AI, yet 53% are terrified it makes them look replaceable. Classic, right? We're using the thing we're afraid of, which tells you everything about how poorly we're handling this transition. Here's what the data actually reveals: the AI skills gap isn't technical - it's cognitive. The World Economic Forum's latest Skills Report hammers this home beautifully. While everyone's obsessing over prompt engineering and tool mastery, the real demand is for uniquely human capabilities: creative problem-solving, emotional intelligence, and adaptive thinking. But here's where it gets interesting (and where most organisations are getting it spectacularly wrong): they're treating AI adoption like learning Excel. Spoiler alert - it's not. Research from MIT's Computer Science and Artificial Intelligence Laboratory shows that successful human-AI collaboration requires what they call "cognitive complementarity" - understanding not just how to use AI, but when NOT to use it, how to validate its outputs, and critically, how to maintain human judgment when the stakes matter. The organisations actually winning aren't just training people on ChatGPT. They're developing professionals who can think strategically about human-AI partnerships. These people understand that AI is brilliant at pattern recognition and terrible at context, exceptional at speed and hopeless at wisdom. For those of us in talent development, this represents a massive opportunity (assuming we don't cock it up). The demand for coaching that bridges technical AI literacy with human capability development has never been higher. But - and this is crucial - it requires us to actually understand what we're developing, not just throwing people at the latest AI course and hoping for the best. The bottom line: Stop competing with AI. Start thinking about how to make it work for you, not the other way around. References (a.k.a, if you feel like getting nerdy, there's some interesting reading below):	2025-06-30T00:00:00		https://www.linkedin.com/pulse/ai-skills-gap-real-sort-mohsin-siddiqui-fcipd--jzrqf	[ { "date": "2025/06/30", "position": 67, "query": "AI skills gap" } ]
Gemini in Classroom: No-cost AI tools that amplify teaching ...	Gemini in Classroom: No-cost AI tools that amplify teaching and learning	https://blog.google	[ "Cinthya Mohr", "Director Of User Experience", "Google For Education", "Keyword Team", "Tom Chapman", "Andy Russell", "Brian Hendricks", "Akshay Kirtikar", "Colin Marson", "Zahra Thompson" ]	This includes over 30 new AI tools to help teachers create content, brainstorm ideas and differentiate content for students. In the coming months, teacher-led ...	Energize teaching and learning with Gemini in Classroom Create engaging content and resources Starting today and rolling out globally over the coming weeks in English, educators with Google Workspace for Education accounts will be able to generate content with Gemini from a central destination in Classroom. With access to more than 30 AI tools, educators can get help kickstarting lessons, brainstorming ideas and differentiating content for students. Early pilot participants have already been sharing how much impact Gemini in Classroom is bringing to their day-to-day. Mariam Fan, a language and robotics teacher, said, “Gemini in Classroom saves me hours on planning and support, fostering a more inclusive and engaging classroom." Technology teacher, Mike Amante, called it “the ultimate teaching assistant—always available, always helpful.” Chris Webb has been especially using the rubric generation tool while planning for his math classes, “taking the repetitive task of making a rubric, and turning it into a quick and easy one, bringing your rubric right into Classroom in a matter of seconds."	2025-06-30T00:00:00	2025/06/30	https://blog.google/outreach-initiatives/education/classroom-ai-features/	[ { "date": "2025/06/30", "position": 8, "query": "AI education" } ]
Pledge to America's Youth	Pledge to America’s Youth	https://www.whitehouse.gov	[]	Advancing Artificial Intelligence Education for American Youth · Read Fact Sheet » · President Donald J. Trump Advances AI Education for American Youth. Stay Up ...	Pledge to America’s Youth: Investing in AI Education As of 6/30/2025 View the organizations investing in America’s youth Stay Up To Date On This Initiative:	2025-06-30T00:00:00		https://www.whitehouse.gov/edai/	[ { "date": "2025/06/30", "position": 34, "query": "AI education" } ]
Teaching Information and AI Literacy - Artificial Intelligence ...	Artificial Intelligence (AI)	https://guides.lib.utexas.edu	[ "Ut Libraries Tls" ]	This page provides resources for instructors interested in engaging their students with generative AI as part of the research process.	This page provides resources for instructors interested in engaging their students with generative AI as part of the research process. Exploring generative AI tools as part of the research process provides an opportunity to teach students how to think critically about information and the tools we use to discover and create it, which is fundamental to both information literacy and AI literacy.	2025-06-30T00:00:00		https://guides.lib.utexas.edu/AI/teaching	[ { "date": "2025/06/30", "position": 72, "query": "AI education" } ]
Inside the growth of the top AI companies on Stripe	Inside the growth of the top AI companies on Stripe	https://stripe.com	[ "Lauren Thomas" ]	AI companies are rewriting the rules of growth. In our new report, Indexing the AI economy, we explore the latest trends and strategies in the AI space.	ElevenLabs surged to a $3 billion valuation in just 2.5 years. Cursor, the AI-powered coding assistant, grew to over $100 million in annual recurring revenue in 3. Bolt—which lets users prompt, run, edit, and deploy full-stack web and mobile apps—hit $20 million in annual recurring revenue in just 2 months. AI companies are rewriting the rules of growth. At Stripe, which powers 78% of the Forbes AI 50, we dug into the data to better understand how these AI companies are racing ahead. In a new report, Indexing the AI economy, we share what we’ve learned from an analysis of the top 100 AI companies on Stripe: AI startups are hitting important revenue milestones much faster than previous generations of tech startups, including SaaS startups. AI companies are expanding internationally right from the start, quickly becoming global businesses. New business models and monetization strategies are emerging, driving accelerated revenue growth and adoption. In this post, we’ll share a preview of our data on revenue milestones and adoption. For the global picture, and a glimpse into the future of AI monetization, please download the full report. AI growth is rapid and accelerating The top 100 AI companies on Stripe achieved annualized revenues of $1 million in a median period of just 11.5 months—about 4 months ahead of the fastest-growing SaaS companies at the height of the subscription boom. And AI company growth is accelerating: the data shows younger AI companies (founded 2020–2023) have reached major revenue milestones about three times faster than those founded before 2020. This revenue growth reflects surging demand, and it suggests an opportunity for other types of businesses. For example, Intercom, a customer support platform founded in 2011, was quick to monetize the new AI boom when ChatGPT launched in December 2022. In just three months, Intercom rolled out the first of a new generation of AI agents that leveraged the new technology. We’ve seen the accelerating adoption and monetization of AI create a powerful cycle of investment, innovation, and global expansion. Download Indexing the AI Economy to understand the metrics behind the AI headlines.	2025-06-30T00:00:00		https://stripe.com/blog/inside-the-growth-of-the-top-ai-companies-on-stripe	[ { "date": "2025/06/30", "position": 13, "query": "AI employers" } ]
Artificial Intelligence Insights	Artificial Intelligence	https://www.bain.com	[]	Explore Bain's artificial intelligence insights, offering expert analysis and research on AI trends, applications, and strategies to drive business success.	AI has reached an inflection point, offering tangible benefits across industries and business functions. Informed by our AI consulting work, these insights explore how early adopters are taking advantage of the opportunity—and the challenges many face with integration.	2025-06-30T00:00:00		https://www.bain.com/insights/topics/ai/	[ { "date": "2025/06/30", "position": 38, "query": "AI employers" } ]
AI and journalism: this could be the beginning of a great ...	AI and journalism: this could be the beginning of a great codependency	https://letraslibres.com	[ "Marga Zambrana", "Miguel Ángel García Díaz", "Michael Reid", "Letras Libres", "Guillermo Valdés Castellanos", "Es Periodista. Ha Cubierto Europa", "Asia Y Medio Oriente Para Medios Como Associated Press Y The Guardian", "Juan Carlos Romero Puga", "Enrique Krauze", "Ricardo Baruch" ]	These days, AI is not only transforming news production, it is also shaping the very infrastructure of the information ecosystem, from newsrooms to distribution ...	AÑADIR A FAVORITOS Please login to bookmark Close Nombre de usuario o dirección de correo Contraseña Recuérdame Artificial intelligence (AI) has arrived in journalism as a promise: fast, inevitable, and transformative. Though imperceptible from the outside, its impact is irreversible and is redefining the speed and scope of journalism from within. At the same time, this fruit of the tree of knowledge comes with structural risks that are not being addressed in public discourse. These days, AI is not only transforming news production, it is also shaping the very infrastructure of the information ecosystem, from newsrooms to distribution. The result? The media, once proud and quixotic guardians of editorial autonomy, are beginning to look like chain smokers, perfectly aware of their dependence on a system that can destroy them, but unable to kick the habit. Or willing submission. The danger is not only technological, but political, ethical, and existential. We must ask ourselves whether we are witnessing, as suggested by Felix Simon, a researcher at the Reuters Institute for the Study of Journalism, a “capture of infrastructure” that threatens the very foundations of independent journalism. Or, as Peter Loge, director of the School of Media and Public Affairs (SMPA) at The George Washington University, the “assisted suicide” of newsrooms, caught between algorithmic efficiency and the abandonment of their mission. Captures, dependencies, vassalage In his 2023 article “Escape me if you can: How AI reshapes news organizations’ dependency on platform companies,” Simon introduces the concept of “infrastructure capture” to describe the phenomenon whereby private companies—technology platforms—not only provide tools to the media, but also design and control the environments in which journalistic content is created, circulated, and monetized. It is not simply a matter of the media using third-party AI, but rather that they operate within closed systems (owned by Amazon, Google, OpenAI, or Microsoft) that set the rules of the game. According to Simon, “whether this will have a significant impact on editorial independence remains to be seen,” but everything points to the path toward such capture already being paved. The perverse part is that this capture need not be coercive. All it takes are so-called “lock-in effects”—increasing dependency whereby, once an organization integrates a foreign infrastructure, the costs of abandoning it become prohibitive. Migrating to another system or building one of your own is, in practice, unfeasible. Like frogs boiled over low heat, the media barely notice how their room for maneuver diminishes with each step. Simon argues that this situation turns the media into “technological vassals,” trapped in relationships of dependency that sooner or later compromise their ability to decide what, how, and for whom they report. Beyond direct capture, Simon draws attention to the indirect effects that AI has on the news industry. It is not that a platform decides to censor local media or uncomfortable investigative reports; that would be too crude, almost a nineteenth-century scenario. The real threat is more elegant and therefore more lethal: that journalism will end up competing on an uneven playing field against a barrage of automatically generated content that pretends to be news. In their own words: “The growing use of AI on digital platforms and the potential risks to the visibility of journalistic content could lead to a progressive hollowing out of the news industry in general.” Particularly vulnerable in this context is local journalism, already hit hard by the economic crisis and the advertising exodus to digital platforms. And, of course, precarious journalists. Thus, while the mainstream media and journalists struggle to survive in a market saturated with AI-generated fake news, independent journalism, an uncomfortable witness to corruption, injustice, and inequality, to giants and windmills, risks becoming an archaeological rarity, relevant only to nostalgic academics and the occasional collector. The mirage of efficiency Peter Loge offers another equally crucial perspective: the mirage of efficiency. AI promises speed, volume, and cost reduction, irresistible temptations for executives who think in terms of quarterly results. However, Loge warns that “newsrooms may be seduced by efficiency and forget that their purpose is not to maximize clicks, but to serve the public interest.” It’s easy to fall into the trap. If producing ten times more content costs half as much, what executive is going to stop and consider whether that content has value? Why ask whether it maintains the rigor, depth, or social responsibility that have historically defined journalism? As Simon puts it, “Whether an organization acts in accordance with journalistic standards has little to do with technology and everything to do with how it conceives its mission.” The disturbing reality is, therefore—as always—that AI or any technological advance, whether the printing press or the internet, does not in itself degrade journalism, but rather it is those responsible for the media who decide, consciously or unconsciously, to sacrifice quality for volume, accuracy for immediacy, truth for profitability. But the machine poses an added danger. The impact of AI is not limited to content generation. It also reconfigures distribution channels: what news the public sees, in what order, with what headlines, with what priorities. Simon points out that this algorithmic control poses serious risks of bias and accidental misinformation. AI can amplify erroneous content without any explicit intention to deceive; all it takes is poor model training or poor optimization of the recommendation algorithm. The danger is that, in an environment where visibility increasingly depends on opaque formulas, journalistic quality criteria will be buried under metrics such as clicks, reading times, or engagement. To counteract this drift, Simon recommends that media outlets adopt safeguards such as rigorous human verification of any AI-generated or assisted content, systematic testing before implementing automated systems, and active collaboration with universities and other media outlets to share best practices. In a world where algorithms write headlines, draft summaries, and optimize virality, the only real defense of journalism is ethics. “No one directly forces publishers to use AI or decide exactly how they should use it,” Simon reminds us. The decision, in the end, is human. And deeply political. AI opens up enormous possibilities for investigating corruption more thoroughly, analyzing large databases, and improving the accessibility of news. At the same time, it can be used to regurgitate low-quality content that simulates depth. We cannot blame AI for this, but rather humans. And what about the role of governments? Don’t expect a cavalry charge. When it comes to state intervention, we cannot place too much trust in magic solutions from governments. And in the current populist drift, it is better that they do not intervene. Neither Simon nor Loge comment on this. In any case, skepticism is well founded: how can a political power that barely understands technology legislate effectively on it? The great codependency Far from being a simple instrumental collaboration, the relationship between AI and journalism is shaping up to be a toxic codependency. The media need the tools that technology offers to survive in a fiercely competitive market. But at the same time, every step they take toward that dependence erodes their autonomy, their credibility, and ultimately their purpose of existence. Beyond the internal use of artificial intelligence tools, traditional media outlets are embracing an even more radical trend: selling their content directly to AI platforms to feed their language models. Companies such as OpenAI, Mistral, and Meta have signed agreements with groups such as Reuters, The Guardian, AFP, Prisa Media, and Schibsted. The logic is understandable: new avenues of monetization, defense of copyright against indiscriminate use, and enhanced visibility. At the same time, AI itself can provide the technical solutions for verifying news content. These two developments deserve more detailed and comprehensive analysis. The dilemma is simple and brutal. Either journalism tames AI to serve its ethical purpose, or AI will tame journalism to serve its commercial purpose. The love of truth should unite man and machine. AI, let us remember, is not epistemologically competent. It does not know what is true or false: it only predicts what, statistically, should sound plausible. As Felix Simon warns, “the risk of factually inaccurate information appearing in news content can reasonably be controlled,” but only if humans impose strict limits. In other words, AI cannot distinguish truth from a plausible photocopy. Worse still, in an environment where the volume of content is multiplying exponentially, how can we distinguish real news from the avalanche of plausibilities designed to distract us? If the visibility of information is left in the hands of algorithms optimized to maximize engagement rather than safeguard truthfulness, truth risks becoming a luxury, a secondary concern at best. Peter Loge, for his part, reminds us that the journalistic commitment is not to efficiency but to the public interest, which presupposes an active search for the truth, not its simulation. AI can be an ally in this task, for example, by analyzing large databases and uncovering hidden patterns, but it can also be the unwitting accomplice of mass trivialization if clear limits are not established. Perhaps the duty of journalism in the age of AI is to distrust not only algorithms, but also the fascination they exert. Because if the goal ceases to be the truth and becomes simply the optimized production of viral content, what will die is not the news business, but the very idea of journalism. Journalism must remember, with a Hippocratic oath, that its purpose is not to sound true, but to be true.	2025-06-30T00:00:00	2025/06/30	https://letraslibres.com/politica/ai-and-journalism-this-could-be-the-beginning-of-a-great-codependency/30/06/2025/	[ { "date": "2025/06/30", "position": 10, "query": "AI journalism" }, { "date": "2025/06/30", "position": 7, "query": "artificial intelligence journalism" } ]
Journalism research news	Journalism research news	https://journalismresearchnews.org	[]	The study “The Human-AI Partnership in Romanian Newsrooms: AI as Both a News Topic and a Tool” by Georgeta Drula from University of Bucharest was a two-part ...	The review article “Handshake or standoff? Global media and the high stakes of Sino–American diplomacy” by Xiaoling Zhang from Xi’an Jiaotong–Liverpool University looked at media portrayals of the summit between Xi and Biden in San Francisco November 2023 through analyzing other research articles. The media portrayal was not investigated just in China and the US, … Continued	2025-06-30T00:00:00		https://journalismresearchnews.org/	[ { "date": "2025/06/30", "position": 55, "query": "AI journalism" }, { "date": "2025/06/30", "position": 57, "query": "artificial intelligence journalism" } ]
Salesforce CEO ignites firestorm after layoffs and praise for AI	Salesforce CEO ignites firestorm after layoffs and praise for AI	https://www.washingtonexaminer.com	[ "Barnini Chakraborty" ]	In May, cybersecurity software maker CrowdStrike announced it planned to lay off 500 employees, a move CEO George Kurtz said reflected the dominance of AI. “AI ...	Marc Benioff, CEO and cofounder of San Francisco-based software giant Salesforce, recently ignited a firestorm after claiming that artificial intelligence does up to “50% of the work” at his cloud computing company. Benioff’s comments on robot labor came after his company, San Francisco’s top employer, cut 1,000 positions this year. Salesforce is one of several companies across the tech industry that have had massive layoffs. In this photo taken Tuesday, Oct. 30, 2018, Salesforce CEO Marc Benioff speaks at a luncheon in San Francisco. (AP Photo/Eric Risberg, File) In May, cybersecurity software maker CrowdStrike announced it planned to lay off 500 employees, a move CEO George Kurtz said reflected the dominance of AI. “AI has always been foundational to how we operate,” Kurtz wrote in a memo included in a securities filing. “AI flattens our hiring curve, and helps us innovate from idea to product faster. It streamlines go-to-market, improves customer outcomes, and drives efficiencies across both the front and back office. AI is a force multiplier throughout the business.” Klarna CEO Sebastian Siemiatkowski said his company has cut its workforce by 40%, citing its investment in AI as a key factor. Amazon CEO Andy Jassy echoed a similar approach, stating that the tech giant plans to use AI to streamline operations and reduce headcount. Benioff tried to put a positive spin on his comments by saying the labor bots taking over duties performed by humans freed them up so the human employees can “do higher value work.” “AI is doing 30 to 50% of the work at Salesforce now, and I think that will, you know, continue,” he said on Bloomberg’s The Circuit with Emily Chang. “All of us have to get our head around this idea that AI can do things that before we were doing, and we can move on to do higher value work.” Benioff estimated that his software company has reached about 93% accuracy with AI technology. “It’s pretty good,” he said, but it’s not “realistic” to hit 100%. He added that other vendors are at “much lower levels because they don’t have as much data and metadata” to build higher accuracy. Benioff said Salesforce is marketing its AI tools on their ability to replace human labor, which raises ethical questions for the CEOs using them. “It’s a digital labor revolution,” he said. “We’re probably looking at $3 to $12 trillion of digital labor getting deployed. And that digital labor is going to be everything from AI to agents to robots. And I do think CEOs have to make sure their values are in the right place and that values bring value.” Benioff’s comments that AI was doing up to 50% of the work at Salesforce were met with backlash, including some in his own company pushing back on his assessment. But to industry observers such as Professor Saikat Chaudhuri, faculty director of the Management, Entrepreneurship, & Technology Program at the University of California, Berkeley’s Haas School of Business, Benioff was just stating the obvious. “There’s no doubt that AI agents are replacing, and will replace, a substantial chunk of the workforce,” Chaudhuri told the San Francisco Chronicle. Chaudhuri likened the current moment to the Internet Revolution. This era upended industries, from print media to brick-and-mortar retail, causing widespread disruption before ushering in a wave of new opportunities. “It became something that people had to acknowledge,” he said, noting that while some jobs vanished, new ones emerged. SUPREME COURT TAKES UP GOP CHALLENGE TO FEC COORDINATED SPENDING LIMITS Benioff’s enthusiasm for AI is far from unique. According to a new survey titled The Labor Market Effects of Generative Artificial Intelligence, 43.2% of firms nationwide now report using generative AI in the workplace, up 10% since December. “It’s increasing very rapidly, even surprisingly,” Jon Hartley, a policy fellow at Stanford’s Hoover Institution and the survey’s lead author, said, adding that the results “have several implications for policymakers, businesses, and researchers navigating the evolving landscape shaped by the integration of Generative AI into the global economy.”	2025-06-30T00:00:00	2025/06/30	https://www.washingtonexaminer.com/policy/technology/3458216/salesforce-ceo-marc-benioff-layoffs-praise-artificial-intelligence/	[ { "date": "2025/06/30", "position": 49, "query": "AI layoffs" } ]
Half of Managers Use AI To Determine Who Gets Promoted ...	Half of Managers Use AI To Determine Who Gets Promoted and Fired	https://www.resumebuilder.com	[]	A majority of these managers use AI to determine raises (78%), promotions (77%), layoffs (66%), and even terminations (64%); More than 1 in 5 frequently let ...	According to a new Resume Builder survey of 1,342 U.S. managers with direct reports, a majority of those using AI at work are relying on it to make high-stakes personnel decisions, including who gets promoted, who gets a raise, and who gets fired. Key findings include: 6 in 10 managers rely on AI to make decisions about their direct reports A majority of these managers use AI to determine raises (78%), promotions (77%), layoffs (66%), and even terminations (64%) More than 1 in 5 frequently let AI make final decisions without human input Two-thirds of managers using AI to manage employees haven’t received any formal AI training Nearly half of managers were tasked with assessing if AI can replace their reports 6 in 10 Managers Use AI To Make Decisions About Their Direct Reports About 65% of managers say they use AI tools at work, and among them, nearly all (94%) use them to make decisions about the people who report to them. When asked which tool they rely on most, ChatGPT takes the top spot, with 53% of AI-using managers citing it as their go-to. About 29% say they primarily use Microsoft’s Copilot, while 16% say they mostly use Google’s Gemini. Just 3% say they primarily use a different AI tool. Managers use AI to manage their teams in a variety of ways. Nearly all (97%) use it to create training materials, 94% to build employee development plans, 91% to assess performance, and 88% to draft performance improvement plans (PIPs). A majority also use AI to determine raises (78%), promotions (77%), layoffs (66%), and even terminations (64%). Nearly half say they use AI all the time or often for several of these tasks. 1 in 5 Managers Are Often Allowing AI To Make Final Decisions Among managers who use AI to help manage their teams, a majority (71%) express confidence in AI’s ability to make fair and unbiased decisions about employees. A notable share of managers let AI operate with limited oversight. More than 20% say they allow AI to make decisions without human input either all the time (5%) or often (16%), while another 24% sometimes do. However, nearly all managers say they are willing to step in if they disagree with an AI-driven recommendation. Two-Thirds of Managers Haven’t Received Formal Training on Using AI To Manage People Only one-third (32%) of managers using AI to manage people say they’ve received formal training on ethically using AI in managing people, while 43% have received informal guidance. Nearly one in four (24%) say they’ve received no training at all. Stacie Haller, chief career advisor at Resume Builder, says risks arise when managers rely on AI to make decisions without proper training. “It’s essential not to lose the ‘people’ in people management. While AI can support data-driven insights, it lacks context, empathy, and judgment. AI outcomes reflect the data it’s given, which can be flawed, biased, or manipulated. Organizations have a responsibility to implement AI ethically to avoid legal liability, protect their culture, and maintain trust among employees,” says Haller. A majority of managers say their company encourages them to use AI in people management. Haller explains that companies encourage managers to use it to improve efficiency, enable faster decision-making, reduce overhead, and support data-driven insights that enhance productivity and scalability. However, she notes that for AI to be truly effective in people management, it must be implemented thoughtfully, used responsibly, and always paired with human oversight. “Organizations must provide proper training and clear guidelines around AI, or they risk unfair decisions and erosion of employee trust,” emphasizes Haller. 1 in 4 Managers Have Replaced Their Direct Reports With AI About 46% of respondents using AI in people management say they were tasked with evaluating whether AI could replace a position. Among those managers, 57% determined AI could replace the position and 43% followed through and replaced the human position with AI. Methodology This survey, launched on June 24, 2025, was commissioned by ResumeBuilder.com and conducted online by the polling platform Pollfish. Overall, 1,342 U.S. full-time manager-level employees were surveyed. To qualify for the survey, all participants had to be at least 25 years old, have a household income of at least $75,000, hold an associate degree or a higher level of education, have a managerial-level role, and work at a company with more than 11 employees. Respondents also had to indicate that they currently have employees who report directly to them. For all media inquiries, contact [email protected].	2025-06-30T00:00:00		https://www.resumebuilder.com/half-of-managers-use-ai-to-determine-who-gets-promoted-and-fired/	[ { "date": "2025/06/30", "position": 64, "query": "AI layoffs" } ]
Entry-level jobs in freefall after launch of ChatGPT	Entry-level jobs in freefall after launch of ChatGPT	https://www.telegraph.co.uk	[ "Matthew Field", "Senior Technology Reporter" ]	Entry-level jobs are in freefall as the rise of AI chatbots such as ChatGPT causes low-paying and graduate roles to disappear.	Entry-level jobs are in freefall as the rise of AI chatbots such as ChatGPT causes low-paying and graduate roles to disappear. Recently released data shows that the number of entry-level roles being advertised has fallen by a third since the launch of OpenAI’s chatbot in November 2022. There were 214,934 entry-level jobs on offer in May this year, down by 32pc from just three years ago, according to figures from online jobs board Adzuna. This decline is outpacing the number of overall vacancies, which have fallen from 1,091,909 to 858,465, or 21pc, over the same period. It comes after The Telegraph reported earlier this month that graduate hiring in the City had also dropped off dramatically since the launch of ChatGPT. This was particularly relevant in the professional services sector, where AI is threatening to automate more mundane tasks carried out by junior accountants and consultants. Data from jobs board Indeed found Britain’s Big Four accountancy firms had posted 44pc fewer adverts for graduate roles this year compared with 2023. KPMG had also cut its graduate recruitment scheme by 29pc, while Deloitte had cut its own programme by 18pc. According to Adzuna’s data, graduate jobs fell 4.2pc in May and are 28.4pc below their level at the same time last year. Overall, graduate hiring is at its lowest level since July 2020.	2025-06-30T00:00:00	2025/06/30	https://www.telegraph.co.uk/business/2025/06/30/entry-level-jobs-in-free-fall-after-launch-of-chatgpt/	[ { "date": "2025/06/30", "position": 71, "query": "ChatGPT employment impact" } ]
AI And the Future of Work: The Impact of Jobs and Skills	AI And the Future of Work: The Impact of Jobs and Skills	https://redresscompliance.com	[ "Fredrik Filipsson", "Fredrik Filipsson Has Years Of Experience In Oracle License Management", "Including Nine Years Working At Oracle", "Years As A Consultant", "Assisting Major Global Clients With Complex Oracle Licensing Issues. Before His Work In Oracle Licensing", "He Gained Valuable Expertise In Ibm", "Sap", "Salesforce Licensing Through His Time At Ibm. In Addition", "Fredrik Has Played A Leading Role In Ai Initiatives", "Is A Successful Entrepreneur" ]	AI And the Future of Work. Increases efficiency in various sectors, automating routine tasks. Creates new jobs, such as AI maintenance and development roles ...	AI And the Future of Work Increases efficiency in various sectors, automating routine tasks. in various sectors, automating routine tasks. Creates new jobs , such as AI maintenance and development roles. , such as AI maintenance and development roles. Displaces traditional jobs , especially in manufacturing and data entry. , especially in manufacturing and data entry. Demands reskilling for workers to adapt to new technologies. for workers to adapt to new technologies. Enhances job quality in some fields by reducing mundane tasks. in some fields by reducing mundane tasks. Raises ethical concerns regarding surveillance and decision autonomy. Introduction AI And the Future of Work The landscape of Artificial Intelligence (AI) has undergone remarkable transformation since its inception, evolving from simple computational models to sophisticated systems integrated across various sectors. Today, AI’s influence extends far and wide, revolutionizing industries by automating tasks, enhancing decision-making processes, and creating new ways of engaging with technology. However, as AI reshapes the operational dynamics of these sectors, it also significantly impacts the job market. This article delves into the dual-edged sword of AI’s evolution, exploring its benefits, drawbacks, and potential worst-case scenarios for employment across different industries. The Transformative Power of AI Across Industries Healthcare Pros : AI’s integration into healthcare has led to breakthroughs in diagnostic tools, enabling quicker and more accurate disease identification. Patient care automation and administrative efficiencies streamline operations, allowing healthcare providers to focus on more complex cases. : AI’s integration into healthcare has led to breakthroughs in diagnostic tools, enabling quicker and more accurate disease identification. Patient care automation and administrative efficiencies streamline operations, allowing healthcare providers to focus on more complex cases. Cons: The reliance on AI for diagnostics and administrative tasks could diminish the roles of diagnostic staff and administrative personnel, raising concerns about job displacement within the sector. Read Top 10 Jobs at Risk Due to AI in the Healthcare Industry. Finance Pros : In finance, AI enhances fraud detection capabilities, allowing for real-time identification and preventing fraudulent activities. AI also makes personalized customer service and algorithmic trading possible, offering tailored advice and optimizing trading strategies. : In finance, AI enhances fraud detection capabilities, allowing for real-time identification and preventing fraudulent activities. AI also makes personalized customer service and algorithmic trading possible, offering tailored advice and optimizing trading strategies. Cons: These advancements may lead to displacing traditional banking roles and financial analysts as AI systems take over tasks previously performed by humans, impacting employment in the sector. Read Top 10 Jobs at Risk Due to AI in the Finance Industry. Manufacturing Pros : AI-driven automation in manufacturing boosts production efficiency and workplace safety, reducing the risk of human error and enhancing overall productivity. : AI-driven automation in manufacturing boosts production efficiency and workplace safety, reducing the risk of human error and enhancing overall productivity. Cons: However, the automation of manufacturing processes threatens jobs involving manual and repetitive tasks, leading to potential job losses and necessitating workforce adaptation to new technological paradigms. Read Top 10 Jobs at Risk Due to AI in the Manufacturing Industry. Transportation Pros : The advent of autonomous vehicles is revolutionizing the transportation industry. They promise to transform logistics and improve road efficiency and safety. : The advent of autonomous vehicles is revolutionizing the transportation industry. They promise to transform logistics and improve road efficiency and safety. Cons: This shift poses a significant threat to driving jobs and logistic operations traditionally reliant on human operators, potentially leading to widespread job displacement. Read Top 10 Jobs at Risk Due to AI in the Transportation Industry. Retail Pros : In retail, AI improves the customer experience through personalization and efficient inventory management, enabling businesses to more effectively meet consumer demands. : In retail, AI improves the customer experience through personalization and efficient inventory management, enabling businesses to more effectively meet consumer demands. Cons: The rise of online shopping and automated checkouts powered by AI may result in shifts in retail jobs, with fewer opportunities for traditional in-store roles as consumer behaviors change. Top 10 Jobs at Risk Due to AI in the Retail Industry Each sector demonstrates AI’s profound impact on industry operations and employment landscapes. As AI continues to evolve, its integration into various industries brings both opportunities for innovation and challenges for the workforce. This highlights the importance of navigating the future of work carefully and strategically. AI Impact on Jobs in the Health Industry The healthcare industry is experiencing a significant transformation due to the integration of AI technologies. These advancements are impacting jobs across various domains within healthcare, from diagnostics and treatment to administrative tasks. Enhancing Diagnostic Accuracy and Speed Description AI enhances diagnostic processes, making them faster and more accurate. Example Stanford University radiologists use an AI system that can more accurately detect pneumonia from chest X-rays than human radiologists. This technology assists radiologists by highlighting areas of concern, allowing for quicker and more accurate diagnoses. Impact on Jobs While AI aids diagnostics, radiologists must interpret results and make final decisions. Their role is evolving to include more oversight of AI tools and a focus on complex cases that require human judgment. Streamlining Administrative Tasks Description AI is automating administrative tasks, reducing the burden on healthcare professionals and administrative staff. Example At the Mayo Clinic, AI-driven chatbots handle appointment scheduling, patient reminders, and initial inquiries. This automation frees administrative staff to focus on more critical tasks and patient care. Impact on Jobs Administrative roles are shifting from routine data entry and scheduling to patient-centric activities. Staff members are retrained to manage and supervise AI systems, ensuring smooth operations and addressing issues. Improving Treatment Planning Description AI is assisting in creating personalized treatment plans based on patient data and predictive analytics. Example Oncologists use IBM Watson Health to analyze vast medical data and suggest personalized treatment options for cancer patients. Watson Health reviews patient records, medical literature, and clinical trial data to recommend treatment protocols. Impact on Jobs Oncologists and medical professionals now have more tools to design effective treatment plans. While AI provides recommendations, medical professionals’ expertise is crucial in tailoring and implementing these plans. Supporting Clinical Research Description AI accelerates clinical research by analyzing large datasets and identifying patterns that may not be evident to human researchers. Example Researchers at the University of California, San Francisco (UCSF) use AI to analyze genetic data and identify potential new drug targets. This speeds up the research process and opens up new avenues for treatment. Impact on Jobs Researchers benefit from AI by focusing more on hypothesis generation and experimental design than data analysis. The need for data scientists and bioinformaticians in clinical research is growing, highlighting the importance of interdisciplinary skills. Enhancing Patient Monitoring Description AI-powered devices and applications are used for continuous patient monitoring, providing real-time health data to healthcare providers. Example At the Cleveland Clinic, AI algorithms analyze data from wearable devices to monitor patients with chronic conditions, such as heart disease. These systems alert healthcare providers to significant changes in patient conditions, enabling timely interventions. Impact on Jobs Nurses and healthcare providers can now monitor multiple patients more efficiently, allowing them to focus on direct patient care and critical cases. The role of healthcare providers is expanding to include managing AI-driven monitoring systems. Reducing Human Error Description AI helps reduce human error in various medical procedures and tasks. Example In operating rooms, AI-assisted robotic surgery systems, like the da Vinci Surgical System, enhance precision and control during surgeries. Surgeons operate these systems to perform complex procedures with higher accuracy and fewer errors. Impact on Jobs Surgeons and operating room staff are trained to use AI-assisted technologies, which augment their skills. While AI reduces the likelihood of errors, surgeons’ expertise and decision-making abilities remain indispensable. Addressing Ethical and Regulatory Challenges Description Integrating AI in healthcare raises ethical and regulatory challenges that must be addressed to ensure patient safety and data privacy. Example The European Union’s General Data Protection Regulation (GDPR) has strict guidelines for using AI to handle patient data. Hospitals and healthcare providers must ensure compliance with these regulations. Impact on Jobs There is a growing demand for professionals specializing in healthcare ethics and regulatory compliance. These roles ensure that AI technologies are used responsibly and within legal frameworks. AI Impact on Jobs in the Retail Industry The retail industry is experiencing significant changes due to the adoption of AI technologies. These advancements reshape jobs across various functions, from customer service and inventory management to marketing and sales. Enhancing Customer Service Description AI is transforming customer service by automating responses and personalizing interactions. Example North Face uses IBM’s Watson to help customers find the perfect jacket. Watson asks customers questions about their preferences and the jacket’s intended use and then recommends products based on the responses. Impact on Jobs While AI chatbots handle routine inquiries, customer service representatives focus on resolving more complex issues and providing personalized assistance. The role of customer service agents is evolving to include managing and supervising AI tools. Optimizing Inventory Management Description AI systems are improving inventory management by predicting demand and automating stock replenishment. Example Walmart uses AI to predict product demand and manage inventory. The system analyzes various data points, such as sales history and weather patterns, to forecast demand and optimize stock levels. Impact on Jobs Inventory managers now rely on AI to make data-driven decisions, reducing the time spent on manual inventory checks and order placements. As a result, the need for data analysis and system management skills is increasing. Personalizing Marketing Strategies Description AI helps retailers personalize marketing efforts by analyzing customer data and predicting shopping behaviors. Example Starbucks uses AI to personalize marketing messages to its customers. The AI system analyzes purchase history and preferences to send personalized offers and recommendations through the Starbucks app. Impact on Jobs Marketing professionals use AI to design targeted campaigns, focusing on creative strategy and customer engagement rather than data crunching. Roles are shifting towards leveraging AI insights to drive marketing initiatives. Improving Supply Chain Efficiency Description AI is enhancing supply chain operations by optimizing logistics and reducing inefficiencies. Example Amazon uses AI to optimize its supply chain and logistics. The AI system predicts product demand, optimizes delivery routes and manages warehouse operations to ensure timely product delivery. Impact on Jobs Supply chain managers and logistics coordinators use AI to streamline operations, allowing them to focus on strategic planning and problem-solving. The role requires combining traditional logistics skills and familiarity with AI tools. Enhancing In-Store Experiences Description AI technologies are being used to enhance in-store customer experiences, from smart mirrors to automated checkout systems. Example Sephora uses AI-powered smart mirrors that allow customers to try on makeup virtually. The mirrors use facial recognition technology to show how different products will look on the customer’s face. Impact on Jobs Retail associates are now trained to assist customers with AI-powered tools, providing a more interactive and personalized shopping experience. The focus is shifting towards customer engagement and technology support. Automating Pricing Strategies Description AI algorithms automate and optimize pricing strategies, ensuring competitive pricing and maximizing profits. Example Zara uses AI to dynamically adjust prices based on various factors, including demand, inventory levels, and competitor pricing. The system helps the retailer maintain competitive pricing while maximizing revenue. Impact on Jobs Pricing analysts and retail managers use AI to inform pricing decisions, reducing the need for manual price adjustments. The role now includes overseeing AI systems and interpreting their recommendations. Reducing Fraud and Enhancing Security Description AI enhances security and fraud detection in retail, protecting the business and customers. Example PayPal uses AI to detect fraudulent transactions. The system analyzes transaction patterns and flags suspicious activity in real time, reducing fraud losses. Impact on Jobs Security analysts and fraud prevention specialists work alongside AI systems to monitor and respond to security threats. The job involves managing AI tools and developing strategies to counteract fraud. Enhancing Product Recommendations Description AI provides personalized product recommendations, improving the shopping experience and increasing sales. Example Netflix uses AI to recommend shows and movies based on viewing history and preferences. This personalization enhances user satisfaction and retention. Impact on Jobs E-commerce managers and digital marketers use AI to optimize product recommendations, focusing on customer engagement and sales strategies. The role emphasizes leveraging AI insights to enhance the shopping experience. Streamlining Workforce Management Description AI helps retailers manage their workforce more effectively, optimizing schedules and improving productivity. Example Tesco uses AI to optimize employee scheduling, ensuring adequate staffing during peak hours while reducing labor costs. The system analyzes sales data, foot traffic, and employee availability to create efficient schedules. Impact on Jobs HR professionals and store managers use AI to plan the workforce, focusing on employee engagement and productivity. Their role includes managing AI tools and ensuring their effective implementation. Supporting Sustainability Initiatives Description AI assists retailers in implementing sustainability initiatives by optimizing resource use and reducing waste. Example H&M uses AI to manage its supply chain and reduce environmental impact. The AI system predicts demand and adjusts production accordingly, minimizing overproduction and waste. Impact on Jobs Sustainability managers and supply chain analysts use AI to drive eco-friendly practices, focusing on strategic planning and implementation. The role requires knowledge of AI and sustainability principles. AI Impact on Jobs in the Finance Industry The finance industry is experiencing significant transformations due to the integration of AI technologies. These advancements reshape jobs across various functions, from trading and risk management to customer service and compliance. Enhancing Trading Strategies Description AI is revolutionizing trading by enabling faster and more accurate analysis of market trends and execution of trades. Example Goldman Sachs uses AI-driven algorithms for high-frequency trading to analyze vast market data and execute trades in milliseconds. Impact on Jobs Traders must now have a strong understanding of AI and algorithmic trading. Their roles shift towards monitoring AI systems and making strategic decisions based on AI-generated insights. Improving Risk Management Description AI helps financial institutions identify and manage risks more effectively by analyzing large datasets and predicting potential issues. Example JPMorgan Chase uses an AI system called COiN (Contract Intelligence) to analyze legal documents and identify potential risks. The system can review thousands of documents in seconds, reducing the risk of human error. Impact on Jobs Risk managers and analysts use AI to enhance their risk assessment processes. The role now involves interpreting AI-generated data and integrating it into broader risk management strategies. Automating Customer Service Description AI automates customer service tasks, quickly and accurately responding to customer inquiries. Example Bank of America’s virtual assistant, Erica, uses AI to assist customers with routine banking tasks, such as checking account balances, transferring funds, and providing financial advice. Impact on Jobs Customer service representatives focus on handling more complex inquiries and providing personalized financial advice. The role includes overseeing AI systems and ensuring they deliver accurate and helpful information. Enhancing Fraud Detection Description AI systems improve fraud detection by analyzing transaction patterns and identifying suspicious activities in real time. Example PayPal uses AI to detect and prevent fraudulent transactions. The system analyzes vast transaction data to identify fraud patterns, helping protect the company and its customers. Impact on Jobs Fraud analysts and security experts work alongside AI systems to monitor and respond to security threats. Their role involves managing AI tools and developing strategies to combat evolving fraud tactics. Streamlining Compliance Description AI assists in automating compliance processes, ensuring financial institutions adhere to regulatory requirements. Example HSBC uses AI to monitor transactions to ensure compliance with anti-money laundering (AML) regulations. The AI system flags suspicious activities for further investigation by compliance officers. Impact on Jobs Compliance officers use AI to streamline their monitoring and reporting tasks. They focus on addressing flagged issues and ensuring regulatory adherence. The role requires a combination of regulatory knowledge and AI expertise. Personalizing Financial Services Description AI enables financial institutions to provide personalized services and recommendations based on customer data. Example Wealthfront is a robo-advisor that uses AI to create personalized investment portfolios for its clients based on their financial goals, risk tolerance, and market conditions. Impact on Jobs Financial advisors use AI to enhance their advisory services, providing clients with data-driven recommendations. The role involves interpreting AI-generated insights and tailoring them to individual client needs. Optimizing Loan Approvals Description AI streamlines the loan approval process by assessing creditworthiness more quickly and accurately. Example Upstart uses AI to evaluate loan applications, considering factors such as education and employment history in addition to traditional credit scores. This results in faster and more inclusive loan approvals. Impact on Jobs Loan officers and underwriters use AI to expedite loan approval. They focus on complex cases and customer interactions, manage AI systems, and ensure accurate decision-making. Enhancing Financial Forecasting Description AI improves financial forecasting by analyzing historical data and predicting future market trends. Example BlackRock’s AI platform, Aladdin, analyzes market data to provide insights and forecasts for portfolio management. This helps portfolio managers make informed investment decisions. Impact on Jobs Financial analysts and portfolio managers use AI-generated forecasts to guide their investment strategies. The role involves integrating AI insights with traditional analysis techniques. Automating Routine Tasks Description AI automates routine administrative tasks, freeing employees to focus on higher-value activities. Example CitiBank uses AI to automate tasks such as data entry and reconciliation, reducing the time spent on manual processes and increasing accuracy. Impact on Jobs Administrative staff transition to roles that require oversight of AI systems and focus on strategic and customer-facing activities. These roles emphasize process management and optimization. Supporting Sustainable Finance Description AI supports sustainable finance initiatives by analyzing environmental, social, and governance (ESG) data to inform investment decisions. Example Morgan Stanley uses AI to analyze ESG data and identify sustainable investment opportunities, helping clients align their portfolios with their values. Impact on Jobs Sustainability analysts and investment advisors use AI to integrate ESG factors into their investment strategies. The role requires knowledge of sustainability issues and proficiency with AI tools. AI Impact on Jobs in the Manufacturing Industry AI technologies are transforming the manufacturing industry, reshaping jobs across various functions, from production and quality control to supply chain management and maintenance. Enhancing Production Efficiency Description AI optimizes production processes, improving efficiency and reducing waste. Example General Electric (GE) uses AI to optimize its jet engine manufacturing process. AI algorithms analyze data from production lines to identify inefficiencies and suggest improvements. Impact on Jobs Production managers and operators now work alongside AI systems to enhance production efficiency. Their roles involve monitoring AI outputs, implementing recommendations, and focusing on complex problem-solving tasks. Improving Quality Control Description AI systems are used for real-time quality control, ensuring products meet high standards. Example BMW uses AI-powered cameras on its production line to inspect vehicle components. The system detects defects that might be missed by human inspectors, ensuring higher quality products. Impact on Jobs Quality control inspectors and engineers use AI to augment their inspection processes. Their roles now focus on interpreting AI findings and addressing quality issues that require human expertise. Streamlining Supply Chain Management Description AI improves supply chain management by optimizing logistics, inventory levels, and supplier selection. Example Siemens uses AI to manage its supply chain, predicting demand and optimizing inventory levels. The AI system analyzes historical data and market trends to forecast demand more accurately. Impact on Jobs Supply chain managers and logistics coordinators use AI to make data-driven decisions, reducing the time spent on manual planning and forecasting. Their roles now emphasize strategic planning and oversight of AI systems. Predictive Maintenance Description AI enables predictive maintenance by analyzing machine data to predict failures before they occur. Example Airbus uses AI to monitor its aircraft manufacturing equipment. The AI system predicts when a machine will likely fail, allowing maintenance teams to perform repairs before a breakdown occurs. Impact on Jobs Maintenance technicians and engineers use AI to schedule and perform maintenance tasks more effectively. Their roles involve interpreting AI predictions and performing targeted maintenance to prevent equipment failures. Automating Routine Tasks Description AI automates repetitive and mundane tasks, freeing workers to focus on more complex activities. Example Foxconn, an electronics manufacturer, uses AI-powered robots for assembly line tasks such as soldering and screw driving. This automation increases production speed and consistency. Impact on Jobs Assembly line workers are transitioning to roles that involve overseeing and maintaining AI systems. The emphasis is on managing automation technologies and ensuring smooth production operations. Enhancing Safety Description AI enhances workplace safety by monitoring conditions and predicting potential hazards. Example Construction company Vinci uses AI to monitor safety conditions on construction sites. The AI system analyzes data from cameras and sensors to identify safety risks and alert workers. Impact on Jobs Safety officers and managers use AI to improve safety monitoring and response. Their roles focus on interpreting AI alerts, implementing safety measures, and ensuring compliance with safety regulations. Customizing Products Description AI allows manufacturers to offer customized products by optimizing production processes. Example Adidas uses AI to enable mass customization in its Speedfactory. Customers can design their shoes, and AI systems manage the production to fulfill personalized orders quickly. Impact on Jobs Production workers and engineers work with AI systems to manage customization processes. Their roles include configuring AI systems and ensuring customized products meet quality standards. Optimizing Energy Use Description AI helps manufacturers optimize energy consumption, reducing costs and environmental impact. Example BASF, a chemical company, uses AI to optimize energy use in its production facilities. The AI system analyzes energy consumption patterns and suggests ways to reduce usage. Impact on Jobs Energy managers and facility operators use AI to monitor and optimize energy use. Their roles involve implementing AI recommendations and developing energy-saving strategies. Facilitating Human-Robot Collaboration Description AI enables seamless collaboration between human workers and robots, enhancing productivity. Example Ford uses AI-powered collaborative robots (cobots) on its production line. These cobots assist human workers with tasks such as lifting and assembling parts. Impact on Jobs Workers collaborate with cobots to perform tasks more efficiently. Their roles involve programming, maintaining, and working alongside AI-powered robots. Driving Innovation Description AI drives innovation in manufacturing by enabling the development of new products and processes. Example In its research and development, Siemens uses AI to create new materials and manufacturing processes. The AI system analyzes vast amounts of data to identify innovative solutions. Impact on Jobs Research and development professionals use AI to enhance their innovation efforts. Their roles involve leveraging AI insights to develop new products and improve existing processes. AI Impact on Jobs in the Transportation Industry The integration of AI technologies is significantly transforming the transportation industry. These advancements reshape jobs across various functions, from vehicle operations and logistics to customer service and safety management. Enhancing Vehicle Operations Description AI improves vehicle operations through automation and advanced analytics, leading to more efficient and safer transportation. Example Waymo, Google’s self-driving car project, uses AI to navigate and operate autonomous vehicles. These self-driving cars analyze real-time data from sensors and cameras to make driving decisions. Impact on Jobs As autonomous vehicles become more prevalent, the role of drivers is evolving. While some driving jobs may be reduced, new roles in monitoring and maintaining autonomous systems are emerging. Optimizing Logistics and Supply Chain Management Description AI optimizes logistics by improving route planning, inventory management, and demand forecasting. Example UPS uses AI to optimize delivery routes through its ORION (On-Road Integrated Optimization and Navigation) system. This AI system analyzes data to determine the most efficient routes, reducing fuel consumption and delivery times. Impact on Jobs Logistics managers and planners use AI to enhance their decision-making processes. They focus on strategic oversight rather than manual route planning. The demand for data analysis and system management skills is increasing. Improving Customer Service Description AI enhances customer service by providing real-time information and personalized experiences. Example Delta Airlines uses AI-powered chatbots to assist customers with booking, flight status updates, and customer service inquiries. These chatbots handle routine questions, freeing human agents to manage more complex issues. Impact on Jobs Customer service representatives are transitioning to roles supervising AI systems and providing higher-level support. Their focus is on complex problem-solving and personalized customer interactions. Enhancing Safety and Maintenance Description AI improves safety by predicting maintenance needs and identifying potential hazards before they cause issues. Example Rolls-Royce uses AI to predict the maintenance of aircraft engines. The AI system analyzes data from engine sensors to predict when maintenance is needed, reducing the risk of in-flight failures. Impact on Jobs Maintenance technicians and safety managers use AI to anticipate and address maintenance needs. Their roles involve interpreting AI predictions and ensuring timely and accurate maintenance. Enabling Smart Infrastructure Description AI is used to develop smart infrastructure, improve traffic management, and reduce congestion. Example Los Angeles uses AI to manage traffic lights and reduce congestion. The AI system analyzes real-time traffic data to optimize traffic light timings, improving traffic flow. Impact on Jobs Urban planners and traffic management professionals use AI to design and implement smart infrastructure solutions. Their roles involve integrating AI systems and monitoring their performance. Facilitating Autonomous Freight and Logistics Description AI powers autonomous freight systems, optimizing the movement of goods and reducing human intervention. Example Tesla’s autonomous trucks use AI to drive and navigate highways. They aim to revolutionize freight transport by reducing the need for human drivers. Impact on Jobs Truck drivers’ roles are evolving to include oversight of autonomous systems and handling complex driving scenarios that require human intervention. Maintenance and supervision roles are becoming more prominent. Personalizing Travel Experiences Description AI personalizes travel experiences by analyzing customer preferences and providing tailored recommendations. Example Uber uses AI to predict rider demand and optimize driver availability. The system also provides personalized ride suggestions based on user history and preferences. Impact on Jobs Roles in customer relationship management and personalized service design are growing. Employees focus on leveraging AI insights to enhance the customer experience. Optimizing Fleet Management Description AI optimizes fleet management by monitoring vehicle health and optimizing routes. Example FedEx uses AI to manage its fleet, ensuring that vehicles are maintained and used efficiently. The AI system tracks vehicle performance and suggests maintenance schedules. Impact on Jobs Fleet managers use AI to oversee vehicle maintenance and operations. Their roles involve strategic planning and implementing AI-driven insights to optimize fleet performance. Enhancing Public Transportation Description AI improves public transportation systems by optimizing schedules and routes based on real-time data. Example Singapore’s public transportation system uses AI to analyze passenger data and optimize bus and train schedules, improving efficiency and reducing wait times. Impact on Jobs Public transportation planners and operators use AI to design better schedules and routes. Their roles focus on managing AI systems and addressing any service issues. Promoting Environmental Sustainability Description AI helps transportation companies reduce their environmental impact by optimizing fuel usage and reducing emissions. Example Maersk, a global shipping company, uses AI to optimize shipping routes and reduce fuel consumption, significantly lowering its carbon footprint. Impact on Jobs Environmental and sustainability officers use AI to develop and implement strategies for reducing environmental impact. Their roles involve integrating AI solutions and monitoring their effectiveness. Pros and Cons of AI in the Workplace Integrating Artificial Intelligence (AI) in the workplace heralds a new era of productivity and innovation, yet it also brings challenges and concerns that must be addressed. Pros Increased Efficiency : AI automates routine and time-consuming tasks, allowing human workers to focus on complex problem-solving and creative tasks, thereby increasing productivity. : AI automates routine and time-consuming tasks, allowing human workers to focus on complex problem-solving and creative tasks, thereby increasing productivity. Creation of New Job Categories : As AI evolves, new roles emerge, such as AI system trainers, maintenance experts, and AI ethicists, offering opportunities in burgeoning tech fields. : As AI evolves, new roles emerge, such as AI system trainers, maintenance experts, and AI ethicists, offering opportunities in burgeoning tech fields. Enhanced Safety : AI-driven automation can reduce human exposure to hazardous environments, leading to safer workplace conditions in industries like manufacturing and transportation. : AI-driven automation can reduce human exposure to hazardous environments, leading to safer workplace conditions in industries like manufacturing and transportation. Ability to Tackle Complex Global Challenges: AI’s data processing and predictive analytics capabilities are instrumental in addressing issues like climate change, healthcare crises, and resource management, providing insights and solutions at an unprecedented scale. Read Positive Impact of Artificial Intelligence on Employment. Negative impact of artificial intelligence on employment Job Displacement : Automating tasks previously carried out by humans can lead to job losses, particularly in manufacturing, retail, and administrative services. : Automating tasks previously carried out by humans can lead to job losses, particularly in manufacturing, retail, and administrative services. Widening Skills Gap : The rapid advancement of AI technologies necessitates specialized skills, creating a gap between the current workforce’s abilities and the demands of AI-driven roles. : The rapid advancement of AI technologies necessitates specialized skills, creating a gap between the current workforce’s abilities and the demands of AI-driven roles. Ethical Concerns Over Surveillance and Decision-Making : Using AI to monitor employee performance and make employment decisions raises ethical questions about privacy and the potential for discriminatory practices. : Using AI to monitor employee performance and make employment decisions raises ethical questions about privacy and the potential for discriminatory practices. Risk of Bias in AI Algorithms: AI systems can inherit biases present in their training data, leading to unfair outcomes in hiring, promotions, and workplace dynamics. Read more about the Negative Impact of Artificial Intelligence on Employment. Worst-Case Scenarios – Impact of AI on jobs While AI presents vast opportunities for progress and efficiency, unregulated and irresponsible advancements could lead to several adverse outcomes. Mass Unemployment : One of the most significant concerns is the potential for AI to automate jobs at a rate faster than the economy can create new roles, leading to widespread unemployment and economic instability. : One of the most significant concerns is the potential for AI to automate jobs at a rate faster than the economy can create new roles, leading to widespread unemployment and economic instability. Societal Inequality : The benefits of AI might disproportionately favor those with access to advanced technologies and the skills to leverage them, exacerbating income and opportunity disparities within and across societies. : The benefits of AI might disproportionately favor those with access to advanced technologies and the skills to leverage them, exacerbating income and opportunity disparities within and across societies. Ethical Breaches in Privacy and Autonomy : In a world heavily reliant on AI, the erosion of privacy and individual autonomy could become common, with algorithms making critical life decisions and constant surveillance becoming normalized. : In a world heavily reliant on AI, the erosion of privacy and individual autonomy could become common, with algorithms making critical life decisions and constant surveillance becoming normalized. Loss of Human Skills and Interpersonal Connections: As AI takes over more functions, there’s a risk that essential human skills, such as critical thinking, empathy, and interpersonal communication, could diminish, impacting social cohesion and personal relationships. Managing AI’s advancement responsibly involves proactive governance, ethical AI development practices, continuous learning opportunities for the workforce, and public engagement in dialogue about AI’s role in society. Ensuring that AI enhances human capabilities and societal well-being rather than diminishes them is crucial as we navigate the future of work and its broader implications for our world. Short-Term and Long-Term Job Impacts Integrating AI into the workplace is having significant effects on jobs, both in the short and long term. Here’s a detailed look at how AI impacts employment, with real-life examples to illustrate these changes. Short-Term Job Impacts 1. Automation of Routine Tasks Description AI automates repetitive and mundane tasks, allowing employees to focus on more complex activities. Example Companies like Bank of America use AI-driven chatbots (Erica) to handle basic inquiries and customer service transactions. This reduces the workload of human agents who can address more complicated customer issues. 2. Job Displacement in Certain Sectors Description Some jobs, particularly those involving routine manual tasks, are displaced by AI and automation. Example Companies like Foxconn have replaced assembly line workers with AI-powered robots in manufacturing. This has led to job losses in easily automated roles and created new opportunities to maintain and program these robots. 3. Increased Demand for Tech-Savvy Workers Description There is a growing demand for workers with skills in AI, machine learning, and data analysis. Example Tech companies like Google and IBM are hiring data scientists and AI specialists to develop and manage their AI systems. This shift is prompting a surge in tech-related educational programs and certifications. 4. Enhanced Productivity Description AI is helping businesses increase productivity by optimizing operations and improving decision-making. Example Retail giant Walmart uses AI to manage inventory, predict stock levels, and ensure shelves are stocked efficiently. This leads to improved store operations and customer satisfaction. 5. Shift in Required Skills Description The skills required in the job market are evolving, with a higher emphasis on technical and analytical skills. Example In finance, firms like JPMorgan Chase use AI for fraud detection and risk management, requiring employees to develop new skills in AI tools and data interpretation. Long-Term Job Impacts 1. Creation of New Job Categories Description AI will lead to the creation of entirely new job categories that do not exist today. Example The rise of AI ethics specialists who ensure AI systems are used responsibly and without bias is an emerging job category. Companies like Microsoft and Google have started hiring for these roles. 2. Transformative Changes in Existing Roles Description AI will transform many existing roles, changing how work is performed across various industries. Example In healthcare, AI is assisting doctors with diagnostic processes. Systems like IBM’s Watson Health analyze patient data and suggest potential diagnoses, changing the traditional roles of doctors and medical staff. 3. Greater Focus on Creativity and Human Skills Description As AI takes over routine tasks, human jobs will increasingly focus on creativity, problem-solving, and interpersonal skills. Example Companies like Ogilvy use AI to analyze market trends and consumer behavior in advertising. Creative professionals then use these insights to develop innovative campaigns, emphasizing the human touch in creativity. 4. Long-Term Economic Shifts Description The widespread adoption of AI will lead to significant economic shifts, including changes in labor market dynamics and economic growth. Read Long-Term Economic Shifts Caused by AI Adoption. Example Countries like South Korea and Japan heavily invest in AI to drive economic growth. This includes initiatives to upskill the workforce and integrate AI into various sectors, potentially reshaping their economies over the next few decades. 5. Job Polarization Description There will be a polarization of jobs, with growth in high-skill, high-pay jobs and low-skill, low-pay jobs, while mid-skill jobs may decline. Example In the banking sector, roles such as data analysts and financial advisors are expected to grow, while traditional teller jobs might decline as more banking operations become automated. 6. Ethical and Regulatory Challenges Description The integration of AI will require addressing ethical and regulatory challenges to ensure fair and transparent use. Example The European Union has been proactive in establishing regulations for AI use, focusing on data protection and ethical considerations. These regulations will shape how AI impacts jobs and industries long-term. Ethical Considerations in AI Deployment As AI technologies become increasingly integrated into various aspects of society, the importance of ethical considerations in their deployment cannot be overstated. It is imperative to establish robust ethical frameworks to guide AI development and application, focusing on: Fairness : Ensuring AI algorithms make decisions without discrimination or bias, promoting equality across all user interactions. : Ensuring AI algorithms make decisions without discrimination or bias, promoting equality across all user interactions. Transparency : AI systems should be transparent in their operations, allowing users to understand how decisions are made and ensuring that AI actions can be explained in understandable terms. : AI systems should be transparent in their operations, allowing users to understand how decisions are made and ensuring that AI actions can be explained in understandable terms. Accountability : Clear mechanisms should exist to hold AI systems and their creators accountable for the outcomes of AI actions, including any harm or errors that arise. : Clear mechanisms should exist to hold AI systems and their creators accountable for the outcomes of AI actions, including any harm or errors that arise. Prevention of Bias: Steps must be taken to prevent bias in AI algorithms. These include careful selection and processing of training data and regular audits for biased outcomes. The Role of Policy and Governance Policy and governance play crucial roles in ensuring that the benefits of AI are distributed equitably across society. This includes: Developing and enforcing regulations that safeguard against misuse of AI and protect individual rights. Encouraging the development of AI technologies that address societal challenges and contribute to the public good. Facilitating public discourse on AI’s role in society, ensuring that diverse voices are heard and considered in shaping the future of AI development. By prioritizing ethical considerations and fostering a regulatory environment that promotes accountability and fairness, we can navigate the challenges of AI deployment and harness its potential for positive societal impact. Navigating the Transition As Artificial Intelligence (AI) reshapes the job landscape, workers and industries must adopt strategies to successfully navigate this transition. Adapting to AI-Driven Changes Reskilling : Due to AI advancements, workers should seek opportunities to acquire new, in-demand skills. This includes learning to work with AI tools and systems in their respective fields. : Due to AI advancements, workers should seek opportunities to acquire new, in-demand skills. This includes learning to work with AI tools and systems in their respective fields. Embracing Lifelong Learning : The pace of technological change necessitates a commitment to continuous education. Staying abreast of the latest AI developments and how they impact one’s profession is crucial. : The pace of technological change necessitates a commitment to continuous education. Staying abreast of the latest AI developments and how they impact one’s profession is crucial. Leveraging AI to Augment Capabilities: Workers and industries should consider how AI can enhance human capabilities instead of viewing AI as a replacement. For example, AI can handle data analysis, allowing humans to focus on decision-making and strategy. Importance of Education and Training Programs Tailored education and training programs are vital for preparing the workforce for an AI-augmented workplace. These programs should: Focus on developing skills AI cannot easily replicate, such as creative problem-solving, emotional intelligence, and interpersonal communication. Include training on AI tools and technologies specific to various industries, ensuring workers can effectively collaborate with AI systems. Be accessible and inclusive, providing opportunities for all workers to adapt to the changing job market. The Future of Employment and Skills in an AI-Driven World Integrating AI into the workplace is not just about the challenges it presents; it’s also about the opportunities it creates for new job categories and the evolution of existing roles. Emerging Job Categories and Skills AI Ethics Officers : As ethical considerations become increasingly important, roles focused on ensuring AI systems are developed and used responsibly will emerge. : As ethical considerations become increasingly important, roles focused on ensuring AI systems are developed and used responsibly will emerge. Machine Learning Specialists : Experts in designing and training AI models will be in high demand across various sectors. : Experts in designing and training AI models will be in high demand across various sectors. Data Privacy Managers: With the proliferation of data-driven AI applications, professionals skilled in managing data privacy and security will be crucial. Shift Towards Collaborative Roles The future workplace will see a shift towards roles that emphasize collaboration between humans and AI, focusing on: Creativity : Jobs that require creative thinking and innovation will increasingly rely on AI to provide data-driven insights, while human creativity will direct these insights into meaningful outcomes. : Jobs that require creative thinking and innovation will increasingly rely on AI to provide data-driven insights, while human creativity will direct these insights into meaningful outcomes. Strategic Thinking : AI can process and analyze information at an unprecedented scale, but human strategic thinking will be necessary to interpret and apply these insights effectively. : AI can process and analyze information at an unprecedented scale, but human strategic thinking will be necessary to interpret and apply these insights effectively. Emotional Intelligence: Roles that require understanding human emotions and building relationships will continue to be uniquely human, with AI augmenting these capabilities in areas like personalized customer service. The future of employment in an AI-driven world is one of transformation rather than obsolescence. By preparing for the evolving landscape through education, training, and focusing on the synergistic potential of human-AI collaboration, workers and industries can navigate the transition to a future where AI enhances human capabilities and opens new horizons for innovation and growth. FAQ: AI and the Future of Work What is AI? AI, or Artificial Intelligence, is the simulation of human intelligence in machines programmed to think and learn like humans. It includes technologies like machine learning, natural language processing, and robotics. How is AI changing the workplace? AI automates routine tasks, provides data-driven insights, and enhances decision-making processes. It is used in various fields, from customer service chatbots to predictive analytics in business operations. Will AI replace jobs? AI will automate some jobs, especially those involving repetitive tasks. However, it is also expected to create new jobs that require more complex problem-solving and creativity. The overall impact on employment will vary by industry. What skills will be important in the future job market? Skills in technology, data analysis, and AI will be crucial. Additionally, soft skills like critical thinking, creativity, and emotional intelligence will remain important as they are harder to automate. Can AI help with career development? Yes, AI can assist with career development by providing personalized learning paths, identifying skill gaps, and offering recommendations for training and development. How are companies using AI for recruitment? Companies use AI to screen resumes, schedule interviews, and even conduct initial interviews through chatbots. AI helps identify the best candidates efficiently. What is the impact of AI on work-life balance? AI can improve work-life balance by automating tedious tasks, allowing employees to focus on more meaningful work. However, it can blur the lines between work and personal life if not managed properly. Are there ethical concerns with AI in the workplace? Yes, there are concerns about bias in AI algorithms, data privacy, and the potential for increased surveillance. Companies must address these issues responsibly. How can businesses ensure ethical AI use? Businesses should implement AI ethics guidelines, ensure transparency in AI processes, regularly audit AI systems for bias, and involve diverse teams in AI development. What is the role of AI in remote work? AI facilitates remote work through virtual assistants, project management software, and video conferencing platforms. It also helps monitor productivity and manage remote teams effectively. How can employees prepare for an AI-driven workplace? Employees can prepare by gaining AI and related technologies skills, staying adaptable, and continuously learning. Engaging in lifelong learning will be key to staying relevant. What industries are most affected by AI? AI significantly impacts industries like manufacturing, healthcare, finance, and retail. These sectors use AI for automation, predictive analytics, customer service, and more. Can AI improve workplace safety? AI can enhance workplace safety by predicting potential hazards, monitoring compliance with safety protocols, and providing real-time alerts for dangerous conditions. How does AI influence decision-making in businesses? AI provides data-driven insights that help businesses make informed decisions. It can analyze large datasets quickly, identify trends, and predict outcomes, aiding strategic planning. What is the future of AI in the workplace? The future of AI in the workplace includes more advanced automation, AI-driven decision-making, and enhanced human-AI collaboration. As AI technology evolves, it will continue transforming how we work and the skills needed in the job market.	2025-01-26T00:00:00	2025/01/26	https://redresscompliance.com/future-of-work-the-impact-of-ai-on-jobs-and-skills/	[ { "date": "2025/06/30", "position": 63, "query": "artificial intelligence employment" }, { "date": "2025/06/30", "position": 41, "query": "future of work AI" } ]
Our Work	Articles Archive	https://cnti.org	[]	Sciences Po. New uses of AI in journalism will require new kinds of disclosures and transparency with the public. It is important that these disclosures be ...	One of the things we heard in Mexico City’s convening, as well as elsewhere, is in many cases journalists are working on devices that are four generations old, they are personal devices. How can technology build stronger tools that really facilitate the needs at the time? — Amy Mitchell, Executive Director, CNTI Read full story	2025-06-30T00:00:00		https://cnti.org/work/	[ { "date": "2025/06/30", "position": 69, "query": "artificial intelligence journalism" } ]
AI Corrections - Goforth Solutions, LLC	Goforth Solutions, LLC	https://www.stephengoforth.com	[ "Stephen Goforth" ]	7 Free Webinars this Week about AI, Journalism & Media · Mon, June 30 - (Mis)use of Data Protection Laws to Suppress Public-Interest Journalism · Mon, June 30 - ...	Mon, June 30 - (Mis)use of Data Protection Laws to Suppress Public-Interest Journalism What: Gain critical insights from legal experts and investigative journalists who have experienced these tactics first-hand. You’ll leave with a deeper understanding of: How international data protection frameworks interact with press freedom The growing use of privacy laws in strategic legal attacks on journalists Journalistic exemptions and legal safeguards — and where they fall short What journalists and legal professionals can do to push back. Who: Melinda Rucz – PhD Researcher, University of Amsterdam; Beatrix Vissy, PhD – Strategic Litigation Lead, Hungarian Civil Liberties Union; Bojana Jovanović – Deputy Editor, KRIK, Serbia; Hazal Ocak – Feelance Investigative Journalist, Türkiye; Grace Linczer – Membership and Engagement Manager, IPI. When: 8 am, Eastern Where: Zoom Cost: Free Sponsors: Media Defence, International Press Institute More Info Mon, June 30 - AI in Scientific Writing What: This talk explores the evolving role of Generative AI in academic writing and publishing. Attendees will gain an understanding of how AI tools can enhance writing efficiency, improve clarity, and streamline the publication process. We will examine the benefits and limitations of using AI in scholarly communication, along with key ethical considerations and responsible use practices. The session will also cover current editorial policies, publishers’ perspectives on AI generated content, and the growing concern over paper mills. Strategies and mitigations to uphold research integrity in response to these challenges will be discussed. Who: Maybelline Yeo, Trainer and Editorial Development Advisor, Researcher Training Solutions, Springer Nature. When: 9:30 pm, Eastern Where: Zoom Cost: Free Sponsor: Springer Nature More Info Tue, July 1 - Learn the Basics of Solutions Journalism What: This one-hour webinar will explore the principles and pillars of solutions journalism. We will discuss its importance, outline key steps for reporting a solutions story, and share tips and resources for journalists investigating responses to social problems. We will also introduce additional resources, such as the Solutions Story Tracker, a database with over 17,000 stories tagged by beat, publication, author, location and more, along with a virtual heat map highlighting successful efforts worldwide. Who: Jaisal Noor, SJN's democracy cohort manager, and Ebunoluwa Olafusi of TheCable. When: 9 am, Eastern Where: Zoom Cost: Free Sponsor: Solutions Journalism Network More Info Tue, July 1 - AI-Powered Visual Storytelling for Nonprofits What: In this hands-on workshop, participants will create impactful visuals, infographics, and videos tailored to their mission and campaigns. Attendees will also explore Tapp Network’s AI services to understand how these tools can elevate their content strategies.. Who: Tareq Monuar Web Developer; Lisa Quigley Tapp Network Director of Account Strategy. When: 1 pm, Eastern Where: Zoom Cost: Free Sponsor: Tech Soup More Info Tue, July 1 - Journalist Development Series What: A once-monthly webinar as an opportunity for general professional development for members and the mentorship program community. Who: Chris Marvin, a combat-wounded Army veteran and nationally recognized narrative strategist who helps shape powerful, purpose-driven storytelling at the intersection of media, public service, and social change. When: 6 pm, Eastern Where: Zoom Cost: Free for members Sponsors: Military Veterans in Journalism, News Corp More Info Wed, July 2 - Business Decisions with AI: Causality, Incentives & Data What: How complex settings in tech companies create additional complications to measure and evaluate business decisions. Drawing on cutting-edge research on the intersection of AI and causal inference, Belloni will demystify how to properly measure the efficacy of these decisions and show how AI can help shape better implementation for a variety of applications. Who: Alexandre Belloni, the Westgate Distinguished Professor of Decision Sciences and Statistical Science at Duke University and an Amazon Scholar WW FBA. When: 12:30, Eastern Where: Linkedin Live Cost: Free Sponsor: Duke University’s Fuqua School of Business More Info Wed, July 3 - Reel Change: Nonprofit Video Storytelling for Social Impact What: Learn to create impactful video stories that amplify your nonprofit’s mission, engage donors, and inspire action. This training provides actionable strategies to craft emotional, audience-driven narratives, empowering you to deepen connections and drive meaningful support for your organization. Who: Matthew Reynolds, founder of Rustic Roots, a video production agency; Dani Cluff is the Channel Marketing Coordinator at Bloomerang. When: 2 pm, Eastern Where: Zoom Cost: Free Sponsor: Bloomerang More Info	2025-06-30T00:00:00		https://www.stephengoforth.com/?offset=1751307420145	[ { "date": "2025/06/30", "position": 83, "query": "artificial intelligence journalism" } ]
Artificial Intelligence (AI) & Information Literacy - Wolfgram ...	Artificial Intelligence (AI) & Information Literacy	https://widener.libguides.com	[ "Heather Burychka" ]	PA Forward Information Literacy · Head of Research, Instruction & Outreach · Generative AI and Text · More videos on YouTube · Generative AI and Images · AI News ...	Algorithm - A sequence of instructions for solving a problem or performing a task. Algorithms define how an artificial intelligence system processes input data to recognize patterns, make decisions, and generate outputs. Anthropomorphism - The tendency for people to attribute humanlike qualities or characteristics to an A.I. chatbot. For example, you may assume it is kind or cruel based on its answers, even though it is not capable of having emotions, or you may believe the A.I. is sentient because it is very good at mimicking human language. Artificial Intelligence (AI) - Computer systems designed to perform tasks associated with human intelligence, such as pattern recognition or decision making. Bias - In regards to large language models, errors resulting from the training data. This can result in falsely attributing certain characteristics to certain races or groups based on stereotypes. Chatbot - A program that communicates with humans through text in a written interface, built on top of a large language model. Examples include ChatGPT by OpenAI, Bard by Google, and more. While many people refer to chatbots and LLMs interchangeably, technically the chatbot is the user interface built on top of an LLM. Deep Learning - A method of AI, and a subfield of machine learning, that uses multiple parameters to recognize complex patterns in pictures, sound and text. The process is inspired by the human brain and uses artificial neural networks to create patterns. Emergent Behavior - When an AI model exhibits unintended abilities. Generative Artificial Intelligence (GAI) - A subfield of Artificial Intelligence, referring to models capable of generating content (such as language, images, or music). The output of GAI models is based on patterns learned from extensive training datasets. Hallucination - In the context of AI, a falsehood presented as truth by a large language model. For example, the model may confidently fabricate details about an event, provide incorrect dates, create false citations, or dispense incorrect medical advice. Language Learning Model (LLM) - A type of neural network that learns skills — including generating prose, conducting conversations and writing computer code — by analyzing vast amounts of text from across the internet. The basic function is to predict the next word in a sequence, but these models have surprised experts by learning new abilities. Machine Learning - A field of computer science in which a system learns patterns or trends from underlying data. Machine learning algorithms perform tasks like prediction or decision making. Neural Network - A mathematical system, modeled on the human brain, that learns skills by finding statistical patterns in data. It consists of layers of artificial neurons: The first layer receives the input data, and the last layer outputs the results. Even the experts who create neural networks don’t always understand what happens in between. Prompt - In the context of AI, it is the input text written by a human that is given to a generative AI model. The prompt often describes what you are looking for, but may also give specific instructions about style, tone, or format. Training Data - The content used to teach a machine learning system how to perform a particular task. Training data gives the system a knowledge base from which the model can make predictions or identify patterns. Training data might include images, text, code, or other types of media. Glossary definitions come from these sources: Khan, I. (2023, September 2). ChatGPT glossary: 41 AI terms that everyone should know. CNET. https://www.cnet.com/tech/computing/chatgpt-glossary-41-ai-terms-that-everyone-should-know/ metaLAB at Harvard. (2024). AI starter. The AI pedagogy project. https://aipedagogy.org/guide/starter/ Pasick, A. (2023, March 27). Artificial intelligence glossary: Neural networks and other terms explained. The New York Times. https://www.proquest.com/blogs-podcasts-websites/artificial-intelligence-glossary-neural-networks/docview/2791317549/se-2?accountid=29103	2025-06-30T00:00:00		https://widener.libguides.com/AI-Literacy	[ { "date": "2025/06/30", "position": 84, "query": "artificial intelligence journalism" } ]
From policy to practice: Responsible media AI ...	From policy to practice: Responsible media AI implementation	https://digitalcontentnext.org	[ "Rich Murphy", "Ceo", "President", "Managing Director", "Alliance For Audited Media" ]	As artificial intelligence becomes more embedded in editorial and business processes, media companies face increased pressure to ensure AI is implemented ...	As artificial intelligence becomes more embedded in editorial and business processes, media companies face increased pressure to ensure AI is implemented responsibly. This requires companies to develop a plan for AI use that covers several areas including bias mitigation, risk management, legal compliance and long-term governance. In my last article, I shared real-world examples of how media companies are implementing ethical AI best practices for transparency and disclosures, bias and ongoing staff education. Here we go deeper into the steps media companies are taking to reduce risk, protect privacy and maintain editorial oversight while integrating AI tools into their processes. Together, these form the eight pillars of ethical AI. Ethical guidelines and standards Establishing clear policies that define how AI is used across editorial, marketing and operational teams is essential to increasing transparency and building trust with audiences. Already, some media leaders have not only created policies around AI usage but share them publicly – which offer some great examples to other organizations grappling with AI governance. The New York Times outlines its AI policies as part of its ethical journalism handbook, which was developed for its editorial and opinion teams and is available to the public. The guidelines state the importance of human oversight and adhering to established standards for journalism and editing. The Financial Times also made its AI governance publicly available by sharing its principles in articles that outline specific tools staff are integrating into their workflows. It also discusses its investment in skill development and how it has transformed into a company committed to AI fluency and innovation. Media companies need to develop formal AI ethics guidelines that help guide staff and increase transparency with the public. However, it’s equally important to regularly evaluate these guidelines as technology evolves. Rights and permissions As part of their governance strategy, companies must also take steps to ensure that any content produced through AI does not infringe on intellectual property rights or violate content licensing agreements. This means securing applicable rights and permissions to use the information generated by the AI tools and creating internal processes to ensure that AI outputs do not use third-party content without permission. The New York Times encourages staff to use AI to create content including quizzes, quote cards and FAQs. However, its guidelines state that copyrighted material should not be input into AI tools, which prevents potential misuse of third-party content in AI training. The Guardian outlines its commitment to protecting content creators’ rights when selecting third-party AI tools by stating it will only use tools that have addressed permission, transparency and fair reward for content usage. These practices can reduce risk and reinforce a publisher’s commitment to responsible content development. Accountability and human oversight Even sophisticated AI systems can produce biased, inaccurate or misleading output. To safeguard against this, media companies should take a “human-in-the-loop” approach and assign qualified individuals to oversee AI tools at every stage of use. Bay City News, a San Francisco Bay area nonprofit news organization, maintains audience transparency by publicly sharing how the team uses AI including in-depth context about the process behind each project. When it created its award-winning election results hub using AI, human oversight including fact-checking was a vital part of the project’s success. While BBC prohibits the use of AI to directly create news content, AI use in other areas such as research must be actively monitored and the outcomes assessed by an editor. Wired also does not create content directly from AI, but the company states that if AI is used to suggest headlines or social media posts, an editor needs to approve the final choice for accuracy. Privacy and data protection As readers grow more concerned about how their personal data is collected and used, publishers must take steps to ensure that AI tools are deployed in ways that maintain legal compliance. AI governance must include the development of transparent data collection policies and adhering to privacy regulations such as GDPR and CCPA. Graham Media Group, a Detroit-based media company, prioritizes reader privacy and security and shares its compliance with data privacy laws on its disclosure page and in its privacy policy. The company also uses an in-house AI tool to help employees streamline their workflows without relying on free AI tools or unsecured platforms. BBC states in its responsible AI policy that if staff intend to include personal data in an AI tool, a data protection impact assessment must be completed prior to use. Risk management and adaptation Using AI introduces a range of potential risks such as bias and fairness that must be actively managed. Effective AI governance requires continuous monitoring and a proactive approach to identifying and addressing these risks. BBC created its AI Risk Advisory Group that includes subject matter experts from legal, data protection, commercial and business affairs and editorial departments. The group provides detailed advice on potential risks of using AI in both the newsroom and across the company. As AI technologies evolve, so must the ethical frameworks that support their use. By integrating ethical AI principles into daily operations, media organizations can protect their brands, maintain audience trust and demonstrate their value to advertisers and partners who seek reliable, trusted media environments.	2025-06-30T00:00:00	2025/06/30	https://digitalcontentnext.org/blog/2025/06/30/from-policy-to-practice-responsible-media-ai-implementation/	[ { "date": "2025/06/30", "position": 94, "query": "artificial intelligence journalism" } ]
High-level expert group on artificial intelligence	High-level expert group on artificial intelligence	https://digital-strategy.ec.europa.eu	[]	The European Commission appointed a group of experts to provide advice on its artificial intelligence strategy.	Deliverables During the first year of its mandate, the high-level expert group on artificial intelligence (AI HLEG) worked on two main deliverables: Deliverable 1: Ethics Guidelines for Trustworthy AI The document puts forward a human-centric approach on AI and list 7 key requirements that AI systems should meet in order to be trustworthy. Deliverable 2: Policy and Investment Recommendations for Trustworthy AI Building on its first deliverable, the group put forward 33 recommendations to guide trustworthy AI towards sustainability, growth, competitiveness, and inclusion. At the same time, the recommendations will empower, benefit and protect European citizens. The results of the work of the AI HLEG were presented at the first European AI Assembly in June 2019. Following the Assembly, the European Commission extended the group’s mandate for one more year. This extended mandate allowed the group to increase its work and pilot the Ethics Guidelines for Trustworthy AI . The mandate of the AI HLEG ended in July 2020 with the presentation of two more deliverables: Deliverable 3: The final Assessment List for Trustworthy AI (ALTAI) A practical tool that translates the Ethics Guidelines into an accessible and dynamic self-assessment checklist. The checklist can be used by developers and deployers of AI who want to implement the key requirements. This new list is available as a prototype web based tool and in PDF format. Deliverable 4: Sectoral Considerations on the Policy and Investment Recommendations The document explores the possible implementation of the recommendations, previously published by the group, in three specific areas of application: Public Sector, Healthcare and Manufacturing & the Internet of Things. AI HLEG and the European AI Alliance The overall work of the AI HLEG has been central to the development of the Commission’s approach to Artificial Intelligence. The concept of trustworthiness and the 7 key requirements, introduced by the Ethics Guidelines are guiding the upcoming legislative steps in AI. The group’s recommendations have served as resources for policymaking initiatives taken by the Commission and its Member States. Among those initiatives, there was the Communication on Building Trust in Human Centric Artificial Intelligence, the White Paper on Artificial Intelligence: a European approach to excellence and trust and the updated Coordinated plan on AI. The AI HLEG has worked closely with the European community of AI stakeholders through the AI Alliance. The European AI Alliance is an online forum with over 4000 members representing academia, business and industry, civil society, EU citizens and policymakers. The members of the AI Alliance offered detailed feedback for the Ethics Guidelines for Trustworthy AI. Moreover, a set of materials such as policy documents, academic papers and discussions published on the forum, helped define the other deliverables of the AI HLEG. In the first European AI Alliance Assembly, 500 members of the forum met in a live event that engaged the community into a direct feedback provision to the European Commission’s policymaking process on AI. Although the AI HLEG ended its mandate in July 2020, the community of the AI Alliance continued its activity. In October 2020 over 1900 participants joined online the second European AI Alliance Assembly to discuss the main findings of the Public Consultation on the Commission’s White Paper on Artificial Intelligence and future perspectives in building a European approach of excellence and trust in AI.	2025-06-30T00:00:00		https://digital-strategy.ec.europa.eu/en/policies/expert-group-ai	[ { "date": "2025/06/30", "position": 40, "query": "artificial intelligence labor union" } ]
Artificial intelligence	Artificial intelligence	https://www.eua.eu	[ "Katerina Topalidou" ]	EUA's work on artificial intelligence. To enable the exchange of practices ... The role of universities in the European Union's ambitions for AI. Europe ...	To enable the exchange of practices and exploration of use cases among EUA members, the Association has launched a work programme focused on universities’ experiences and approaches in addressing artificial intelligence. Activities carried out in 2024 and into 2025 will address practical and ethical questions around the integration of AI technologies in universities, as well as providing orientation on AI-related trends in higher education and research. Building on EUA’s previous work on digital transformation, its AI work programme, guided by a dedicated task-and-finish group, will address how AI can benefit university management, research and education, while also addressing its ethical dimensions and social impact. The preservation of human control and university values in the rollout of AI technologies is another key concern. Therefore, EUA will investigate the impact of European regulation in the digital space and consider how this might facilitate (or constrain) universities in promoting a rights-based approach to AI innovation. By tackling issues related to privacy, digital sovereignty, and data availability and quality, EUA strives to support universities in navigating legal frameworks and in developing institutional policies on the use of AI. In parallel, the Association’s activities on AI will emphasise the importance of culture and community in building institutions’ capacity to manage change. Furthermore, as the debate around the benefits versus risks of AI moves up the political agenda, EUA will continue to highlight the role of universities in fostering ethical innovation for the benefit of society, culture and the economy.	2025-06-30T00:00:00		https://www.eua.eu/our-work/topics/artificial-intelligence.html	[ { "date": "2025/06/30", "position": 43, "query": "artificial intelligence labor union" } ]
Future of Work Insights from the HR Industry \| UNLEASH	Future of Work Insights from the HR Industry	https://www.unleash.ai	[ "Lucy Buchholz" ]	Our Take: AI could be the death of entry level jobs, but only if… we allow it ... Recent statements have all but declared that the entry level role will be ...	Name * First Name Last Name Professional Email Address * Please enter a work or professional email address. 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You can unsubscribe at anytime by clicking the unsubscribe link in the footer of any email. By clicking "Submit" you acknowledge and agree that you have read, understood and agree to be bound by our Terms and Conditions and Privacy Policy. I accept	2025-06-30T00:00:00		https://www.unleash.ai/future-of-work/	[ { "date": "2025/06/30", "position": 62, "query": "future of work AI" } ]
Automated Testing Specialist	Automated Testing Specialist	https://www.womentech.net	[]	But above all, in NTT DATA your career has no limit – you make your future! We are looking for experienced professionals to join our team. Are you ready to ...	JOB DESCRIPTION NTT DATA – part of NTT Group – is a trusted global innovator of IT and business services headquartered in Tokyo. We help clients transform through consulting, industry solutions, business process services, digital & IT modernization and managed services. NTT DATA enables them, as well as society, to move confidently into the digital future. We are committed to our clients' long-term success and combine global reach with local client attention to serve them in over 50 countries around the globe. NTT DATA is the 6th most valuable IT Company in the world dedicated to Consulting and Outsourcing services, with more than 139,000 professionals located in 50 countries. With offices in Casablanca and Tetouan, NTT DATA is today a key-player - the first IT employer in the Northern region - with more than 450 experts across the Kingdom. Flexibilty is a key-advantage allowing our Digital Nomads to work totally from home or partially in a hybrid mode at their convenience. Our objective is to continue our growth reaching 1000 professionals by 2025. By joining us, you’ll be able to collaborate with large multinationals while working with cutting-edge technologies. You will benefit of a flexible work schedule: Smartworking, Homeworking and BeFlex programs to better balance your professional and personal lives. But above all, in NTT DATA your career has no limit – you make your future! We are looking for experienced professionals to join our team. Are you ready to accept the challenge and become part of our success? Visit our career site to learn more about NTT DATA Main Responsibilities · Create new automated test cases and adapt existing tests to IS evolutions. · Execute and analyze automated test results · Strengthen the automated test assets · Contribute to the definition of the non-regression testing strategy Requirements · 4 years of experience in Software Quality Assurance and Test Automation · Knowledge and practical experience in testing processes · Mastery of test automation tool: Selenium, Gherkin, testLink, ... · Strong verbal and written communication skills	2025-07-14T00:00:00	2025/07/14	https://www.womentech.net/en-pt/job/ntt-data/automated-testing-specialist-0	[ { "date": "2025/06/30", "position": 83, "query": "job automation statistics" } ]
Utilize machine learning to improve employee retention rates	Utilize machine learning to improve employee retention rates	https://www.datasciencecentral.com	[ "Zachary Amos", "Tosin Clement", "Dan Wilson", "Jelani Harper" ]	It combines the intuition of experienced HR professionals with the predictive power of AI to design strategies to boost engagement and build stronger workplace ...	Employee turnover is one of the most pressing challenges modern businesses face. It drains resources, lowers morale and slows team momentum. Traditional HR tools like surveys and exit interviews often reveal issues after valuable employees have left. However, machine learning (ML) can detect patterns, forecast risk and deliver actionable insights based on real-time data. Analyzing performance metrics and sentiment in feedback helps HR teams understand why people leave and what keeps them around. It combines the intuition of experienced HR professionals with the predictive power of AI to design strategies to boost engagement and build stronger workplace cultures. Forecast engagement trends using time series models Monitoring employee engagement, absenteeism and productivity gives companies a clearer picture of workforce health and potential red flags. While traditional metrics may show only the surface, ML models can uncover deeper trends and fluctuations that might go unnoticed. Time series tools help HR teams forecast dips tied to seasonal cycles, workplace changes or major organizational events like mergers and restructures. One critical insight they offer is the early detection of quiet quitting. Quiet quitting occurs when a team member begins putting in minimal effort for an extended period of time. Though harder to quantify, quiet quitting can lead to business losses nearly as significant as actual turnover and drain team performance and morale. With the ability to predict and visualize downward trends before they impact the bottom line, companies can take timely, targeted actions. They can adjust workloads or organize recognition programs to re-engage employees and strengthen retention strategies across departments. Analyze sentiment in employee feedback Natural language processing (NLP) allows HR teams to make sense of unstructured employee input like open-ended survey responses, anonymous reviews or casual conversations. Instead of manually sifting through pages of text, NLP tools can automatically extract meaning, sentiment and context. These features help teams understand how employees truly feel in their own words. More advanced applications can pinpoint the structure of conversations, such as who’s talking to whom, what tone they’re using and how sentiment shifts over time. This kind of analysis can flag early signs of dissatisfaction, burnout or disengagement before they appear in performance reviews. Enterprise solutions often have built-in NLP features that plug directly into communication platforms and HR dashboards. By combining language data with other engagement signals, HR leaders can respond to morale issues quickly and precisely. Personalize learning and development paths ML delivers personalized education and development opportunities based on each employee’s role, interests and performance trends. Collaborative filtering or content-based filtering techniques allow HR teams to create custom upskilling plans at scale. This kind of personalization improves retention and builds a stronger internal talent pipeline. In fact, 65% of global business leaders believe AI is critical to staying competitive across international markets. Aligning employee growth with business goals is a significant part of that strategy. Platforms like LinkedIn Learning and Coursera for Business already use algorithms to recommend courses, track progress and adjust content based on engagement data. Tapping into these tools allows companies to boost employee satisfaction, close skill gaps faster and future-proof their workforce. Predict turnover before it happens ML can use historical employee data to reveal clear patterns behind who stays, who leaves and why. By training models like logistic regression or random forests, HR teams can assign attrition risk scores to individual employees based on factors such as tenure, performance, engagement levels, role changes or manager feedback. These scores help prioritize retention efforts toward high-performing or at-risk team members before they decide to leave. When integrated with Human Resource Information Systems or Applicant Tracking Systems, these models can generate real-time alerts for HR managers and make it easier to act quickly when warning signs appear. With data-driven insights at their fingertips, companies can move from reactive to proactive, addressing turnover risks before they become costly exits. Cluster employees by retention risk Unsupervised learning offers a powerful way for companies to better understand and manage employee retention by grouping staff into distinct risk profiles based on shared characteristics. By feeding models data from job performance metrics, employment history, and payroll records, organizations can uncover which employees might be disengaging or preparing to leave. This type of segmentation allows HR teams to go beyond a one-size-fits-all approach and instead tailor retention strategies to meet the specific needs of each group. Using unsupervised learning to pinpoint what different groups truly need, businesses can deploy smarter, more targeted initiatives that reduce churn and keep valuable talent growing within the organization. Optimize onboarding through predictive matching Matching new hires with the right mentors, learning paths or team environments can significantly impact how quickly and comfortably they settle into a new role. Businesses can use models like those used in recommendation systems for e-commerce or streaming platforms. HR teams can suggest personalized pairings based on past hires with similar skills, goals or backgrounds. This matching level helps align expectations and create a sense of belonging from day one, which is especially important considering that it costs an average of $4,700 to hire a new employee. When new talent connects with the right people and resources early on, the likelihood of early-stage churn drops significantly. In HR, recommendation systems are a smart way to foster culture fit, encourage development and protect the investment made in every new team member. Detect pay and promotion biases ML gives organizations a practical way to analyze sensitive issues like pay equity and promotion fairness across departments, genders and roles. By training models on historical HR data, companies can identify the frequency of compensation disparities, delayed career progression and inconsistent recognition patterns and whether these factors are linked to turnover rates. These insights are critical in light of recent findings — over 50% of employees who quit in 2021 said low pay and feeling disrespected were major factors in their decision to leave. ML makes it easier to spot these trends early and course correct with data-backed actions. Whether adjusting salary bands, standardizing promotion timelines or improving communication around career development, businesses prioritizing transparency and fairness reduce attrition and strengthen trust across the workforce. Getting started with machine learning in HR ML is a powerful ally that enhances — not replaces — the instincts and experience of HR professionals. Companies should start small by piloting one or two models, learn from the results and confidently scale up. Behind every successful company is a dedicated, engaged team.	2025-06-30T00:00:00	2025/06/30	https://www.datasciencecentral.com/utilize-machine-learning-to-improve-employee-retention-rates/	[ { "date": "2025/06/30", "position": 6, "query": "machine learning workforce" } ]
2025 AI Adoption Across Industries: Trends You Don't Want ...	2025 AI Adoption Across Industries: Trends You Don't Want to Miss	https://www.coherentsolutions.com	[]	According to the index above, various iterations of AI will touch 980 million jobs worldwide, affecting about 26% of the global workforce in some way or another ...	The AI niche used to be very concept-driven back in the day, with investor-seeking designs, Proofs-of-Concept, ICOs, and crowdfunded campaigns reigning supreme. We see real models bringing tangible results and respective profits to their owners and creators. For instance, Accenture reports that AI should bring a 35% productivity boost to the US labor sector by 2035 (as well as to other economies, 36% for Finland, 37% for Sweden, etc.). The boundaries of AI adoption across industries expand even further due to an opportunity to take clean slate AI models and tune them into whatever you need. Customizable AI is readily available today, which means you can save a ton of automation expenses without going far or going broke. This is why a majority of organizations surveyed by Accenture plan to expand beyond pre-built AI solutions to customized or custom-built AI workloads, which brings us to another point. The Current State of AI Adoption According to global AI adoption studies by several sources: of firms have employed AI by 2025 vs. 55% by 2024 of companies look to invest more in AI in 2025–2027 of tech budgets will be allocated to AI in 2025 Within the top 25% of AI spenders are healthcare, financial agencies and banks, media and telecom, manufacturing, and retail. Following those, energy and materials, consumer goods and ecommerce, hardware engineering, travel, transport, and logistics are all powered by AI to a certain extent. AI Adoption Trends Across Key Industries We can typically see the highest rates of AI adoption among the operations that must generate or digitize large sets of structured and unstructured data. The greater the data available, the more effectively AI models can be trained, refined, and scaled. So, this data focus works both ways. IT and Telecom Symbiosis with AI is projected to potentially earn $4.7 trillion in gross value added for IT and telecom by 2035. This is a spacious niche where providers can develop and integrate AI platforms to run a range of internal, technical, and consumer services. Source: 2025 Global Telecommunications Outlook We can already witness the pioneers in these niches, like the AI-RAN Alliance, launched back in February 2024. The AI-RAN Alliance gathers the top telecom and tech market leaders to focus efforts on merging AI with cellular technology. The ultimate goal of the alliance is to achieve new advancements in the RAN (radio access network) technology. Other use cases for AI adoption in IT and telecom: Network planning and optimization Network security CX enhancement Predictive maintenance Network slicing Healthcare Numerous healthcare facilities and brands rely on the custom development of AI solutions. For example, custom AI tools enable safer and hyper-precise drug development and testing, highly detailed medical imaging, and automation of a ton of administrative work. Source: AI Adoption in Healthcare Report 2024 Importantly, the generative AI adoption rate is still only maturing in settings as complex and responsibility-driven as medicine. However, we can already see impressive implementations: At Coherent Solutions, we tapped into the creation of AI for healthcare with the RX transcription tool for an eyewear manufacturer company. This solution helps interpret optical prescriptions and select the right glasses. Tempus is a precision medicine platform that uses AI to analyze clinical data and personalize cancer care and other treatments. PathAI uses deep learning to improve the accuracy of pathology diagnoses for faster, more precise treatments. The NMDP Donor Readiness Score helps predict individual stem cell donor availability. Other use cases for AI adoption in healthcare: Developing drugs Clinical documentation Clinical trials Medical imaging Finance and Banking The productivity of knowledge workers, from accountants and managers to researchers and developers, can be boosted dramatically by automating mundane tasks. Like routine mortgage reviews, market inspection, answering generic customer queries, etc. AI tools, like innovative authentication systems, have also been developed to reinforce the security of access and interaction with valuable assets. At Coherent Solutions, we had the pleasure of building a feature-rich identity authentication platform that restricts access based on real-time user behavior monitoring and analysis. In dry figures, the financial sector can get up to $1.2 trillion extra GVA thanks to mass AI adoption in financial services in 2035. But that’s if the market players are not slowed down by the emerging governance of AI adoption in central banks and other associated risks too much. Use cases for AI adoption in banking and finance: Anomaly detection Payments Robo-advisors (portfolio management) Algorithmic trading Manufacturing Robotics and IoT help accelerate AI adoption in manufacturing with intelligent systems that connect directly to construction sites and enable remote opportunities. Accenture’s research shows that AI could enrich the manufacturing sector with an extra $3.8 trillion GVA in 2035. But there are more promising stats. Source: Taking AI to the Next Level in Manufacturing The 2025 State of AI in Manufacturing Survey, which indicates that: More than 77% of manufacturers have implemented AI to some extent (as compared to 70% in 2023). AI in manufacturing is mostly employed in solutions for production (31%), customer service (28%), and inventory management (28%). Rather than fully autonomous AI bots, most manufacturing specialists (53%) would prefer working with collaborative bots or “copilots” (AI agents that support human workflows instead of fully replacing them). The leading investment niches for AI in manufacturing are supply chain management (49%) and big data analytics (43%). 56% of manufacturers are still unsure whether their existing ERP systems are ready for full-on AI integration. Use cases for AI adoption in manufacturing: Cobots (collaborative robots) Industry 4.0 Generative design Quality assurance Predictive maintenance and demand forecasting Retail According to Deloitte’s 2025 US Retail Industry Outlook, GenAI is really coming in handy in commerce. In particular, retailers saw 15% higher conversion rates after using chatbots during the Black Friday weekend. Furthermore, IBM’s research states that organizations working with retail and consumer products will be making the most extensive use of AI across 2025 and beyond. Solutions like Spokn AI have been developed to help ease global consumers’ widespread adoption of AI features. Spokn AI is a tool for in-depth speech analytics in a contact center, which helps analyze sentiment and gain insights from customer conversations to find ways to improve their experience. Other use cases for AI adoption in retail:	2025-06-30T00:00:00		https://www.coherentsolutions.com/insights/ai-adoption-trends-you-should-not-miss-2025	[ { "date": "2025/06/30", "position": 95, "query": "workplace AI adoption" } ]
Hierarchical gap in workplace AI adoption \| HRD America	Hierarchical gap in workplace AI adoption	https://www.hcamag.com	[ "Dexter Tilo" ]	Gaps in artificial intelligence use in the workplace might be more hierarchical than generational, according to a new report, ...	It also found that executives are more than twice as likely to create efficiencies using AI than ICs. Among their uses include drafting emails to clients and creating presentations. "This staggering divide indicates a significant disconnect between those at the top and their employees, where those in managerial positions are in a better position to recognise the value of AI in optimising operations and decision-making processes but may be failing to communicate that value to their employees," the BambooHR report read. Beyond daily use, the gap also exists when it comes to training. According to the report, 72% of employees want to improve their AI skills, but only 32% said they had received formal AI training from their employer. Half of managers and more senior titles also received training on AI, compared to just 23% of ICs, the report added.	2025-07-01T00:00:00		https://www.hcamag.com/us/specialization/hr-technology/hierarchical-gap-in-workplace-ai-adoption/541137	[ { "date": "2025/07/01", "position": 24, "query": "workplace AI adoption" }, { "date": "2025/07/01", "position": 24, "query": "workplace AI adoption" }, { "date": "2025/07/01", "position": 22, "query": "workplace AI adoption" }, { "date": "2025/07/01", "position": 23, "query": "workplace AI adoption" }, { "date": "2025/07/01", "position": 23, "query": "workplace AI adoption" }, { "date": "2025/07/01", "position": 26, "query": "workplace AI adoption" }, { "date": "2025/07/01", "position": 69, "query": "workplace AI adoption" } ]
Get your students workplace-ready - Times Higher Education (THE)	Get your students workplace-ready	https://www.timeshighereducation.com	[]	Not everyone wants to be a computer scientist, a software engineer or a machine learning developer. ... job market – AI. Ioannis Glinavos ...	The leap from higher education to employment has always been a daunting one, but with artificial intelligence (AI) challenging long held norms, post-Covid working practices still in flux and climate change now affecting every sector, the future has never been murkier. Today’s students need universities’ guidance to prepare for jobs that do not exist yet. This guide offers insight into how to teach skills that will stay relevant as jobs evolve, offer them the best career services possible, link to industry partners and get students prepped for job applications. Teach transferable skills for the future There are certain skills that support professional success across any chosen career path. While universities can’t prepare students for every specific role, embedding soft skills such as critical thinking, communication, problem solving and resilience will give them a rock-solid foundation from which to launch their careers. Below, academics and educators share insights and experiences of what works best when training students in these transferable human skills. Tried and tested ways to teach your students soft skills: The introduction of ChatGPT reignited the debate surrounding employability skills. Add two decades of intensifying international competition and a pandemic, and it is no wonder we’re fundamentally rethinking the modern workplace, writes Kate Pettifer of the University of Exeter. Teach the skills required for a future we can’t yet imagine: Times are changing too quickly for any of us to accurately predict what the future employment market will look like. But we can still prepare our students. Hajer N. Sheikh of Dubai Medical University advocates for a more agile approach. Let’s give learners on all levels the skills for a green future: To support the switch to a green economy, educators need to update sustainability education programmes to meet learners’ needs. Ethan Chong Yih Tng of Singapore Institute of Technology offers his tips. Strategies to train students in three transferable skills wanted by employers: Two simple teaching methods that faculty can use in the classroom to train students in the communication, problem-solving and critical thinking skills sought by employers, shared by Elly Vandegrift of the University of Oregon. Heart skills to future-proof students: These 10 skills might sound as soft as the centre of a Valentine’s Day chocolate, but they are essential for the careers and employability of our students, writes Elizabeth Reid Boyd of Edith Cowan University. Four ways to weave job skills teaching into the university experience: With research finding a hefty proportion of graduates underemployed, what can higher education do to improve career readiness? Erica Estes and Sean O’Keefe of the University of Arkansas offer advice. Prepare students for the job application process Help your students show their best selves to prospective employers, whether that’s through well written CVs, sharp interview skills or networking know-how. Read about ways to help students identify their own strengths, understand potential careers and prepare them for in-person and remote interviews. Show off students’ employability with e-portfolios: Why and how to make e-portfolios a central part of university courses, helping students identify and exhibit skills that will appeal to employers, by Lourdes Guàrdia and Marcelo Maina of the Open University of Catalonia. Career mentoring can support student employability: Support for students extends beyond the classroom. Here’s how to develop a successful mentoring programme to help students take their first steps into the workplace, explained by Zurria Qureshi of the University of Westminster. Sharpen your students’ interview skills: The employees of the future will need to showcase their skills in job interviews. Make sure they’re prepared for each setting, writes Lewis Humphreys of the London School of Economics and Political Sciences. Three steps to unearth the hidden curriculum of networking: How to support students in developing networking skills that will enhance their future career prospects, by Julia Freeland Fisher of the Clayton Christensen Institute. How to improve your university career services Students considering future job options will look for careers advice on campus. The university careers teams and lecturers can support students on their first steps towards permanent employment, offering guidance on different career paths and entry points, on necessary skillsets and application processes and by providing useful industry contacts. Find insight on how to make careers advice accessible, relevant and useful. Want student success? Modernising your careers centre is vital: Camille Dumont of Post University gives advice on how to adapt a university careers centre to better align with the evolving needs of students and the job market. Social mobility via social media: opportunities for career services: Four practical suggestions for how university career services can make greater use of social media to support social mobility among their students, from William E. Donald of the Ronin Institute and the University of Southampton and Kaz Scattergood of the University of Liverpool. Student support: four ways to innovate for improvement: What fresh approaches could provide more proactive, tailored and cohesive student support? Andy Wistow of the University of Bristol shares insights from pilot schemes designed to do just that, from careers advice to peer support. How to help postdocs take a holistic look at career choices: After their terminal degrees, many postdocs find themselves at a career crossroads. Here, Karena Nguyen of Georgia Tech’s Center for 21st Century Universities offers four key considerations across background, skills, values and interests to help determine what’s next. Careers services: how to prepare graduates for workplace abuse: University career services must do a better job of helping students identify and manage psychological abuse following entry into the labour market, write William E. Donald of the Ronin Institute and the University of Southampton and Sucheta Das. Digital literacy for future jobs The pace of digital transformation makes it difficult to predict what the future of employment will look like. But it is clear that the ability to adeptly use artificial intelligence (AI) tools, as well as compete against them, and manage and analyse data will be greatly in demand. Here academics share tips on how to boost data literacy among students, ensure they understand AI’s potential and limitations and can even use it to aid their job search. Prepare the workforce of tomorrow by integrating data literacy into your curriculum: Data literacy skills are increasingly important in the modern workplace. Colleagues from the London School of Economics and Political Science offer their advice on readying your students for the future. What does it mean for students to be AI-ready? Not everyone wants to be a computer scientist, a software engineer or a machine learning developer. We owe it to our students to prepare them with a full range of AI skills for the world they will graduate into, writes David Joyner of Georgia Tech’s Center for 21st Century Universities. The ‘deep learn’ framework: elevating AI literacy in higher education: AI literacy is no longer a futuristic concept; it’s a critical skill for university students. The ‘deep learn’ framework, shared here by Birgit Phillips of FH Joanneum University of Applied Sciences, offers a comprehensive approach to enhancing literacy around artificial intelligence and application in higher education settings. How your graduates can beat AI in the job market of tomorrow: Your students are facing a competition against a faster, better and cheaper opponent in 2025’s job market – AI. Ioannis Glinavos of the University of Westminster offers his advice on readying them for the fight. How we can use AI to power career-driven lifelong learning: By using data from job postings, course catalogues and students’ CVs, AI can help people address skill gaps and plot their educational journeys, writes Teck-Hua Ho of the National University of Singapore. Build links between student and employers Find out how to give your students’ graduate careers a jump-start by connecting them with potential employers. This could be through internships and placements, real business challenges, work-integrated learning or supporting student entrepreneurship, as these resources explain. Balancing career readiness and finances: the case for abbreviated internships: Internships give students professional experience, guide career choices and boost job market competitiveness. But what if students need higher-paying summer jobs or can’t afford three months in a far-flung city? That’s where abbreviated winter internships come in, explains Magarita McGrath of Virginia Tech. Three tips for using capstone projects to improve employability: How can we make sure our students are workplace-ready? Capstone projects may hold the key, writes Ardy Cheung of the London School of Economics and Political Science. Helping students to see the future career value of their work-integrated learning: Real-world experience and outputs tailored to industry allow students to see the relevance of what they learn in the classroom, writes Sabine Matook of the University of Queensland. Four ways to create an entrepreneurial culture at your institution: Universities are perfectly placed to help start-ups get off the ground. Alan Murray, Robert Crammond and Kingsley Omeihe from the University of the West of Scotland advise on how best to get your students thinking with a business mindset. Tips for successful apprenticeships courses: Learn how to please both the learner and employer when setting up and running apprenticeships, from Steven Hurst of Arden University whose team who recently earned a 'Good' from Ofsted for their efforts. If you would like advice and insight from academics and university staff delivered direct to your inbox each week, sign up for the Campus newsletter.	2025-04-01T00:00:00	2025/04/01	https://www.timeshighereducation.com/campus/get-your-students-workplaceready	[ { "date": "2025/07/01", "position": 100, "query": "machine learning job market" }, { "date": "2025/07/01", "position": 100, "query": "machine learning job market" } ]
How business leaders can manage integration of AI - TechRadar	How business leaders can manage integration of AI	https://www.techradar.com	[ "Drew Posey", "Social Links Navigation" ]	According to a survey of C-suite executives, 40 percent say their companies will increase their investment in AI tools overall. Latest Videos ...	2023 was the breakout year of AI and since then it’s been going from strength to strength. It’s seen as the solution to everything from productivity and a skills gap to fixing the NHS, with Tony Blair calling for AI doctors and chatbots to ‘save’ the health service. There has been an explosive growth of generative AI with most companies using it in at least one of their business functions. It’s gone from being a subject discussed by tech teams to something regularly mentioned in the boardroom. According to a survey of C-suite executives, 40 percent say their companies will increase their investment in AI tools overall. And whilst there is no doubt AI is developing in accuracy, I do not believe it can replace humans in every single area and one in particular – emotional intelligence. Drew Posey Social Links Navigation Founder and CEO of DPC. Over-reliance on AI in business Over-reliance on AI in business risks removing that vital input from key decision making and team building and runs the risk of making some areas of leadership redundant – at significant cost. The costs might not immediately show up on a PNL spreadsheet, but they will be felt in other areas where it might not be so easy to quantify. AI is a useful tool, but it's just that - a tool and it cannot replace that ‘gut feeling’ or connection that a great leader of any team has. That’s the magic which turns a group of disparate people into a team – the sum of which is greater than its parts. My concern is that we need to strike the right balance between our use of technology and building and developing our own skills. If all we do is put resources into AI at the expense of other training and development, or replace people with machines, we will be the worse for it. In short, I worry that people will become reliant on AI and could lose that innate human element that we bring to leadership and team building. Leaders have understanding and insights Leaders have understanding and insights built over many years which cannot be replaced by data or machines. If AI cannot find the answers to a question, it can make things up. Look at the infamous court case in America which made headlines in May 2023 when a law firm, Levidow, Levidow & Oberman got caught citing fake cases generated by ChatGPT. The ‘soft skills’ which good leaders at all levels have make the difference between a good leader and a great leader can’t be replaced by software. These personal qualities enable people to interact effectively and successfully with others: communication, teamwork, problem-solving and adaptability – not to mention empathy. These should be highly valued in the workplace, and especially by leaders, as they contribute to improved teamwork, productivity and overall job satisfaction. My experience of working in elite sports has shown me that humans cannot just be replaced by technology, no matter how smart. AI has a role to play AI has a role to play in any team, particularly with more basic tasks of information gathering or data analysis, but it cannot replace the power of a human connection. An emotionally intelligent leader goes beyond the numbers and knows their team. AI can’t pick up that real emotional response, and it can't read people like humans do. It’s ‘machine learning’ for a reason – it uses whatever data you pump into it but there are just some cues and traits which cannot be quantified and that’s what cannot be replaced. We've used technology and data in sport for a long time; elite sports is incredibly data driven. We've got all the information that says the players should train at this point because they are due to pull a hamstring or develop another injury or over train. And whilst it's useful to have that information, it should be used as a guide. I've seen many top-level coaches when the sports scientists are running over, saying ‘we need to stop training now.’ But the coach looks at the players and can see that the players can continue for another ten minutes, and he’s pushed the players through. The data could also get it wrong and put players at risk by pushing them too much whereas a coach will see if his players look physically fatigued and need to stop training early. Costs of bad investment The costs of misreading that at elite sports level go beyond the investment in a machine: we’re talking millions of pounds worth of players or the opportunity to achieve a lifetime goal of a medal on the world stage. And even when Olympic golds aren’t in the picture, the impact of a toxic working environment is felt not only in the lower productivity or staff turnover but in more personal impacts on someone’s health and sense of value. This knowledge and consequent decision making comes from the human understanding of people. In my 25 years’ of working in both a team and in a leadership role in sports I have yet to see a coach who has got that wrong. Because we’ve used data in sports for so many years I think it provides a lesson for other areas on how we can use AI: as a way of gathering data, of making predictions or analysing patterns but only as a tool to help inform our own human-driven intelligence. To rely on AI wholly would be a mistake: nothing can replace that human intelligence. We've compiled a list of the best data visualization tools and the best business intelligence platforms. This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro	2025-07-01T00:00:00	2025/07/01	https://www.techradar.com/pro/how-business-leaders-can-manage-integration-of-ai	[ { "date": "2025/07/01", "position": 71, "query": "AI business leaders" } ]
The Top AI Roles Companies Are Hiring For - Nelson Connects	The Top AI Roles Companies Are Hiring For	https://www.nelsonconnects.com	[]	Artificial Intelligence (AI) is no longer a future vision—it's here, and it's transforming every industry it touches.	Artificial Intelligence (AI) is no longer a future vision—it’s here, and it’s transforming every industry it touches. From personalized customer experiences to real-time analytics and workflow automation, AI is driving innovation and reshaping the workforce. As companies race to stay competitive, demand for specialized AI talent is skyrocketing. At Nelson Connects, we’re seeing this trend play out across every sector we serve—technology, finance, healthcare, logistics, and beyond. Whether you're a business looking to hire smarter or a professional exploring where your skills fit in the AI landscape, understanding the roles leading the charge is essential. Here’s a look at some of the most in-demand AI roles shaping the future of work. 1. AI/ML Engineer AI/ML Engineers are at the forefront of AI innovation. These professionals design and deploy machine learning models that allow systems to learn from and act on data. Their work involves complex algorithm design, processing large datasets, and integrating AI systems into business operations. Why It’s in Demand: As AI becomes central to everything from fraud detection to customer personalization, companies need technical experts who can build and scale these systems effectively. Key Skills: Python, R, Java Machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) Data engineering, model deployment, and algorithm development Cloud platforms (AWS, Azure, GCP) 2. Data Scientist Data Scientists play a pivotal role in extracting actionable insights from raw data. They apply advanced statistical techniques and machine learning algorithms to support decision-making and uncover patterns that drive business outcomes. Why It’s in Demand: With businesses becoming more data-centric, the ability to turn massive datasets into strategic insights is more valuable than ever—especially in industries like healthcare, retail, and finance. Key Skills: Python, R, SQL Data wrangling and visualization (Pandas, NumPy, Tableau, Power BI) Machine learning, predictive analytics Big data tools (Spark, Hadoop) 3. AI Product Manager AI Product Managers serve as the critical bridge between technical teams and business stakeholders. They define the vision, strategy, and roadmap for AI-powered products, ensuring development efforts align with organizational goals. Why It’s in Demand: Companies increasingly need leaders who not only understand AI technologies but can also translate them into successful, scalable solutions that meet customer and business needs. Key Skills: Product lifecycle management Understanding of AI/ML capabilities and limitations Competitive market analysis Agile methodologies and stakeholder management 4. AI Project Manager AI Project Managers oversee the successful execution of complex AI initiatives. From managing cross-functional teams to mitigating risks and staying on budget, they ensure projects move forward efficiently and deliver real results. Why It’s in Demand: The technical complexity and cross-departmental nature of AI initiatives make this role essential. Businesses want project leaders who understand both the strategy and the science behind AI. Key Skills: Project management tools (Jira, Asana, MS Project) Cross-functional team leadership AI project scoping and risk assessment Budgeting and timeline planning 5. Prompt Engineer / Generative AI Specialist As generative AI tools like ChatGPT and DALL·E go mainstream, Prompt Engineers are emerging as specialists who craft effective prompts that guide these models. This role blends creativity, logic, and language to maximize performance from large language models (LLMs). Why It’s in Demand: More businesses are integrating generative AI into customer service, content creation, product development, and internal tools—and skilled prompt engineers are key to unlocking full potential. Key Skills: Natural language processing (NLP) Prompt engineering and prompt tuning Familiarity with LLM APIs (OpenAI, Anthropic, Cohere) Critical thinking and iterative experimentation 6. AI Solutions Architect AI Solutions Architects design the technical frameworks for scalable AI systems. They evaluate business needs, choose appropriate technologies, and oversee implementation across cloud and enterprise environments. Why It’s in Demand: As organizations invest in long-term AI infrastructure, they need professionals who can architect robust, flexible, and secure systems from the ground up. Key Skills: Systems architecture and API design AI/ML platforms (SageMaker, Vertex AI) Data pipelines and ETL processes Cloud infrastructure (AWS, GCP, Azure) 7. AI/ML Ethicist Responsible AI is now a business imperative. AI/ML Ethicists ensure AI systems are transparent, fair, and accountable, especially in industries that face regulatory oversight or public scrutiny. Why It’s in Demand: As businesses expand AI use, the risk of bias, misuse, or unintended consequences grows. AI ethicists help navigate these challenges and ensure compliance and trust. Key Skills: AI ethics frameworks (OECD, IEEE, EU AI Act) Bias detection and fairness analysis Governance and compliance documentation Communication and policy-making The Future of AI Hiring The AI job market is booming—and it's not slowing down. Whether you're a developer, analyst, project manager, or strategic thinker, there’s a growing need for your skills in the world of AI. For employers, now is the time to assess your workforce, upskill existing talent, and partner with experts who understand how to recruit for the future. Partner with Nelson Connects At Nelson Connects, our technology and professional staffing teams understand the AI landscape because we’re working in it every day. We can help you build high-performing teams that include AI, data, and automation experts, and we help candidates navigate their next big opportunity in this exciting space. 👉 Explore the AI talent market and view open roles here: www.nelsonconnects.com.	2025-07-01T00:00:00		https://www.nelsonconnects.com/learning-center/blogs/the-top-ai-roles-companies-are-hiring-for	[ { "date": "2025/07/01", "position": 44, "query": "artificial intelligence employers" }, { "date": "2025/07/01", "position": 47, "query": "artificial intelligence employers" }, { "date": "2025/07/01", "position": 57, "query": "artificial intelligence employment" } ]
Anthropic launches program to track AI's economic disruption	Anthropic launches program to track AI's economic disruption	https://www.ainews.com	[ "Alicia Shapiro" ]	The program comes amid growing unease over how equitably the gains from generative AI will be distributed. While some see opportunities for ...	Anthropic launches program to track AI's economic disruption As job losses loom, the company seeks data-driven insight into labor impacts and policy responses. Image Source: ChatGPT-4o Anthropic launches program to track AI's economic disruption As concerns about AI-driven job losses intensify, Anthropic is launching a new effort to better understand the technology’s broader economic effects. On Friday, the company introduced its Economic Futures Program, a research initiative focused on studying the labor market disruptions caused by artificial intelligence and developing policy ideas to address them. The program comes amid growing unease over how equitably the gains from generative AI will be distributed. While some see opportunities for entrepreneurship and GDP growth, others warn of potential mass displacement — particularly in white-collar jobs. “Everybody’s asking questions about what are the economic impacts [of AI], both positive and negative,” said Sarah Heck, head of policy programs and partnerships at Anthropic. “It’s really important to root these conversations in evidence and not have predetermined outcomes or views on what’s going to [happen].” A response to stark predictions The announcement follows a recent warning from Anthropic CEO Dario Amodei, who in May said AI could eliminate half of all entry-level white-collar jobs within the next one to five years and push unemployment as high as 20%. Asked whether the program’s goal is to directly address such job losses, Heck struck a careful tone. “I think the key goal is to figure out what is actually happening,” she said. “If there is job loss, then we should convene a collective group of thinkers to talk about mitigation. If there will be huge GDP expansion, great. We should also convene policy makers to figure out what to do with that. I don’t think any of this will be a monolith.” Building on existing data tools The new initiative expands on Anthropic’s Economic Index, launched in February, which aggregates and shares anonymized data to study AI’s impact on employment and productivity trends — a level of transparency uncommon among tech firms. The Economic Futures Program will focus on three areas: Grants for researchers studying AI’s effect on labor, productivity, and value creation. Create policy forums to develop and evaluate proposals that prepare for shifts in the economy. Build new datasets to track AI adoption and its economic consequences over time. Anthropic is opening applications for rapid research grants of up to $50,000, aiming to fund empirical studies and evidence-based policy proposals. These grants are intended to yield results within six months. “It doesn’t necessarily have to be peer-reviewed,” Heck said. “We want to be able to complete it within six months.” Anthropic is also organizing symposia in Washington, D.C., and Europe this fall, where selected policy proposals will be discussed. In addition, it plans to partner with independent research institutions, offering access to Claude API credits and other technical resources to support economic research. Beyond job loss: understanding transitions Heck emphasized that the initiative isn’t limited to studying labor market risks. The company also wants to examine how AI may reshape workflows, generate new types of jobs, and shift the value of specific skills. “We want to understand more about the transitions,” she said. “How do workflows happen in new ways? How are new jobs being created that nobody ever contemplated before? … How are certain skills remaining valuable while others are not?” One area of interest is fiscal policy — particularly how traditional models of value creation might evolve as AI adoption increases. “We really want to open the aperture here on things that can be studied,” said Heck. “Labor is certainly one of them, but it’s a much broader swath.” A different approach than OpenAI Anthropic’s launch follows a related — but differently focused — initiative from competitor OpenAI, which released an Economic Blueprint in January. That plan emphasizes infrastructure development and public AI adoption, including ideas like AI economic zones and expanded access to computing resources. While OpenAI’s proposal includes workforce training and support for AI literacy, it does not directly address potential job loss from AI automation. Its infrastructure projects, like the Stargate data center partnership with Oracle and SoftBank, are projected to create thousands of construction jobs — but mostly in the short term. What This Means Anthropic’s Economic Futures Program reflects a broader shift among AI companies as they begin to grapple with the real-world disruptions their technologies may bring. Unlike many corporate statements that highlight only opportunity, this initiative acknowledges both upside and risk — and commits resources to measure them. As policy makers look for credible data to shape future labor and economic policy, initiatives like this may help bridge the gap between Silicon Valley optimism and public concern. The clearer the picture of AI’s impact becomes, the better prepared societies may be to manage its effects — whether that means supporting displaced workers, reshaping education, or rethinking how value is defined in an automated economy. In a rapidly changing labor landscape, efforts to understand the full scope of AI’s economic impact are no longer optional — they’re essential.	2025-07-01T00:00:00		https://www.ainews.com/p/as-concerns-about-ai-driven-job-losses-intensify-anthropic-is-launching-a-new-effort-to-better-under	[ { "date": "2025/07/01", "position": 40, "query": "AI economic disruption" }, { "date": "2025/07/01", "position": 41, "query": "AI economic disruption" } ]
AI is now screening job candidates before humans ever see them	AI is now screening job candidates before humans ever see them	https://www.washingtonpost.com	[ "Danielle Abril", "Dan Lamothe", "Ellie Silverman", "Tatum Hunter", "Kc Hysmith", "Hannah Knowles", "Alexandra Frost", "Natalie Allison", "Matt Viser" ]	Virtual recruiters, or conversational AI agents, are making screening calls for some jobs, speeding up the hiring process and confusing some ...	Lumier Rodriguez flipped on the “open to work” setting on the professional social network LinkedIn to show that she was actively looking for contract work in April. She thought she’d instantly get responses from recruiters. She was met with silence. So she started actively applying to jobs. But rather than hear back from human recruiters, she received emails, calls and texts from artificial intelligence agents called virtual recruiters seeking interviews. By late June, she had been screened over the phone and via video by AI four times, leaving her to wonder: “Where are all the people?” Advertisement Advertisement Advertisement Advertisement “It felt a little bit like when you have a blind date and you don’t get enough information before going,” said Rodriguez, a Central Florida resident. “You don’t want to be rude and hang up … but I also felt catfished a little bit.” Advertisement Increasingly, job candidates are running into virtual recruiters for screenings. The conversational agents, built on large language models, help recruiting firms and hiring companies respond to every applicant, conduct interviews around-the-clock and find the best candidate in increasingly large talent pools. People who have experienced AI interviews have mixed reviews: surprisingly good or cold and confusing. “I realized I have to get ready for AI versus” humans, Rodriguez said. “I know it’s here to stay.” According to the Society for Human Resource Management (SHRM), a growing number of organizations use AI for recruiting to automate candidate searches and communicate with applicants during the interview process. Job applicants also are increasingly turning to AI to quickly tailor their résumés and cover letters, and to apply instantly. LinkedIn said applications for job openings have jumped 30 percent in two years, partially because of AI, with some jobs receiving hundreds of applications within a couple of hours. Advertisement There’s a high likelihood that people will someday get a call from AI, said Nichol Bradford, SHRM’s executive-in-residence. “We’re going to move from assuming it’s human and surprised by AI to assuming it’s AI.” Advertisement Advertisement How AI interviews work In cases where AI is used, job candidates are often informed that they may be contacted by a virtual recruiter during the application process. Shortly after, they may be sent a text message or email with further instructions, which may include a link to the interview or a request to schedule. Interviews, hosted by phone or video, can last anywhere between a few minutes to about 20, depending on the candidate’s experience and the hiring firm’s questions. Advertisement Questions may be basic to more complex, such as asking to describe specific scenarios and resolutions. Agents can end an interview if the candidate doesn’t meet minimum requirements. Some allow questions, though agents may not be able to answer all of them. (During a test call The Post conducted, one agent couldn’t provide any information about hours or the hiring company.) The agent then passes on summaries or transcripts, and sometimes video or audio recordings, to human recruiters. Staffing firms said some also have sentiment indicators that can flag issues, such as when a candidate gets frustrated. The firms that spoke to The Post said candidates can opt out of AI interviews without consequences. Agents collect information from screening calls to help human recruiters pick which candidates to push through to the next step, three companies that use the bots said. Advertisement Advertisement Advertisement Advertisement Job applicants say they are hearing from agents called Recruiter Jamie, Robin, Angel and Raya, all virtual recruiters from different companies. For many, this is a first, and some are taking to social media to ask their networks whether these agents real. Advertisement But recruiting firms say it’s just a matter of time before AI recruiter calls become the norm. “The best way to describe Angel is 24/7/365 technology that augments our human capital’s recruiting efforts,” said Adam Samples, president of talent solutions at Atrium, which uses the virtual recruiter called Angel. “It’s not making hiring decisions. Those are left for the recruiting team.” Some candidates who have been interviewed by virtual recruiters say agents interrupted or misunderstood them or felt impersonal, and they worried that their responses weren’t going to be accurately transcribed or evaluated. Jen Glaser, an instructional designer and Charlotte resident, tried to bypass the AI. But the agent told her that it was best to complete the virtual interview first and that she would then be routed to a human. The process sounded easy — five minutes with an agent. But she says her experience left her baffled. Advertisement The agent asked questions she thought a human wouldn’t have after reading her résumé. And while the bot sounded humanlike and responsive, it lacked empathy. After asking about her job experience, the bot cut her off midsentence. Then, after asking her to repeat an answer it didn’t understand, it replied, “No problem. I’ll call you back,” and hung up. Advertisement Advertisement “I thought it was silly,” she said, adding that it never called her back. “I just dropped it because I couldn’t get to a human.” Nisha Kaushal’s virtual recruiter seemed to have time limits, cutting her off when she spoke too long and leaving dead air if her answer was short. It left her concerned about how the AI might summarize her answers and whether a human would vet. Advertisement “Because AI isn’t perfect, who knows what it got,” said Kaushal, a Bay Area data scientist. “It did say a human recruiter would reach out if they liked me, but am I being filtered out by a human or AI?” Some virtual recruiters, such as Raya from IT consulting and staffing firm Akraya, score and rank candidates on criteria set by the employer. Human recruiters can review rank, as well as AI summaries, transcripts and video recordings. Raya can also detect when a candidate is distracted or reading another screen based on eye movement. Agents like Angel from Atrium and Anna AI from recruiting firm PSG Global Solutions mostly serve as information gatherers, requiring humans to do the evaluation. Advertisement Advertisement Advertisement Advertisement Sometimes a screening agent may be better than a human, such as in customer support or seasonal retail gigs, some staffing firms said. Recruiters scramble on a tight deadline, which can cause burnout and lower effectiveness. Advertisement Virtual recruiter “Anna doesn’t get tired,” David Koch, chief transformation and innovation officer at PSG, said. Candidates who meet Raya via video interview won’t have to dumb down their answers or translate technical terms because the AI is trained on subject expertise, said Amar Panchal, CEO of Akraya. “The quality of interviewing has improved,” he said. “You’re interviewing with an expert, so talk like one.” Tiffney Keller, who runs a professional training and coaching firm in Allen, Texas, said she was surprised to interview with AI but thought it was a good experience. “It makes you think with your instincts based on your knowledge,” she said, saying that a live transcript made her aware of the filler words she used. “I was very conscious about being polished and taking a second to think out my responses before just blurting it out.” Advertisement Jobseekers asked to interview with AI should be ready to demonstrate their skills and experience but also their authenticity, said Jackie Watrous, an analyst in the HR tech practice at Gartner. Those worried about scams should verify the agent’s legitimacy with the hiring firm. Often, firms will mention the bot on their website or application. If you’re uncomfortable being interviewed by AI, find out whether it’s necessary, say experts. As for Rodriguez, her worst experience was with an AI agent that didn’t understand her request to repeat the question. She found that hanging up made the agent call back and repeat itself. She says she has since had better AI interviews.	2025-06-30T00:00:00	2025/06/30	https://www.washingtonpost.com/business/2025/06/30/virtual-recruiters-ai-jobs/	[ { "date": "2025/07/01", "position": 96, "query": "AI hiring" }, { "date": "2025/07/01", "position": 96, "query": "AI hiring" } ]
When AI steals our jobs we create new ones - The Times	When AI steals our jobs we create new ones	https://www.thetimes.com	[ "Rohan Silva", "Rachel Sylvester", "Reid Hoffman", "Matt Rudd", "Jeremy Clarkson", "Jawad Iqbal", "Melissa Harrison", "Melanie Phillips", "The Times View" ]	That's the title of a seminal book by the American economist Tyler Cowen, looking at the impact of emerging technologies such as artificial ...	Average Is Over. That’s the title of a seminal book by the American economist Tyler Cowen, looking at the impact of emerging technologies such as artificial intelligence on the work we do. Cowen points to AI having a potentially profound effect, creating a “bifurcated” labour market: lots of low-paid roles at the bottom, those at the top getting paid even more, and middle-income white-collar occupations getting hollowed out by automation. Cowen’s book came out a decade ago but new data in recent days looks to support his predictions. The number of vacancies for UK graduates, apprenticeships and other junior positions has fallen by 31.9 per cent since the launch of the AI tool ChatGPT in November 2022, for instance. This sobering finding from Adzuna, the recruitment website, covers a period when British companies such as BT announced plans to use AI in place of thousands of human workers. Only this week, the Wall Street Journal revealed that the e-commerce giant Amazon was on the brink of using more robots than humans in its American warehouses. More than a million robots are now deployed across its distribution network. This automation drive may well mean fewer warehouse jobs in future. Amazon’s chief executive, Andy Jassy, has also announced that mid-tier white-collar roles are also likely to be cut. “As we roll out more generative AI and agents … we expect that this will reduce our total corporate workforce,” he has said. At the same time, we’re seeing evidence that the AI wave is driving higher salaries at the top end of the tech sector, where it is already having a real-world impact on software engineering. Large language models (LLMs) turn out to be really good at writing code. This is tough for entry-level and mid-tier programmers who are at risk of being replaced. But for the very best, these AI tools make them even more productive, and mean the companies they work for need fewer staff. Advertisement The current wave of AI start-ups is generating significant revenues with smaller teams to a greater degree than any previous generation of technology companies. One example: Midjourney, a popular AI image generator, hit £150 million of annual income with only ten workers — an eye-popping £15 million per staffer. So AI may come to mean fewer tech positions overall but those who are employed could earn astronomical sums. How astronomical? Well, over the past few weeks Meta’s founder, Mark Zuckerberg, has been offering signing bonuses worth tens of millions of pounds to elite AI programmers, with chunky salary and share packages on top. Zuckerberg is also investing £11 billion in the AI start-up Scale AI, primarily to recruit its founder Alexandr Wang, a 28-year-old MIT maths prodigy, to run Meta’s “superintelligence” AI division. Cowen puts it starkly: “If you are a programmer who is only slightly better than the bots, you may lose respect and income. The exceptional programmers … will command more attention and status. And as successive generations of [AI models] improve, these rewards will be doled out to a smaller and smaller percentage of humans.” In other words, lots of middle-class professions get squeezed, while the rewards at the top become ever greater. So far, so worrying — unless you happen to be an MIT whizz-kid. Over the long term, it does seem inevitable that AI will squeeze the life out of many white-collar roles. At the same time, if you’re a partner at a law firm or accountancy practice, you may well see your income increase, because you need fewer staff beneath you and your career strengths — human relationships, network, strategy and so on — are hard for AI models to replace. Most importantly though, what about the jobs that are lost? It’s obviously a tragedy for the families that relied on those salaries, and for the youngsters whose career plans are right now being upended. Advertisement That being said, as the brilliant business analyst Benedict Evans has observed, there’s nothing fundamentally novel about automation: humans have been using technology to automate work for two centuries. As Evans points out: “Every time we go through a wave of automation, whole classes of jobs go away, but new classes of jobs get created. There is frictional pain and dislocation in that process… but over time the total number of jobs doesn’t go down, and we have all become more prosperous.” Back in 1800, few could have imagined that a century later, hundreds of thousands of Britons would be working on the railways or lighting gas lamps in cities. And in 1900, no newspaper writer fretting about industrialisation could have foreseen that by 2000, large numbers of Brits would be working in roles as unimaginable as IT managers or HR professionals. If the past is any guide, the same will be true in Britain in a hundred years. It’s tricky to predict what the professions of the future will look like, but Cowen is a ballsier man than I am, and he’s forecasting that occupations involving “emotional intelligence will rise in importance, as it’s one of the few things machines can’t replicate”. Cowen therefore prophesies growth in fields such as care of the elderly and children, as well as roles such as coaches, therapists and personal trainers, because these tasks, which depend on interpersonal skills, are extremely hard for AI models to emulate. And Cowen — much like the cerebral Reid Hoffman, who co-founded LinkedIn — also foresees a surge in demand for human workers who know how to work effectively alongside AI. This might include data analysts and AI trainers, but also “hybrid professionals” such as medical staff and management consultants using AI to work more productively. Advertisement For anyone wanting to apply for one of these AI enabled careers some day, Cowen thinks “the key question will be: are you good at working with intelligent machines or not?” Of course, no one really knows how all this will play out, not even ChatGPT. (I’ve asked it.) But my hunch is this: the average may indeed be over, but another equilibrium will soon emerge — as it always does. And however turbulent the transition ends up being, this new normal will quickly come to feel pretty average. Daniel Finkelstein is away	2025-07-01T00:00:00		https://www.thetimes.com/comment/columnists/article/artificial-intelligence-jobs-ai-careers-w5vn3vd0g	[ { "date": "2025/07/01", "position": 92, "query": "AI impact jobs" } ]
Cloudflare Just Changed How AI Crawlers Scrape the Internet-at ...	Cloudflare Just Changed How AI Crawlers Scrape the Internet-at-Large; Permission-Based Approach Makes Way for A New Business Model	https://www.cloudflare.com	[]	“This is a critical step toward creating a fair value exchange on the Internet that protects creators, supports quality journalism and holds AI ...	This Press Release is also available in 日本語, 한국어, Deutsch, Français, Español (Latinoamérica), Nederlands, Indonesia, Tiếng Việt, แบบไทย. San Francisco, CA, July 1, 2025 – Cloudflare, Inc. (NYSE: NET), the leading connectivity cloud company, today announced it is now the first Internet infrastructure provider to block AI crawlers accessing content without permission or compensation, by default. Starting today, website owners can choose if they want AI crawlers to access their content, and decide how AI companies can use it. AI companies can also now clearly state their purpose – if their crawlers are used for training, inference, or search – to help website owners decide which crawlers to allow. Cloudflare's new default setting is the first step toward a more sustainable future for both content creators and AI innovators. For decades, the Internet has operated on a simple exchange: search engines index content and direct users back to original websites, generating traffic and ad revenue for websites of all sizes. This cycle rewards creators that produce quality content with money and a following, while helping users discover new and relevant information. That model is now broken. AI crawlers collect content like text, articles, and images to generate answers, without sending visitors to the original source – depriving content creators of revenue, and the satisfaction of knowing someone is viewing their content. If the incentive to create original, quality content disappears, society ends up losing, and the future of the Internet is at risk. “If the Internet is going to survive the age of AI, we need to give publishers the control they deserve and build a new economic model that works for everyone – creators, consumers, tomorrow’s AI founders, and the future of the web itself,” said Matthew Prince, co-founder and CEO of Cloudflare. “Original content is what makes the Internet one of the greatest inventions in the last century, and it's essential that creators continue making it. AI crawlers have been scraping content without limits. Our goal is to put the power back in the hands of creators, while still helping AI companies innovate. This is about safeguarding the future of a free and vibrant Internet with a new model that works for everyone.” “Cloudflare’s innovative approach to block AI crawlers is a game-changer for publishers and sets a new standard for how content is respected online. When AI companies can no longer take anything they want for free, it opens the door to sustainable innovation built on permission and partnership,” said Roger Lynch, CEO of Condé Nast. “This is a critical step toward creating a fair value exchange on the Internet that protects creators, supports quality journalism and holds AI companies accountable.” “We have long said that AI platforms must fairly compensate publishers and creators to use our content. We can now limit access to our content to those AI partners willing to engage in fair arrangements,” said Neil Vogel, CEO of Dotdash Meredith. “We're proud to support Cloudflare and look forward to using their tools to protect our content and the open web.” "As the largest publisher in the country, comprised of USA TODAY and over 200 local publications throughout the USA TODAY Network, blocking unauthorized scraping and the use of our original content without fair compensation is critically important,” said Renn Turiano, Chief Consumer and Product Officer of Gannett Media. “As our industry faces these challenges, we are optimistic the Cloudflare technology will help combat the theft of valuable IP.” “Creators and publishers around the world leverage Pinterest to expand their businesses, reach new audiences and directly measure their success. As AI continues to reshape the digital landscape, we are committed to building a healthy Internet infrastructure where content is used for its intended purpose, so creators and publishers can thrive,” said Bill Ready, CEO of Pinterest. “AI companies, search engines, researchers, and anyone else crawling sites have to be who they say they are. And any platform on the web should have a say in who is taking their content for what,” said Steve Huffman, co-founder and CEO of Reddit. “The whole ecosystem of creators, platforms, web users and crawlers will be better when crawling is more transparent and controlled, and Cloudflare’s efforts are a step in the right direction for everyone.” "We applaud Cloudflare for advocating for a sustainable digital ecosystem that benefits all stakeholders — the consumers who rely on credible information, the publishers who invest in its creation, and the advertisers who support its dissemination," said Vivek Shah, CEO of Ziff Davis. Enforcing a Permission-Based Model for the Internet Cloudflare powers one of the world’s largest networks, helping to manage and protect traffic for 20% of the web. The company handles trillions of requests daily, and thus has the world’s most advanced bot management solutions, accurately distinguishing between human users and AI crawlers. In September 2024, Cloudflare introduced the option to block AI crawlers in a single click. More than one million customers have since chosen this option, meant to be an aggressive but easy solution that halts scraping while they determine their AI strategy. Now, Cloudflare is taking the next step to enforce a permission-based model for AI crawlers. AI companies will now be required to obtain explicit permission from a website before scraping. Upon sign-up with Cloudflare, every new domain will now be asked if they want to allow AI crawlers, giving customers the choice upfront to explicitly allow or deny AI crawlers access. This significant shift means that every new domain starts with the default of control, and eliminates the need for webpage owners to manually configure their settings to opt out. Customers can easily check their settings and enable crawling at any time if they want their content to be freely accessed. Top Global Publishers, Media, & Technology Companies Embrace a Permission-Based Model for AI Crawling Leading content, media, and technology companies are in support of creating a more sustainable future that values original content, including: ADWEEK, The Arena Group, The Associated Press, The Atlantic, Atlas Obscura, BuzzFeed, Inc., Condé Nast, Digital Content Next, DOC, Dotdash Meredith, Drupal & Acquia, EngineEars, Evolve Media, Fortune, Gannett \| USA TODAY Network, Groundviews.org, Half Baked Newsletter, Hyperscience, IAB Tech Lab, Independent Media, International Center for Journalists, Internet Brands, Linkup, News/Media Alliance, O'Reilly Media, PMC, Pinterest, ProRata AI, Quora, Raptive, Reddit, SimpleFeed, Sky News Group, Snopes.com, SourceForge, Sovrn, Inc., Stack Overflow, StockTwits, SustainableMedia.Center, Third Door Media, TIME, Universal Music Group, Webflow, and Ziff Davis. AI Companies Can Now More Reliably Verify Their Crawlers Now Cloudflare is making the content ecosystem more transparent for AI companies and creators. The company recently proposed new ways for AI bots to authenticate themselves as well as for websites to identify those bots – giving creators and website owners new identification mechanisms and control over what crawlers they want to allow. Cloudflare is participating in the development of a new protocol to provide bot owners and AI agent developers with a public, standard way to identify themselves. Companies in Support of a Permission-Based Approach for AI Crawling ADWEEK: “As the front page and homepage for marketing, advertising and media industry leaders, ADWEEK’s position has been clear that we must be compensated for our investment grade journalism and information. I am thrilled Cloudflare has created a marketplace and mechanism that will enable us to properly participate in the promise LLMs have for our industry.” – Will Lee, CEO, ADWEEK “As the front page and homepage for marketing, advertising and media industry leaders, ADWEEK’s position has been clear that we must be compensated for our investment grade journalism and information. I am thrilled Cloudflare has created a marketplace and mechanism that will enable us to properly participate in the promise LLMs have for our industry.” – Will Lee, CEO, ADWEEK The Arena Group: “We think of our writers and content creators as entrepreneurs. Their work deserves protection. By blocking unauthorized AI crawlers, Cloudflare is not just defending content – it’s defending the future of creators and storytellers. This is a vital move toward a digital economy built on trust, permission and fair value.” – Paul Edmondson, CEO, The Arena Group “We think of our writers and content creators as entrepreneurs. Their work deserves protection. By blocking unauthorized AI crawlers, Cloudflare is not just defending content – it’s defending the future of creators and storytellers. This is a vital move toward a digital economy built on trust, permission and fair value.” – Paul Edmondson, CEO, The Arena Group The Associated Press: “The information landscape continues to change rapidly but the value of accurate, factual, nonpartisan journalism has never been more essential. We’re pleased to participate in this important framework that will help ensure intellectual property is protected and all content creators are fairly compensated for their work.” – Kristin Heitmann, Chief Revenue Officer, The Associated Press “The information landscape continues to change rapidly but the value of accurate, factual, nonpartisan journalism has never been more essential. We’re pleased to participate in this important framework that will help ensure intellectual property is protected and all content creators are fairly compensated for their work.” – Kristin Heitmann, Chief Revenue Officer, The Associated Press The Atlantic: “For too long, giant AI companies have built businesses on training data that they never paid for, and by scraping sites from whom they haven’t even asked permission. Now, thanks to Cloudflare, and its long-time commitment to the health of the open Web, this dynamic is finally going to change.” – Nicholas Thompson, CEO, The Atlantic “For too long, giant AI companies have built businesses on training data that they never paid for, and by scraping sites from whom they haven’t even asked permission. Now, thanks to Cloudflare, and its long-time commitment to the health of the open Web, this dynamic is finally going to change.” – Nicholas Thompson, CEO, The Atlantic Atlas Obscura: “As a media CEO, a former chief technology officer, and a longtime journalist, I am constantly reflecting on the moment we are in and how pivotal it is to the economics of public discourse. We have to get the calculus right now, so that publishers are treated fairly. As a customer of Cloudflare, I’m glad Cloudflare is looking for ways to create fair economics in the age of AI.” – Louise Story, CEO, Atlas Obscura “As a media CEO, a former chief technology officer, and a longtime journalist, I am constantly reflecting on the moment we are in and how pivotal it is to the economics of public discourse. We have to get the calculus right now, so that publishers are treated fairly. As a customer of Cloudflare, I’m glad Cloudflare is looking for ways to create fair economics in the age of AI.” – Louise Story, CEO, Atlas Obscura BuzzFeed, Inc.: “Cloudflare’s initiative is a crucial first step in publishers taking control of their content in the AI era. BuzzFeed is proud to stand with Cloudflare and our peers as part of our multipronged approach to fuel innovation responsibly while also securing the future of quality content and journalism.” – Ken Blom, Chief Business Officer, BuzzFeed, Inc. “Cloudflare’s initiative is a crucial first step in publishers taking control of their content in the AI era. BuzzFeed is proud to stand with Cloudflare and our peers as part of our multipronged approach to fuel innovation responsibly while also securing the future of quality content and journalism.” – Ken Blom, Chief Business Officer, BuzzFeed, Inc. Digital Content Next: “Permission is the law when it comes to copyrighted content - full stop. Cloudflare’s move brings technology to help ensure AI companies can’t sidestep the rules. It’s a critical step toward restoring a fair value exchange for trusted publishers and content creators.” – Jason Kint, CEO, Digital Content Next “Permission is the law when it comes to copyrighted content - full stop. Cloudflare’s move brings technology to help ensure AI companies can’t sidestep the rules. It’s a critical step toward restoring a fair value exchange for trusted publishers and content creators.” – Jason Kint, CEO, Digital Content Next DOC: “Generative AI has given the entire Internet industry an opportunity to reimagine the broken value exchange between publishers, consumers, and marketers. It takes companies with courage and conviction to break the decades-old practice of ‘steal first, apologize later’ that dominates the business models of most Internet giants. Kudos to Cloudflare and its founding participants for taking decisive and consequential action while there's still time.” – John Battelle, Co-founder and CEO, DOC “Generative AI has given the entire Internet industry an opportunity to reimagine the broken value exchange between publishers, consumers, and marketers. It takes companies with courage and conviction to break the decades-old practice of ‘steal first, apologize later’ that dominates the business models of most Internet giants. Kudos to Cloudflare and its founding participants for taking decisive and consequential action while there's still time.” – John Battelle, Co-founder and CEO, DOC Drupal & Acquia : "Large sites can afford the technical infrastructure to detect and block crawlers. Some can even pursue direct licensing deals with AI companies. However, most content creators can do neither. Cloudflare's solution isn't complete, but it establishes a crucial principle: AI training data has a price, and creators deserve to share in the value AI generates from their work." – Dries Buytaert, Founder and Project Lead of Drupal and Co-founder and Executive Chair of Acquia : "Large sites can afford the technical infrastructure to detect and block crawlers. Some can even pursue direct licensing deals with AI companies. However, most content creators can do neither. Cloudflare's solution isn't complete, but it establishes a crucial principle: AI training data has a price, and creators deserve to share in the value AI generates from their work." – Dries Buytaert, Founder and Project Lead of Drupal and Co-founder and Executive Chair of Acquia EngineEars: “In the world of music, copyright protection is everything for the livelihood of creators. EngineEars, the operating system for music creation, wholeheartedly supports Cloudflare pioneering technology that protects creator’s art and human expression from being stolen by AI firms.” – Derek Ali, 4x Grammy award winning audio engineer, founder and CEO, EngineEars “In the world of music, copyright protection is everything for the livelihood of creators. EngineEars, the operating system for music creation, wholeheartedly supports Cloudflare pioneering technology that protects creator’s art and human expression from being stolen by AI firms.” – Derek Ali, 4x Grammy award winning audio engineer, founder and CEO, EngineEars Evolve Media: “The rise of AI brings incredible opportunity, and there’s a clear need for a future where creators, publishers, and AI companies can thrive together. Cloudflare’s initiative supports that vision by promoting a more sustainable Internet through protecting the value of original content.” – Aaron Broder, Founder and CEO, Evolve Media “The rise of AI brings incredible opportunity, and there’s a clear need for a future where creators, publishers, and AI companies can thrive together. Cloudflare’s initiative supports that vision by promoting a more sustainable Internet through protecting the value of original content.” – Aaron Broder, Founder and CEO, Evolve Media Fortune: “The rise of AI presents incredible opportunities but also the moment for when publishers lock in proper attribution and compensation for our valuable intellectual property and carefully created content. Fortune sees a future of both active cooperation with AI companies to license content and suitable pay per read models. Because of that, we support Cloudflare's initiative to provide a framework that ensures equitable use of content by AI companies, and which contributes to sustainability for publishers.” – Anastasia Nyrkovskaya, CEO, Fortune “The rise of AI presents incredible opportunities but also the moment for when publishers lock in proper attribution and compensation for our valuable intellectual property and carefully created content. Fortune sees a future of both active cooperation with AI companies to license content and suitable pay per read models. Because of that, we support Cloudflare's initiative to provide a framework that ensures equitable use of content by AI companies, and which contributes to sustainability for publishers.” – Anastasia Nyrkovskaya, CEO, Fortune Groundviews.org: “After over two decades creating and editing critical content, especially in violent contexts defined by democratic backsliding, I've negotiated firsthand how civic media platforms struggle to operate, and rely on traffic to original work in order to sustain operations. Today, we face a chilling reality where AI systems scrape knowledge that citizen journalists often risk their lives to produce, and publish – extracting value without attribution or compensation. Cloudflare's permission-based approach represents a novel, and urgent, and meaningful intervention. For independent, small, local language based media networks, where international visibility often provides the only protection against censorship or worse, maintaining control over how our content is accessed, and monetised isn't merely about sustainability. It’s about preserving the incentive structures that enable bearing witness to continue. This initiative helps ensure that the next generation of investigative journalists, and civic media platforms can still afford to speak truth to power.” – Dr. Sanjana Hattotuwa, Founding Editor, Groundviews.org “After over two decades creating and editing critical content, especially in violent contexts defined by democratic backsliding, I've negotiated firsthand how civic media platforms struggle to operate, and rely on traffic to original work in order to sustain operations. Today, we face a chilling reality where AI systems scrape knowledge that citizen journalists often risk their lives to produce, and publish – extracting value without attribution or compensation. Cloudflare's permission-based approach represents a novel, and urgent, and meaningful intervention. For independent, small, local language based media networks, where international visibility often provides the only protection against censorship or worse, maintaining control over how our content is accessed, and monetised isn't merely about sustainability. It’s about preserving the incentive structures that enable bearing witness to continue. This initiative helps ensure that the next generation of investigative journalists, and civic media platforms can still afford to speak truth to power.” – Dr. Sanjana Hattotuwa, Founding Editor, Groundviews.org Half Baked Newsletter: “As a small publisher, we rely on the trust and engagement of our readers. Cloudflare’s move gives us the control we need to protect our content and continue building something real in a world of AI noise. It protects the creative spark that made the Internet worth exploring in the first place.” – Darragh Lucey, CEO, Half Baked Newsletter “As a small publisher, we rely on the trust and engagement of our readers. Cloudflare’s move gives us the control we need to protect our content and continue building something real in a world of AI noise. It protects the creative spark that made the Internet worth exploring in the first place.” – Darragh Lucey, CEO, Half Baked Newsletter Hyperscience: “As AI reshapes the way we create, consume, and interact with information, the value of original content, and the rights of those who create it, have never been more important. At Hyperscience, our success is built on original research and proprietary ML models, which our customers rely on to run transparent, compliant, and accurate AI workflows. We remain steadfast in our belief that creators, researchers, and technologists deserve recognition and protection in this new era of AI. We are excited to support this visionary Cloudflare initiative and believe that it will provide the framework to ensure that creators in every domain – including software development, healthcare and biotech, art and music, and journalism – benefit from an equitable and productive exchange with the LLMs and AI systems that leverage their work.” – Andrew Joiner, CEO, Hyperscience “As AI reshapes the way we create, consume, and interact with information, the value of original content, and the rights of those who create it, have never been more important. At Hyperscience, our success is built on original research and proprietary ML models, which our customers rely on to run transparent, compliant, and accurate AI workflows. We remain steadfast in our belief that creators, researchers, and technologists deserve recognition and protection in this new era of AI. We are excited to support this visionary Cloudflare initiative and believe that it will provide the framework to ensure that creators in every domain – including software development, healthcare and biotech, art and music, and journalism – benefit from an equitable and productive exchange with the LLMs and AI systems that leverage their work.” – Andrew Joiner, CEO, Hyperscience IAB Tech Lab: “What we're hearing from publishers is consistent. Their content is being pulled into AI systems without notice, and they're seeing real drops in traffic as a result. That’s why we launched the LLM Content Ingest API Initiative. To give publishers and brands the ability to decide how and when their content is accessed by AI tools. Cloudflare is helping make that possible by implementing parts of the framework, building the enforcement infrastructure behind it and moving the industry toward a more permission-based approach to content access.” – Shailley Singh, EVP of Product and COO, IAB Tech Lab “What we're hearing from publishers is consistent. Their content is being pulled into AI systems without notice, and they're seeing real drops in traffic as a result. That’s why we launched the LLM Content Ingest API Initiative. To give publishers and brands the ability to decide how and when their content is accessed by AI tools. Cloudflare is helping make that possible by implementing parts of the framework, building the enforcement infrastructure behind it and moving the industry toward a more permission-based approach to content access.” – Shailley Singh, EVP of Product and COO, IAB Tech Lab Independent Media: “Trusted, truly independent journalism is vital for us all, so it’s great to see Cloudflare demonstrating that ingenuity and innovation, not just legislation, can play an important role in securing a sustainable model for how publishers and AI companies co-exist. Creating a marketplace for high-quality content from responsible publishers is crucial – for the AI companies as well as the news industry.” – Christian Broughton, CEO, The Independent & Independent Media “Trusted, truly independent journalism is vital for us all, so it’s great to see Cloudflare demonstrating that ingenuity and innovation, not just legislation, can play an important role in securing a sustainable model for how publishers and AI companies co-exist. Creating a marketplace for high-quality content from responsible publishers is crucial – for the AI companies as well as the news industry.” – Christian Broughton, CEO, The Independent & Independent Media International Center for Journalists: “We see journalists across the world providing vital, original reporting to their communities, yet AI bots scrape their work for free while newsrooms struggle to stay open. At ICFJ+, we are working with small news sites -- beginning in Africa and across a variety of languages -- to help them protect and reclaim the value of their original work in the age of AI. We welcome this very promising initiative from Cloudflare.” – Sharon Moshavi, co-CEO of ICFJ+ and president of ICFJ “We see journalists across the world providing vital, original reporting to their communities, yet AI bots scrape their work for free while newsrooms struggle to stay open. At ICFJ+, we are working with small news sites -- beginning in Africa and across a variety of languages -- to help them protect and reclaim the value of their original work in the age of AI. We welcome this very promising initiative from Cloudflare.” – Sharon Moshavi, co-CEO of ICFJ+ and president of ICFJ Linkup: “High-quality, trusted content is the lifeblood of Linkup’s answer engine, ensuring we deliver reliable insights to our customers. Cloudflare’s program gives us a clear, AI-ready path to that content while respecting and rewarding its creators. We’re thrilled to help pioneer a model that safeguards a vibrant, sustainable future for the Internet.” – Phil Mizrahi, CEO and Co-founder, Linkup “High-quality, trusted content is the lifeblood of Linkup’s answer engine, ensuring we deliver reliable insights to our customers. Cloudflare’s program gives us a clear, AI-ready path to that content while respecting and rewarding its creators. We’re thrilled to help pioneer a model that safeguards a vibrant, sustainable future for the Internet.” – Phil Mizrahi, CEO and Co-founder, Linkup News/Media Alliance: “The rise of AI presents exciting opportunities, but in order for the industry to grow sustainably, it must do so in cooperation with publishers. Cloudflare's tools provide a strong framework for a more equitable exchange, offering a path for both industries to grow and thrive together. By valuing and protecting the rights of publishers, we're ensuring that they can continue to create the high-quality content that fuels AI innovation.” – Danielle Coffey, President & CEO, News/Media Alliance “The rise of AI presents exciting opportunities, but in order for the industry to grow sustainably, it must do so in cooperation with publishers. Cloudflare's tools provide a strong framework for a more equitable exchange, offering a path for both industries to grow and thrive together. By valuing and protecting the rights of publishers, we're ensuring that they can continue to create the high-quality content that fuels AI innovation.” – Danielle Coffey, President & CEO, News/Media Alliance O'Reilly Media: “It's so great to see Cloudflare standing up for publishers! Building a sustainable economy for AI starts with giving creators and publishers control over their content, rather than simply letting it be expropriated by AI platforms and application developers. Colonialism doesn't age well as a business model.” – Tim O'Reilly, Founder and CEO, O'Reilly Media “It's so great to see Cloudflare standing up for publishers! Building a sustainable economy for AI starts with giving creators and publishers control over their content, rather than simply letting it be expropriated by AI platforms and application developers. Colonialism doesn't age well as a business model.” – Tim O'Reilly, Founder and CEO, O'Reilly Media PMC: “We are very pleased to see the market-based solution that Cloudflare has offered and encourage others to join. Waiting for legal or government interventions to remedy the current challenges in our ecosystem isn't a strategy. Supporting sustainable models that compensate content creators fairly is an obligation that we all share as news and media organizations.” – Craig Perreault, Chief Strategy Officer, PMC “We are very pleased to see the market-based solution that Cloudflare has offered and encourage others to join. Waiting for legal or government interventions to remedy the current challenges in our ecosystem isn't a strategy. Supporting sustainable models that compensate content creators fairly is an obligation that we all share as news and media organizations.” – Craig Perreault, Chief Strategy Officer, PMC ProRata AI: "Our whole mission is to protect and elevate human creativity in the AI era. That’s why we’re proud to be one of the first AI companies to participate in Cloudflare’s initiative to create a new permission-based model for the Internet. We believe that creators and publishers deserve to be fairly compensated for the value they bring, and we’re thrilled to support Cloudflare in helping make that vision a reality." – Bill Gross, Founder & CEO, ProRata AI "Our whole mission is to protect and elevate human creativity in the AI era. That’s why we’re proud to be one of the first AI companies to participate in Cloudflare’s initiative to create a new permission-based model for the Internet. We believe that creators and publishers deserve to be fairly compensated for the value they bring, and we’re thrilled to support Cloudflare in helping make that vision a reality." – Bill Gross, Founder & CEO, ProRata AI Quora: “Publishers are essential to both the Internet's future and AI's growth. At Quora, we believe these two industries can thrive together, and we're committed to supporting initiatives like Pay Per Crawl that create mutual value and sustainable growth for the long term." – Ricky Arai-Lopez, Head of Product, Quora “Publishers are essential to both the Internet's future and AI's growth. At Quora, we believe these two industries can thrive together, and we're committed to supporting initiatives like Pay Per Crawl that create mutual value and sustainable growth for the long term." – Ricky Arai-Lopez, Head of Product, Quora Raptive: “Digital publishers fuel the Internet with original ideas and expertise, and they deserve control over how their work is used. This move toward a permission-based model is a meaningful step—restoring fair value, protecting creativity, and ensuring a better future for those who make the web worth visiting.” — Michael Sanchez, CEO, Raptive “Digital publishers fuel the Internet with original ideas and expertise, and they deserve control over how their work is used. This move toward a permission-based model is a meaningful step—restoring fair value, protecting creativity, and ensuring a better future for those who make the web worth visiting.” — Michael Sanchez, CEO, Raptive SimpleFeed: “As the leader in content syndication, SimpleFeed is on the front lines of the battle with AI bots. We are excited for solutions that bring publishers greater transparency and fair compensation for their work. The world needs healthy publishers and we welcome opportunities to partner with companies building a new ecosystem on more equitable incentives.” – Mark Carlson, CEO, SimpleFeed “As the leader in content syndication, SimpleFeed is on the front lines of the battle with AI bots. We are excited for solutions that bring publishers greater transparency and fair compensation for their work. The world needs healthy publishers and we welcome opportunities to partner with companies building a new ecosystem on more equitable incentives.” – Mark Carlson, CEO, SimpleFeed Sky News Group: “This permission-based model will help secure the future of quality digital journalism, which is our commitment. Sky News is all about providing 'the full story, first'– so we wanted to be among the first to join Cloudflare's framework for setting fair terms of trade in news. We'll help design the future of these services as video becomes an ever-larger part of both crawling and publishing.” – David Rhodes, Executive Chairman, Sky News Group “This permission-based model will help secure the future of quality digital journalism, which is our commitment. Sky News is all about providing 'the full story, first'– so we wanted to be among the first to join Cloudflare's framework for setting fair terms of trade in news. We'll help design the future of these services as video becomes an ever-larger part of both crawling and publishing.” – David Rhodes, Executive Chairman, Sky News Group Snopes.com : “If the shift toward AI continues to erode web traffic, I worry that most premium publishers will have no choice but to adopt a subscription-only model. The whole Internet behind a paywall isn’t good for anyone. That’s why I’m optimistic about Cloudflare’s efforts to protect publishers and help us find a sustainable solution that benefits all sides.” – Chris Richmond, CEO, Snopes.com : “If the shift toward AI continues to erode web traffic, I worry that most premium publishers will have no choice but to adopt a subscription-only model. The whole Internet behind a paywall isn’t good for anyone. That’s why I’m optimistic about Cloudflare’s efforts to protect publishers and help us find a sustainable solution that benefits all sides.” – Chris Richmond, CEO, Snopes.com SourceForge: “At SourceForge, we empower millions of businesses and developers by providing a trusted platform for discovering software through authentic user-generated B2B software reviews and open source projects. Cloudflare's permission-based model for AI crawlers is a vital advancement that helps protect original content while fostering innovation. By giving publishers control over how their content is accessed and used, Cloudflare supports a fairer digital ecosystem that benefits publishers, creators, developers, and users alike. We’re excited to partner with Cloudflare in promoting transparency and responsible AI practices across the Internet.” – Logan Abbott, President, SourceForge “At SourceForge, we empower millions of businesses and developers by providing a trusted platform for discovering software through authentic user-generated B2B software reviews and open source projects. Cloudflare's permission-based model for AI crawlers is a vital advancement that helps protect original content while fostering innovation. By giving publishers control over how their content is accessed and used, Cloudflare supports a fairer digital ecosystem that benefits publishers, creators, developers, and users alike. We’re excited to partner with Cloudflare in promoting transparency and responsible AI practices across the Internet.” – Logan Abbott, President, SourceForge Sovrn, Inc.: “For more than a decade, Sovrn has relentlessly championed the open and free Internet. While AI represents incredible opportunities to advance human knowledge and abundance, we are putting at risk creators and publishers who make the Internet indispensable. We collectively need to ensure a balance where creators and publishers can continue their important work and thrive in the future, and that's why Cloudflare's work is so critical to this next chapter of the Internet.” – Walter Knapp, CEO, Sovrn, Inc. “For more than a decade, Sovrn has relentlessly championed the open and free Internet. While AI represents incredible opportunities to advance human knowledge and abundance, we are putting at risk creators and publishers who make the Internet indispensable. We collectively need to ensure a balance where creators and publishers can continue their important work and thrive in the future, and that's why Cloudflare's work is so critical to this next chapter of the Internet.” – Walter Knapp, CEO, Sovrn, Inc. Stack Overflow: “We applaud Cloudflare for all they are doing to support the new business models of the modern day Internet. Community platforms that fuel LLMs should be compensated for their contributions so they can invest back in their communities. We've been very vocal around the importance and integrity of socially responsible AI practices. Our mission is to set new standards with vetted, trusted, and accurate data that will be the foundation on which technology solutions are built and delivered to our users. We believe attribution is non-negotiable, that human review of content is necessary and community feedback is the only way to ensure GenAI tools accelerate innovation and not misinformation.” – Prashanth Chandrasekar, CEO, Stack Overflow “We applaud Cloudflare for all they are doing to support the new business models of the modern day Internet. Community platforms that fuel LLMs should be compensated for their contributions so they can invest back in their communities. We've been very vocal around the importance and integrity of socially responsible AI practices. Our mission is to set new standards with vetted, trusted, and accurate data that will be the foundation on which technology solutions are built and delivered to our users. We believe attribution is non-negotiable, that human review of content is necessary and community feedback is the only way to ensure GenAI tools accelerate innovation and not misinformation.” – Prashanth Chandrasekar, CEO, Stack Overflow StockTwits: “At Stocktwits, original content and real-time conversation are at the heart of our community. As AI transforms how information is discovered and used, it's essential that innovation doesn't come at the expense of the creators and platforms driving it. We’re proud to support Cloudflare’s efforts to ensure a more transparent, fair, and sustainable Internet.” – Howard Lindzon, Founder and CEO, StockTwits “At Stocktwits, original content and real-time conversation are at the heart of our community. As AI transforms how information is discovered and used, it's essential that innovation doesn't come at the expense of the creators and platforms driving it. We’re proud to support Cloudflare’s efforts to ensure a more transparent, fair, and sustainable Internet.” – Howard Lindzon, Founder and CEO, StockTwits SustainableMedia.Center: “In order for the Internet to remain the critical source of news and information it has been for web users, we need to dramatically re-think the business model for users and publishers. Cloudflare’s vision aligns strongly with the Sustainable Media Center’s mission to give GenZ users control of their digital lives. We applaud this critical effort.” – Steven Rosenbaum, Co-founder and Executive Director, SustainableMedia.Center “In order for the Internet to remain the critical source of news and information it has been for web users, we need to dramatically re-think the business model for users and publishers. Cloudflare’s vision aligns strongly with the Sustainable Media Center’s mission to give GenZ users control of their digital lives. We applaud this critical effort.” – Steven Rosenbaum, Co-founder and Executive Director, SustainableMedia.Center Third Door Media: “For years, publishers large and small have played by the rules, creating high-quality content in exchange for visibility and traffic. But AI shifts the game. Cloudflare’s approach recognizes that content has value beyond clicks. It’s time we build a new framework, one that respects the work of journalists and creators while fueling the future of AI responsibly. I, for one, am hoping to see more solutions for publishers in the marketplace.” – Marc Sirkin, CEO, Third Door Media “For years, publishers large and small have played by the rules, creating high-quality content in exchange for visibility and traffic. But AI shifts the game. Cloudflare’s approach recognizes that content has value beyond clicks. It’s time we build a new framework, one that respects the work of journalists and creators while fueling the future of AI responsibly. I, for one, am hoping to see more solutions for publishers in the marketplace.” – Marc Sirkin, CEO, Third Door Media TIME: “At TIME, we’re committed to advancing innovation without compromising the integrity of original journalism. Cloudflare’s initiative is a meaningful step toward building a healthier AI ecosystem—one that respects the value of trusted content and supports the creators behind it.” – Mark Howard, Chief Operating Officer, TIME “At TIME, we’re committed to advancing innovation without compromising the integrity of original journalism. Cloudflare’s initiative is a meaningful step toward building a healthier AI ecosystem—one that respects the value of trusted content and supports the creators behind it.” – Mark Howard, Chief Operating Officer, TIME Universal Music Group: “We welcome this new initiative from Cloudflare, that will help address the indiscriminate, disruptive, and unauthorized scraping of both creative and commercial IP by AI model developers and support new licensing. At UMG, we have always embraced innovation and new technologies, and firmly believe that AI, when used ethically, transparently, and respectfully of copyright and human creativity, has the opportunity to introduce significant new avenues for creativity and future monetization.” – Boyd Muir, Chief Operating Officer, Universal Music Group “We welcome this new initiative from Cloudflare, that will help address the indiscriminate, disruptive, and unauthorized scraping of both creative and commercial IP by AI model developers and support new licensing. At UMG, we have always embraced innovation and new technologies, and firmly believe that AI, when used ethically, transparently, and respectfully of copyright and human creativity, has the opportunity to introduce significant new avenues for creativity and future monetization.” – Boyd Muir, Chief Operating Officer, Universal Music Group Webflow: “With millions of websites powered by Webflow, we see how quickly AI-driven discovery is becoming the norm. Cloudflare’s opt-in model brings structure and permission into that shift, giving content owners and marketing teams more control over how their work is accessed and reused. It’s a necessary evolution, and a meaningful step toward a more accountable AEO ecosystem.” – Allan Leinwand, CTO, Webflow To learn more, please check out the resources below: About Cloudflare Cloudflare, Inc. (NYSE: NET) is the leading connectivity cloud company on a mission to help build a better Internet. It empowers organizations to make their employees, applications and networks faster and more secure everywhere, while reducing complexity and cost. Cloudflare’s connectivity cloud delivers the most full-featured, unified platform of cloud-native products and developer tools, so any organization can gain the control they need to work, develop, and accelerate their business. Powered by one of the world’s largest and most interconnected networks, Cloudflare blocks billions of threats online for its customers every day. It is trusted by millions of organizations – from the largest brands to entrepreneurs and small businesses to nonprofits, humanitarian groups, and governments across the globe. Learn more about Cloudflare’s connectivity cloud at cloudflare.com/connectivity-cloud. Learn more about the latest Internet trends and insights at radar.cloudflare.com. Follow us: Blog \| X \| LinkedIn \| Facebook \| Instagram Forward-Looking Statements This press release contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which statements involve substantial risks and uncertainties. In some cases, you can identify forward-looking statements because they contain words such as “may,” “will,” “should,” “expect,” “explore,” “plan,” “anticipate,” “could,” “intend,” “target,” “project,” “contemplate,” “believe,” “estimate,” “predict,” “potential,” or “continue,” or the negative of these words, or other similar terms or expressions that concern Cloudflare’s expectations, strategy, plans, or intentions. However, not all forward-looking statements contain these identifying words. 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Actual results could differ materially from those stated or implied in forward-looking statements due to a number of factors, including but not limited to, risks detailed in Cloudflare’s filings with the Securities and Exchange Commission (SEC), including Cloudflare’s Quarterly Report on Form 10-Q filed on May 8, 2025, as well as other filings that Cloudflare may make from time to time with the SEC. The forward-looking statements made in this press release relate only to events as of the date on which the statements are made. Cloudflare undertakes no obligation to update any forward-looking statements made in this press release to reflect events or circumstances after the date of this press release or to reflect new information or the occurrence of unanticipated events, except as required by law. Cloudflare may not actually achieve the plans, intentions, or expectations disclosed in Cloudflare’s forward-looking statements, and you should not place undue reliance on Cloudflare’s forward-looking statements. © 2025 Cloudflare, Inc. All rights reserved. Cloudflare, the Cloudflare logo, and other Cloudflare marks are trademarks and/or registered trademarks of Cloudflare, Inc. in the U.S. and other jurisdictions. All other marks and names referenced herein may be trademarks of their respective owners.	2025-07-01T00:00:00		https://www.cloudflare.com/press-releases/2025/cloudflare-just-changed-how-ai-crawlers-scrape-the-internet-at-large/	[ { "date": "2025/07/01", "position": 97, "query": "AI journalism" }, { "date": "2025/07/01", "position": 95, "query": "artificial intelligence journalism" }, { "date": "2025/07/01", "position": 76, "query": "AI employers" }, { "date": "2025/07/01", "position": 93, "query": "AI journalism" } ]
Salesforce AI Shock: What 50% AI Work Means for Your Business Now	AI Workforce Transformation: Salesforce's 50% AI Work Revolution	https://www.e-spincorp.com	[ "Daw Phyu Pyar Pwint", "Jean Ariane H. Evangelista", ".Pp-Multiple-Authors-Boxes-Wrapper.Pp-Multiple-Authors-Layout-Boxed.Multiple-Authors-Target-The-Content .Pp-Author-Boxes-Avatar Img", "Width", "Important", "Height", "Border-Radius", ".Pp-Multiple-Authors-Boxes-Wrapper.Pp-Multiple-Authors-Layout-Boxed.Multiple-Authors-Target-The-Content .Pp-Author-Boxes-Meta A", "Background-Color", "Color" ]	AI Workforce Transformation: Salesforce CEO confirms 50% AI-driven tasks. Prepare for workforce shifts, from big tech to small businesses.	The recent statement from Salesforce CEO Marc Benioff, where he claims that up to 50% of his company’s work (with 76,000 employees) is now performed by AI, sends a strong signal about the accelerating pace of AI transformation. This isn’t just about incremental improvements; it suggests a fundamental shift in how work is done, potentially leading to significant workforce restructuring. The Dawn of a “Digital Labor Revolution” Benioff’s remarks, echoed by other tech leaders like Microsoft’s Satya Nadella, paint a picture of a “digital labor revolution.” The idea is not necessarily mass unemployment, but a re-allocation of human effort towards “higher-value work” as AI takes over repetitive, lower-value tasks. Salesforce, for instance, is reportedly seeing a reduction in hiring for roles like software engineering and customer service, while simultaneously planning an increase in sales roles, indicating a strategic shift rather than outright elimination of jobs. However, the question remains: if a giant like Salesforce can achieve 50% AI-driven work, what does this mean for its 76,000 employees, and more broadly, for the 80% of smaller businesses that dominate the market and revenue landscape? The Imminent Impact on Workforce and Businesses For large corporations like Salesforce: While Benioff speaks of moving to “higher-value work,” the sheer scale of AI adoption suggests that a significant portion of the current workforce might need to be reskilled or redeployed. This could manifest as: Quarterly layoffs: As AI efficiencies become clearer, companies might opt for regular, targeted layoffs in roles that are increasingly automated. As AI efficiencies become clearer, companies might opt for regular, targeted layoffs in roles that are increasingly automated. Zero-based staffing: This extreme practice involves re-evaluating every role and hiring only those aligned with the AI-centric future, potentially leaving a large portion of the existing workforce vulnerable. This extreme practice involves re-evaluating every role and hiring only those aligned with the AI-centric future, potentially leaving a large portion of the existing workforce vulnerable. Reskilling and upskilling initiatives: Forward-thinking companies will invest heavily in training their employees to work alongside AI, focusing on skills like AI supervision, strategic thinking, and human-AI collaboration. For the 80% of smaller businesses: This is where the challenge becomes even more acute. Small businesses often lack the scale benefits, financial resources, and dedicated R&D departments of large corporations. Yet, to survive, they must embrace AI. Here’s what they need to consider: AI as an Equalizer, Not a Destroyer: While large corporations can invest in bespoke AI solutions, cloud-based, accessible, and affordable AI tools are rapidly emerging. Small businesses can leverage these to automate tasks, improve efficiency, and enhance customer experience without massive upfront investments. Focus on Niche and Personalization: AI can help small businesses understand their customers on a deeper level, allowing them to offer highly personalized services and products that large corporations, despite their scale, might struggle to replicate with the same level of intimacy. This is a competitive advantage for SMEs. Strategic AI Adoption – Start Small, Scale Smart: Identify Pain Points: Begin by identifying repetitive or time-consuming tasks where AI can offer immediate value (e.g., customer service chatbots, automated marketing, inventory management, data entry). Begin by identifying repetitive or time-consuming tasks where AI can offer immediate value (e.g., customer service chatbots, automated marketing, inventory management, data entry). Choose the Right Tools: There are thousands of AI solutions available, many designed for SMEs. Research and select tools that align with specific business objectives and budget. There are thousands of AI solutions available, many designed for SMEs. Research and select tools that align with specific business objectives and budget. Prioritize Data Quality: AI thrives on data. Small businesses need to ensure their data is clean, organized, and accessible to maximize AI’s effectiveness. AI thrives on data. Small businesses need to ensure their data is clean, organized, and accessible to maximize AI’s effectiveness. Phased Implementation: Don’t try to transform everything at once. Implement AI in small, manageable phases, monitor performance, gather feedback, and iterate. Upskilling the Existing Workforce: Instead of fearing job displacement, small business owners should view AI as an opportunity to empower their employees. Training staff in AI literacy, data analysis, and human-AI collaboration will be crucial. This could involve: Internal training programs: Leveraging online courses and certifications. Leveraging online courses and certifications. Cross-functional teams: Encouraging employees from different departments to collaborate on AI projects. Encouraging employees from different departments to collaborate on AI projects. Fostering a “discovery mentality”: Creating an environment where employees are encouraged to experiment with AI tools and identify new applications. Leverage AI for Competitive Intelligence: AI tools can help small businesses analyze competitor strategies, market trends, and customer behavior, enabling them to make data-driven decisions and adapt quickly to market changes. Cost Efficiency and Productivity Gains: AI can significantly reduce operational costs by automating mundane tasks, freeing up human capital to focus on strategic initiatives and customer relationships. This can lead to increased productivity per employee, a critical factor for SMEs competing with larger players. Embrace Agility and Innovation: Small businesses, by their nature, are often more agile than large corporations. This agility can be a powerful asset in the AI era. They can experiment faster, adapt to new technologies more quickly, and innovate in niche areas where large companies might be slower to move. Are You Ready? The Future is Now. The “future now” is indeed about change, and AI transformation is undeniably one of the most significant digital transformation agendas for all businesses. The shift isn’t a question of if but how and when. For small businesses, the key to survival and growth in this AI-driven landscape lies in proactive engagement. It’s about being more than just reactive to quarterly layoffs or incremental shifts. It’s about: Mindset Shift: Recognizing AI not as a threat to eliminate jobs, but as a powerful tool to augment human capabilities, enhance efficiency, and create new opportunities. Recognizing AI not as a threat to eliminate jobs, but as a powerful tool to augment human capabilities, enhance efficiency, and create new opportunities. Strategic Investment: Even with limited resources, smart investments in accessible AI tools and employee training can yield significant returns. Even with limited resources, smart investments in accessible AI tools and employee training can yield significant returns. Continuous Learning and Adaptation: The AI landscape is evolving rapidly. Businesses that commit to continuous learning and are willing to adapt their strategies will be the ones that thrive. The companies that succeed will be those that view AI as a partner in innovation and productivity, allowing their human workforce to focus on creativity, critical thinking, and the human connection that AI, for all its power, still cannot fully replicate. The question is no longer “are you ready?” but “what are you doing to get ready, right now?” The Unspoken Strategy: Demand, Metrics, and Workforce Optimization Let’s unpack these seemingly disparate corporate directives and their underlying objectives, especially in an AI-driven world. 1. The “Return to Office” Mandate: A Multi-faceted Playbook The insistent demand for employees to return to the office, often under threat of termination, is rarely just about fostering collaboration or company culture, particularly for large, geographically dispersed corporations. While these are often cited reasons, other, less palatable, motives are likely at play: De-facto Workforce Reduction: For many employees, the forced return to a long commute and rigid office hours, especially after years of remote flexibility, is a significant deterrent. This can lead to voluntary resignations, effectively achieving a “quiet layoff” without the financial and reputational costs associated with formal severance packages. It’s a way to shed employees who are less committed to the new (old) work model or who find the commute untenable, without explicitly firing them. For many employees, the forced return to a long commute and rigid office hours, especially after years of remote flexibility, is a significant deterrent. This can lead to voluntary resignations, effectively achieving a “quiet layoff” without the financial and reputational costs associated with formal severance packages. It’s a way to shed employees who are less committed to the new (old) work model or who find the commute untenable, without explicitly firing them. Performance Monitoring and Control: In-office presence allows for more traditional, visible monitoring of employee activity. While not necessarily a direct measure of productivity, it creates an environment where managers can perceive greater control and accountability. This aligns with the historical corporate preference for visible management, even if the actual impact on productivity is debatable in a knowledge-work context. In-office presence allows for more traditional, visible monitoring of employee activity. While not necessarily a direct measure of productivity, it creates an environment where managers can greater control and accountability. This aligns with the historical corporate preference for visible management, even if the actual impact on productivity is debatable in a knowledge-work context. Justification for Real Estate Holdings: Many large corporations have significant investments in commercial real estate. Empty offices are a drain on resources and a poor look for shareholders. Mandating a return justifies these expenditures and keeps assets “productive,” even if a portion of the workforce could perform equally well or better remotely. Many large corporations have significant investments in commercial real estate. Empty offices are a drain on resources and a poor look for shareholders. Mandating a return justifies these expenditures and keeps assets “productive,” even if a portion of the workforce could perform equally well or better remotely. Identifying the “Committed”: Those who do return, especially those who move closer, demonstrate a higher level of commitment (or desperation) to the company’s dictates. This signals a workforce willing to conform, which can be seen as desirable by management seeking to streamline operations and reduce potential friction during future changes. 2. “Enhanced Performance Reviews” and New Metrics: The Path to Justified Cuts The introduction of “new dimensions and metrics” into performance reviews, particularly when it feels sudden or disconnected from previous evaluation criteria, can also be a precursor to workforce reductions. Quantifying the “Unproductive”: When companies anticipate the need to downsize, they often need a seemingly objective and defensible reason. New metrics, especially those that are difficult to meet or are tied to new, AI-driven efficiencies, can easily identify employees who don’t “measure up” to the newly defined standards. When companies anticipate the need to downsize, they often need a seemingly objective and defensible reason. New metrics, especially those that are difficult to meet or are tied to new, AI-driven efficiencies, can easily identify employees who don’t “measure up” to the newly defined standards. Shifting Goalposts: By changing the rules of engagement, companies can make it harder for existing employees to meet expectations, even if their previous performance was stellar. This creates a pipeline of individuals whose underperformance can be “justified” for termination. By changing the rules of engagement, companies can make it harder for existing employees to meet expectations, even if their previous performance was stellar. This creates a pipeline of individuals whose underperformance can be “justified” for termination. AI Readiness as a Metric: Increasingly, these new metrics might include “AI fluency,” “ability to integrate with AI tools,” or “contribution to AI-driven initiatives.” Employees who haven’t embraced AI or aren’t seen as adaptable to new technologies will naturally fall short, providing a clean rationale for their removal. Increasingly, these new metrics might include “AI fluency,” “ability to integrate with AI tools,” or “contribution to AI-driven initiatives.” Employees who haven’t embraced AI or aren’t seen as adaptable to new technologies will naturally fall short, providing a clean rationale for their removal. A Veneer of Fairness: While the outcome is workforce reduction, the process is dressed up as a rigorous, merit-based performance evaluation. This helps mitigate legal challenges and maintains a facade of fairness for remaining employees and external stakeholders. The Investor’s Mind: Why Not Scale AI Indefinitely? This is where the investor’s perspective becomes critical, and it illuminates the driving force behind these strategies. For an investor who has poured massive amounts of capital into a corporation, the appeal of AI is undeniable and profoundly logical: Infinite Scalability, Zero Human Constraints: AI doesn’t get sick, demand raises, need vacation, or require benefits. It works 24/7, across time zones, without complaint. Once the initial investment in AI infrastructure and development is made, the cost per unit of output can approach zero, especially for tasks that are highly automatable. From a purely economic standpoint, why wouldn’t an investor want to replace every possible human function with a tirelessly efficient AI? AI doesn’t get sick, demand raises, need vacation, or require benefits. It works 24/7, across time zones, without complaint. Once the initial investment in AI infrastructure and development is made, the cost per unit of output can approach zero, especially for tasks that are highly automatable. From a purely economic standpoint, why wouldn’t an investor want to replace every possible human function with a tirelessly efficient AI? Predictability and Reliability: Humans are inherently unpredictable. They have good days and bad days, personal lives interfere with work, and morale fluctuates. AI, conversely, offers highly predictable and reliable performance within its programmed parameters. This predictability translates directly into more stable projections for revenue and profit, which is music to an investor’s ears. Humans are inherently unpredictable. They have good days and bad days, personal lives interfere with work, and morale fluctuates. AI, conversely, offers highly predictable and reliable performance within its programmed parameters. This predictability translates directly into more stable projections for revenue and profit, which is music to an investor’s ears. Reduced Overhead and Risk: Every employee represents a significant overhead (salary, benefits, office space, management time, legal risks, potential for unionization, etc.). By replacing human labor with AI, companies drastically reduce these recurring costs and mitigate a host of human-related risks. Every employee represents a significant overhead (salary, benefits, office space, management time, legal risks, potential for unionization, etc.). By replacing human labor with AI, companies drastically reduce these recurring costs and mitigate a host of human-related risks. Accelerated Growth and Market Dominance: If a company can achieve 50% (or more) of its work through AI, it can theoretically scale its operations much faster and more aggressively than competitors reliant on human labor. This promises rapid market dominance and superior returns. If a company can achieve 50% (or more) of its work through AI, it can theoretically scale its operations much faster and more aggressively than competitors reliant on human labor. This promises rapid market dominance and superior returns. The “Unemotional” Decision: Investors operate on logic and returns. The emotional impact of job displacement, while significant to individuals and society, is often a secondary concern in the pursuit of maximizing shareholder value. The argument “AI can do it better, faster, cheaper” is incredibly compelling. The Cold Calculus: If an investor sees that AI can perform a task with 90% accuracy for 10% of the cost of a human, and scale infinitely, the decision to invest in AI-driven automation over human employment becomes a straightforward, albeit ruthless, economic imperative. The Boiling Frog Syndrome: When Employees Live in the Old World The concept of the “boiling frog” perfectly describes the plight of employees who remain “living in the old world” while the corporate environment undergoes a rapid, AI-driven transformation. Gradual Changes, Insidious Impact: The changes aren’t always sudden. It starts with a new software tool, then a new performance metric, then a “suggestion” to automate certain aspects of a job. Each individual change might seem minor, but cumulatively, they chip away at the necessity and value of human roles. The water gets hotter slowly. The changes aren’t always sudden. It starts with a new software tool, then a new performance metric, then a “suggestion” to automate certain aspects of a job. Each individual change might seem minor, but cumulatively, they chip away at the necessity and value of human roles. The water gets hotter slowly. Lack of Awareness or Denial: Many employees, comfortable in their routines and skills, may genuinely be unaware of the depth of the AI shift. Others might be in denial, believing their jobs are “safe” due to perceived complexity or human-centricity. “My job requires critical thinking/creativity/empathy – AI can’t do that!” they might think, failing to recognize that AI is increasingly capable of many aspects of these very skills, and at the very least, can augment or streamline them to the point where fewer humans are needed. Many employees, comfortable in their routines and skills, may genuinely be unaware of the depth of the AI shift. Others might be in denial, believing their jobs are “safe” due to perceived complexity or human-centricity. “My job requires critical thinking/creativity/empathy – AI can’t do that!” they might think, failing to recognize that AI is increasingly capable of many aspects of these very skills, and at the very least, can augment or streamline them to the point where fewer humans are needed. Resistance to Change: Even if aware, some employees may resist upskilling or adapting to new AI tools, preferring their established ways of working. This inertia, while understandable on a human level, makes them increasingly vulnerable. Even if aware, some employees may resist upskilling or adapting to new AI tools, preferring their established ways of working. This inertia, while understandable on a human level, makes them increasingly vulnerable. Focus on Immediate Tasks, Not Future Trends: Employees are often busy with their day-to-day responsibilities, leaving little time or mental bandwidth to assess long-term industry trends or actively re-skill for the future. The focus is on keeping the current boat afloat, not preparing for a completely different kind of vessel. Employees are often busy with their day-to-day responsibilities, leaving little time or mental bandwidth to assess long-term industry trends or actively re-skill for the future. The focus is on keeping the current boat afloat, not preparing for a completely different kind of vessel. Corporate Communication Gaps (Intentional or Otherwise): While some companies are transparent about AI’s impact, others might use ambiguous language to avoid alarm or premature panic. This can leave employees in the dark about the true extent of the changes coming. The Inevitable Outcome: For the employee caught in this “boiling water,” the outcome is predictable. As AI capabilities expand and the investor pressure to scale automation intensifies, those who haven’t adapted will find their roles diminished, their skills obsolete, and ultimately, their jobs eliminated. The “incremental or quarterly workforce reduction” is not just a possibility; it becomes a sustained reality. The Call to Action for the Workforce The implications are clear for individuals: Proactive AI Literacy: Don’t wait for your company to mandate training. Understand what AI is, how it works, and how it’s being applied in your industry and specific role. Don’t wait for your company to mandate training. Understand what AI is, how it works, and how it’s being applied in your industry and specific role. Become AI-Augmented, Not AI-Replaced: Focus on developing skills that complement AI, such as AI supervision, ethical AI considerations, data interpretation, critical thinking, creativity, and complex problem-solving that still requires human intuition. Focus on developing skills that complement AI, such as AI supervision, ethical AI considerations, data interpretation, critical thinking, creativity, and complex problem-solving that still requires human intuition. Continuous Upskilling: The “job for life” is dead. Lifelong learning, particularly in emerging technologies, is the new norm. The “job for life” is dead. Lifelong learning, particularly in emerging technologies, is the new norm. Network and Diversify Skills: Don’t put all your eggs in one professional basket. Explore adjacent fields and build a network that extends beyond your current company. The corporate strategies of demanding office returns or implementing new performance metrics, when viewed in the context of an accelerating AI revolution and investor imperatives, reveal a clear trajectory towards a significantly leaner, more AI-driven workforce. The “hot water” is indeed boiling, and awareness, coupled with proactive adaptation, is the only viable survival strategy for the human element in this new economic paradigm. Since 2005, E-SPIN Group has empowered businesses across the region with comprehensive enterprise ICT solutions, including consulting, supply, project management, training, and maintenance. Let’s connect to discover how we can mutually create value and innovate together.	2025-07-01T00:00:00	2025/07/01	https://www.e-spincorp.com/ai-workforce-transformation-salesforce/	[ { "date": "2025/07/01", "position": 94, "query": "AI workforce transformation" } ]
AI in EdTech: Advantages and Methods of Application	AI in EdTech: Innovations Reshaping Modern Education	https://litslink.com	[ "Viacheslav Petrenko", "Anastasia Kovalevskaya", "Iryna Deremuk", "Anton Trubnikov" ]	A thorough analysis of the benefits of AI in education to improve the learning process for both learners and teachers. Explore how AI can change your ...	Only a decade ago, it would have been hard to believe that machine learning and artificial intelligence would become commonplace in society. Voice assistants like Amazon Echo or Siri have introduced these technologies into our daily lives. AI is mainly used in education through tools that help improve skills and learning. As AI solutions for education evolve, the hope is that AI will help bridge gaps in learning and teaching and improve employment in education by simplifying business management for schools and giving teachers the time and freedom to understand and harness human capabilities that machines cannot. In this article, you will learn about the role and future of AI in education. How AI Is Already Integrated Into Education In the modern world, almost everybody is familiar with assistants and programs for adaptive learning. Artificial intelligence has made it possible for such applications to simplify technical tasks and personalize the learning process. The vision of EdTech AI is to harness the best behavior of both machines and teachers, allowing them to work together to achieve the best outcomes for students. Schools, universities, and other training centers need to start seamlessly implementing AI software in EdTech and make students aware of the technology to use it properly. The Role of Artificial Intelligence in Learning EdTech AI is a broad concept. It covers any technology replicating human thinking and skills such as understanding complex information, drawing conclusions independently, and engaging in meaningful and coherent dialogue. Artificial intelligence can perceive much more information than a human. This means completing tasks much faster and more accurately. Further, artificial intelligence can be used to facilitate a personalized approach and provide the curriculum that the student needs at the moment. Some educational software developers have begun to take advantage of the knowledge-based AI with EdTech features to create programs tailored to each student’s needs. Positive Impact or Empowerment of Education There are numerous benefits of AI in education. For example, AI can automatically review student assignments and grade them and help teachers keep records of learning progress, relieving teachers of these tasks so they will be able to work more efficiently and save time. Data analysis can help teachers improve curriculum and materials to meet student’s needs better and achieve the best outcomes. Artificial intelligence can also help students learn. The ongoing advancements in AI are significantly impacting school management system development, enabling the creation of personalized learning programs that take into account the needs and abilities of each student. Such programs can help students acquire knowledge more efficiently and at their own pace. In addition, AI can provide students with access to more diverse and relevant sources of information, allowing them to receive complete and useful information for their learning. The Benefits of Artificial Intelligence in Education In today’s world of education, AI digital platforms for EdTech can bring many benefits to teachers and students. Read more about all the strengths below. Personalized Learning AI can easily understand what students really want. The system responds to students based on their performance and behavior. They can then focus on specific topics and learning characteristics that students are not yet familiar with and improve their ability to use the information presented. High Availability Artificial Intelligence in EdTech helps create and develop tools that facilitate learning across multiple learning spaces. Accessibility is a must, especially for those with disabilities. Such students often struggle in academic environments when resources are limited. For example, voice communication does work for students who are deaf or hard of hearing. Improve Interaction EdTech AI startup can support the digitization of content and help students capture and retain learning materials. Digitizing documents, including manuscripts, makes information easier to retrieve and use. Automation to Optimize Processes Automation can streamline many processes. One such method is recording and transcribing video lectures, where students have access to text lectures that will later be used as teaching material. Reduce Threats The most important thing in learning is trial and error. However, misunderstanding or not knowing the answers to various questions may discourage students. AI allows students to react and experiment in an unbiased environment. AI teachers can also respond to students’ mistakes by offering solutions for improvement. AI Tools in Education The education sector is at the forefront of AI, where technology is not only implemented but often faces frequent updates to make it even better for all involved. It is now a multi-billion dollar global market. Year Educational Software Market Value (in billions USD) Annual Growth (in millions USD) Government Spending (in billions USD) AI Adoption CAGR (%) 2021 $10.85 $200 $26 – $41 47 2025 $11.6 $200 $26 – $41 47 Additionally, AI can create immersive virtual learning environments that will look like personalized plans for each student and much more. Many innovative AI EdTech companies are developing such tools to achieve these results. Gradescope A popular AI in the education sector is Gradescope: it gives students even more options and allows them to evaluate each other and provide feedback. This greatly simplifies assessment and also saves time and energy. Main features of Gradescope: AI-powered assessment and verification; Grouping questions using artificial intelligence and manually; Improving efficiency and fairness; Extending time for students. Now, thanks to such a convenient programming tool, teachers can focus on more important areas. Teachers most often use Gradescope to grade paper exams, as well as to check homework online, which has become especially relevant during the period of remote learning. Fetchy This is a unique generative AI EdTech startup platform. The application was specifically developed for teachers to help them fully realize their teaching potential. With the help of AI, many tasks can be optimized, including creating engaging lessons, newsletters, and professional emails. Using a range of capabilities, Fetchy allows educators to improve their teaching methods. Program features: Create lesson plans; View history from multiple viewpoints; Use math or science experiments. Fetchy has several specializations. The application works based on generated language according to the requirements of teachers. Taken together, all this makes the program very useful. As a result, teachers can receive a set of universal solutions and get the desired results in a modern educational program. Ivy Chatbot This is a range of tools combined with chatbots and EdTech artificial intelligence. The program was specifically designed for universities and colleges. Using this program, universities can control not only academic performance but also the recruitment and application processes based on collected data and the cost of training. Key features of Ivy: Ability to integrate with Facebook, ERP, CRM, and SIS; Live chat with tips; The bot can develop and adapt as it interacts with users. Thanks to this tool, EdTech and AI can provide applicants and students with important information that interests them, including information about student loans, scholarships, grants, and tuition fees. Such an AI tool can be used in different departments due to the ability to develop specialized chatbots for each of them. Key Issues of AI in Education Despite its significant potential, artificial intelligence has its limitations. It works best when there is a vast virtual depository of examples from which it can generate information. Yet, in a high-risk industry like education, where professors cannot afford to make significant mistakes, it can be challenging to get many examples of what not to do. Artificial intelligence must also use only the right data to reach the right conclusions. If inaccurate information suddenly gets into the total volume of data, the results will come out false. In fact, there is no such thing as unbiased information. Some algorithms can make it even more subjective. Technology also raises concerns regarding the protection of personal data. It is worth caring not only about the quality and accuracy of information but also its responsible use. Developers of AI in EdTech should consider measures to ensure that students’ personal information is protected. And remember: if the most the program can do is advise you to re-read the seventh section of the textbook, it will not help you in your learning. But if the software development immediately generates new content based on how students interact with the program, then this is the path to revolutionary change. Conclusion Advances in AI in education have enormous potential to transform learning by empowering students and saving teachers time so they can focus on what’s important. AI EdTech startups can help improve student performance by providing real-time assessments and help professors by enhancing their teaching strategies to improve student learning. However, many schools are struggling to incorporate AI into their teaching methods adequately. Indeed, this problem includes ethical concerns and the high cost of AI tools, which prevent many schools and universities from using AI technologies. Therefore, AI tools have become the first choice for E-learning students who want to improve their education.	2023-10-18T00:00:00	2023/10/18	https://litslink.com/blog/ai-in-edtech	[ { "date": "2025/07/01", "position": 59, "query": "AI education" } ]
AI Skills - Training and Resources	AI Skills - Training and Resources	https://www.microsoft.com	[]	Learn about AI and access resources and training on in demand artificial intelligence and machine learning skills for jobs and organizations.	AI skills for everyone Discover the right learning path for every organization, every role, and every learner. Unlock the opportunity of AI in your work now and get ready for in-demand jobs in the future.	2025-07-01T00:00:00		https://www.microsoft.com/en-us/corporate-responsibility/ai-skills-resources	[ { "date": "2025/07/01", "position": 98, "query": "AI education" } ]
AI for Business - SymphonyAI - AI Applications	AI for Business	https://www.symphonyai.com	[]	Explore AI applications for your business. SymphonyAI combines predictive, generative, and agentic AI for powerful, ready-to-deploy business applications.	SymphonyAI is made for the messy reality of modern compliance where the cost of missed risk isn’t just fines, it’s trust and reputation. Our AI flags real risk, not noise. It slashes alert volumes while capturing new hidden risk and shows your team exactly why each decision was made, so you’re ready when regulators ask. No black boxes. No hiding behind complexity. Just transparency, control, and speed at the scale your institution demands.	2025-07-01T00:00:00		https://www.symphonyai.com/	[ { "date": "2025/07/01", "position": 30, "query": "AI employers" } ]
Worldwide: AI companies major economies 2023	Worldwide: AI companies major economies 2023	https://www.statista.com	[ "Bergur Thormundsson", "Jul" ]	The United States had by far the greatest amount of AI companies in major western economies in 2023, with around ****** companies engaging in the field.	Expert resources to inform and inspire. See why Statista is the trusted choice for reliable data and insights. We provide one platform to simplify research and support your strategic decisions. Learn more Statista R identifies and awards industry leaders, top providers, and exceptional brands through exclusive rankings and top lists in collaboration with renowned media brands worldwide. For more details, visit our website. Transforming data into content marketing and design: Strategy and business building for the data-driven economy Statista+ offers additional, data-driven services, tailored to your specific needs. 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Free Statistics Based on your interests Starter Account For single users $199 USD per month, billed annually 1 Buy now Free Statistics Premium Statistics The statistic on this page is a Premium Statistic and is included in this account. Professional Account For teams of up to 5 people $1,299 USD per month, billed annually 1 Buy now Free + Premium Statistics Reports Market Insights Compare accounts Learn more about how Statista can support your business. Request webinar Global AI Ecosystem. (September 15, 2023). Number of artificial intelligence (AI) companies in major economies worldwide in 2023 [Graph]. In Statista . Retrieved July 15, 2025, from https://www.statista.com/statistics/1413456/major-economies-ai-companies-worldwide/ Global AI Ecosystem. "Number of artificial intelligence (AI) companies in major economies worldwide in 2023." Chart. September 15, 2023. Statista. Accessed July 15, 2025. https://www.statista.com/statistics/1413456/major-economies-ai-companies-worldwide/ Global AI Ecosystem. (2023). Number of artificial intelligence (AI) companies in major economies worldwide in 2023 . Statista . Statista Inc.. Accessed: July 15, 2025. https://www.statista.com/statistics/1413456/major-economies-ai-companies-worldwide/ Global AI Ecosystem. "Number of Artificial Intelligence (Ai) Companies in Major Economies Worldwide in 2023." Statista , Statista Inc., 15 Sep 2023, https://www.statista.com/statistics/1413456/major-economies-ai-companies-worldwide/ Global AI Ecosystem, Number of artificial intelligence (AI) companies in major economies worldwide in 2023 Statista, https://www.statista.com/statistics/1413456/major-economies-ai-companies-worldwide/ (last visited July 15, 2025) Number of artificial intelligence (AI) companies in major economies worldwide in 2023 [Graph], Global AI Ecosystem, September 15, 2023. [Online]. Available: https://www.statista.com/statistics/1413456/major-economies-ai-companies-worldwide/	2025-07-01T00:00:00		https://www.statista.com/statistics/1413456/major-economies-ai-companies-worldwide/	[ { "date": "2025/07/01", "position": 45, "query": "AI employers" } ]
Non-tech employers seek workers with AI skills. Colleges ...	Employers say AI skills aren’t just for tech majors anymore. How colleges are responding	https://www.latimes.com	[]	As generative AI technology is rapidly changing the labor market, employers are increasingly seeking AI skills for positions outside the technology sector.	Miami Dade College launched its artificial intelligence program shortly after ChatGPT came out. The center gives students the option to take classes to strengthen their AI skills or complete a degree. By the time Christian Vivas enrolled in a new artificial intelligence program at Miami Dade College, he had already experimented with using ChatGPT to help him write emails to clients of the creative media studio he owns. Vivas, 37, said most of his classmates were like him — adults well into their careers looking to learn how to use AI, or use it better. Thanks to his classes, Vivas, who has a bachelor’s degree in electrical engineering, has advanced way beyond using ChatGPT. He now employs AI in nearly every aspect of his work: generating images, videos, marketing plans and social media captions. For the record: An earlier version of this story incorrectly said Stephanie Chavez wrote this story. The correct byline is Ariel Gilreath of the Hechinger Report. “It’s integrated very deeply into our business now,” Vivas said. Christian Vivas completed Miami Dade College’s artificial intelligence certification program to gain skills for the creative media studio he owns in south Florida. (Courtesy of Miami Dade College) As generative AI technology is rapidly changing the labor market, employers are increasingly seeking AI skills for positions outside the technology sector, such as in healthcare, hospitality and media. To keep up, students are looking for ways to boost their AI skills and make themselves more marketable amid growing concerns that AI will replace humans in the workforce. There’s evidence to suggest artificial intelligence may have already replaced some jobs. Entry-level positions are particularly at risk of being replaced by AI, a report from Oxford Economics shows. A global survey of more than 1,000 large businesses showed 41% expect to reduce their workforces within five years because of AI. But most companies — 77% — also plan to train their employees to “better work alongside AI,” according to the World Economic Forum’s Future of Jobs report in January. Last year, the number of online job postings that included generative AI as a desired skill grew 323%, to more than 66,000 from fewer than 16,000, according to a report from the labor analytics company Lightcast. Advertisement Colleges are also motivated by these trends: They’re adding AI to their course catalogs, and individual professors are altering lessons to include AI skill building. Colleges are rushing to add artificial intelligence lessons to their curricula as more employers list AI skills in their job postings. (Liliana Mora) Miami Dade College, for example, debuted its artificial intelligence certificate program in 2023, just over a month after ChatGPT was unveiled. The program offers classes in machine learning, ethics and natural language programming, among other courses. Since rolling out the certificate program, the school has added associate and bachelor’s degree programs in applied AI. Advertisement “We started developing this idea around the application of AI — how you can apply AI, how can you learn AI at a community college — where it is open to everyone, not just to a few who can get a master’s or PhD,” said Antonio Delgado, vice president of innovation and technology partnerships at Miami Dade College. In 2022, the college also created Miami Tech Works, an organization that helps tech companies find skilled workers. Recently, more businesses outside tech have reached out to hire people who know how to use AI. Miami Dade College’s programs have attracted students such as Vicky Cheung, who decided to enroll in the college’s artificial intelligence awareness certificate program in 2024, after she was let go from the Miami hospital where she had worked for more than two decades. Advertisement Cheung, who already had a bachelor’s in business and a master’s in health management, was looking into resume-building courses. She believes her AI courses, coupled with her work experience, helped her land her new job analyzing how to improve processes and workflow at a different hospital. Enrolling in the program showed employers “that I’m trying to find a way to improve my skill sets,” she said. Schools across the country have announced programs similar to the one at Miami Dade College: courses in artificial intelligence in business settings and minors in AI marketed to students who are not computer science majors. But higher education institutions are not inherently nimble — and the technology is evolving quickly. Because generative AI is changing so rapidly, there’s no one curriculum or credential schools are using, or can look to, as a guidepost. What these lessons look like and the rules about how students should use AI vary by institution, or even classroom to classroom. “The problem we have is that AI is changing industries so fast that the textbooks, the curriculum — by the time you get it approved, it’s relevant, but it’s outdated,” said Josh Jones, chief executive of QuantHub, a company that works with schools including the University of Alabama and Emory University to add AI lessons. There are downsides for using generative AI as well — students can use the technology to cheat on assignments and some studies indicate college students who use AI on assignments are less engaged with their lessons and use it to avoid critical thinking. Advertisement Higher education institutions acknowledge the risks, but also the need to prepare for students for the working world. For Derrick Anderson, who teaches public affairs at Arizona State University and is senior vice president at the American Council on Education, it’s simple: If AI is a tool students will use at jobs, they should learn how to use it in his classroom. “Because I’m preparing them for the job market, they need to know how to use generative AI ethically, but efficiently and effectively,” Anderson said. Now, instead of having students write an essay at the end of one of his public affairs courses, Anderson has them produce a video with the help of ChatGPT. One student in Anderson’s class created a video about new technology that mimics the human brain. In the video, the student narrates as an AI-generated image of a model brain spins on the screen. Previously, one of Anderson’s class assignments required students to write a memo; now, they have to write four different kinds of memos using ChatGPT and describe scenarios where they would be appropriate. “It’s a fundamentally different exercise that involves a much larger volume of content because content is so much easier to create,” Anderson said. Advertisement The students in his classes have used their AI videos and projects in their portfolios when looking for jobs to show they have experience with these programs, even if they lack a specific degree or credential. Employers are looking for those kinds of demonstrable examples of AI skills from graduates, said Ken Finneran, vice president of human resources at the digital healthcare company eMed. Every department at eMed, from marketing to human resources to finance, uses generative artificial intelligence tools in some way, said Finneran, and the company expects prospective employees to have foundational knowledge of AI.	2025-07-01T00:00:00	2025/07/01	https://www.latimes.com/california/story/2025-07-01/ai-college-courses-for-job-seekers	[ { "date": "2025/07/01", "position": 48, "query": "AI employers" } ]
Top Skills for the AI Era: What Tech Executives Say You ...	Top Skills for the AI Era: What Tech Executives Say You Should Learn	https://www.businessinsider.com	[ "Ana Altchek" ]	Business Insider asked eight tech executives about the top skills job seekers — and all employees — should have in the age of AI. Here are three tips they ...	Generalists may become especially in demand in the modern workplace. Generalists may become especially in demand in the modern workplace. Weedezign/Getty Images Generalists may become especially in demand in the modern workplace. Weedezign/Getty Images This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now. Whether you're just entering the workforce or decades into your career, chances are your job is evolving — or will be soon. A recent Salesforce study suggested that with agentic AI adoption expected to grow 327% by 2027, chief human resource officers expect to re-deploy 23% of their workforce in the next two years. While 61% of the workforce is expected to stay in their roles, those jobs are also expected to change, the report said. Some tech CEOs still believe that foundational knowledge in areas like coding remains important. However, other skills are rising in importance and reshaping what it takes to thrive in the workplace. In January's World Economic Forum's Future of Jobs Report, 86% of employers said they believe that technological advancements will transform their businesses over the next five years. This shift is projected to result in a decline in some roles and growth in others, while also increasing demand for skills in AI and big data, cybersecurity, and technological literacy. Business Insider asked eight tech executives about the top skills job seekers — and all employees — should have in the age of AI. Here are three tips they shared: Be a generalist The age of the Renaissance person may be returning. Cognizant CEO Ravi Kumar told Business Insider in an interview that the world is shifting toward an era where "deep expertise will be less valued." He said those who merge specific knowledge in one domain with technological capabilities will be more relevant than those with narrow expertise in one area. Related stories Business Insider tells the innovative stories you want to know Business Insider tells the innovative stories you want to know Kumar said that a history major who can leverage AI tools to apply historical insights to future scenarios, for instance, will be a stronger historian in today's market than someone who can solely speak to a historical period. Similarly, Cloudflare CEO Matthew Prince told BI that as cybersecurity is increasingly embedded into other platforms, the company is focused on recruiting talent with a diverse skillset. "We're trying to find people who have a broad set of skills and can be general," Prince told BI. Other cybersecurity executives have also previously told BI that while foundational skills in data and IT are important, soft skills and adaptability are key to the job. Focus on fresh ideas When many executives talk about AI tools, they emphasize the expectation that employees will have more time for "deep work." Dropbox VP of product and growth Morgan Brown defines this as uninterrupted time dedicated to "expansive thinking" about new ideas. "The quality of ideas that we're going to be able to get people to think about because they will have time — rather than just tactically going out and fixing bugs — might actually enhance not just the output capacity, but also the satisfaction that someone gets from a job," Cisco executive Jeetu Patel said in a recent conversation about shifts in engineering. Brown added that with AI efficiency gains, product rollouts are moving at a much faster pace, which allows employees to turn ideas into reality more quickly, Brown said. Cisco executive vice president and chief customer experience officer Liz Centoni echoed the sentiment in a March interview with BI. She said that being able to think creatively is vital. "I want someone in there who's sitting with the subject matter experts who can not just understand the problem, but look at how can we creatively craft a solution," Centoni said. Get good at using AI tools Most people know how to ask ChatGPT for answers to basic questions, but prompt engineering is a more complex skill. Google Cloud executive Yasmeen Ahmad told BI that people need to know the kind of questions to ask, what kind of data is available, and how to craft their queries effectively. Successful workers will be able to "interact with these new-age tools and be able to prompt to engineer and ask the right questions and interact in this flow that hasn't been there before," Ahmad said. Google Cloud CTO Will Grannis told BI that to stay current, employees need to look "beyond the formal curriculum." That means following your curiosity and using available AI tools to "vibe code," or use AI to generate code. While prompt engineering is important, he said job seekers need to be skilled in context engineering as well, which means knowing the larger systems at play. AI literacy also requires effectively interacting with agents, said Salesforce talent executive Lori Castillo Martinez in a recent interview with Business Insider. The executive told BI that employees need to know when to use agents and how to communicate with them. Patel also told BI that orchestrating agent workflows is a crucial skill that will be "super important." That includes assigning work to agents and overseeing their progress.	2025-07-01T00:00:00		https://www.businessinsider.com/top-skills-learn-ai-era-tech-executives-2025-7	[ { "date": "2025/07/01", "position": 51, "query": "AI employers" } ]
AI companies start winning the copyright fight \| Technology	AI companies start winning the copyright fight	https://www.theguardian.com	[ "Blake Montgomery" ]	Tech firms notch victories in battle over copyrighted text, Trump's gold phone, and online age checks.	Hello, and welcome to TechScape. If you need me after this newsletter publishes, I will be busy poring over photos from Jeff Bezos and Lauren Sanchez’s wedding, the gaudiest and most star-studded affair to disrupt technology news this year. I found it a tacky and spectacular affair. Everyone who was anyone was there, except for Charlize Theron, who, unprompted, said on Monday: “I think we might be the only people who did not get an invite to the Bezos wedding. But that’s OK, because they suck and we’re cool.” AI companies start winning the copyright fight Last week, tech companies notched several victories in the fight over their use of copyrighted text to create artificial intelligence products. Anthropic: A US judge has ruled that Anthropic, maker of the Claude chatbot, use of books to train its artificial intelligence system – without permission of the authors – did not breach copyright law. Judge William Alsup compared the Anthropic model’s use of books to a “reader aspiring to be a writer.” And the next day, Meta: The US district judge Vince Chhabria, in San Francisco, said in his decision on the Meta case that the authors had not presented enough evidence that the technology company’s AI would cause “market dilution” by flooding the market with work similar to theirs. The same day that Meta received its favorable ruling, a group of writers sued Microsoft, alleging copyright infringement in the creation of that company’s Megatron text generator. Judging by the rulings in favor of Meta and Anthropic, the authors are facing an uphill battle. These three cases are skirmishes in the wider legal war over copyrighted media, which rages on. Three weeks ago, Disney and NBCUniversal sued Midjourney, alleging that the company’s namesake AI image generator and forthcoming video generator made illegal use of the studios’ iconic characters like Darth Vader and the Simpson family. The world’s biggest record labels – Sony, Universal and Warner – have sued two companies that make AI-powered music generators, Suno and Udio. On the textual front, the New York Times’ suit against OpenAI and Microsoft is ongoing. The lawsuits over AI-generated text were filed first, and, as their rulings emerge, the next question in the copyright fight is whether decisions about one type of media will apply to the next. “The specific media involved in the lawsuit – written works versus images versus videos versus audio – will certainly change the fair-use analysis in each case,” said John Strand, a trademark and copyright attorney with the law firm Wolf Greenfield. “The impact on the market for the copyrighted works is becoming a key factor in the fair-use analysis, and the market for books is different than that for movies.” To Strand, the cases over images seem more favorable to copyright holders, as the AI models are allegedly producing images identical to the copyrighted ones in the training data. A bizarre and damning fact was revealed in the Anthropic ruling, too: the company had pirated and stored some 7m books to create a training database for its AI. To remediate its wrongdoing, the company bought physical copies and scanned them, digitizing the text. Now the owner of 7m physical books that no longer held any utility for it, Anthropic destroyed them. The company bought the books, diced them up, scanned the text and threw them away, Ars Technica reports. There are less destructive ways to digitize books, but they are slower. The AI industry is here to move fast and break things. Anthropic laying waste to millions of books presents a crude literalization of the ravenous consumption of content necessary for AI companies to create their products. AI and the environment: bad news Two stories I wrote about last week saw significant updates in the ensuing days. The website for Trump’s gold phone, dubbed “T1”, has dropped its “Made in America” pledge in favor of “proudly American” and “brought to life in America”, per the Verge. Trump seems to have followed the example of Apple, which skirts the issue of origin but still emphasizes the American-ness of iPhones by engraving them with “Designed in California”. What is unsaid: assembled in China or India, and sourced from many other countries. It seems Trump and his family have opted for a similar evasive tagline, though it’s been thrown into much starker relief by their original promise. The third descriptor that now appears on Trump’s phone site, “American-Proud Design”, seems most obviously cued by Apple. The tagline “Made in the USA” carries legal weight. Companies have faced lawsuits over just how many of their products’ parts were produced in the US, and the US’s main trade regulator has established standards by which to judge the actions behind the slogan. It would be extremely difficult for a smartphone’s manufacturing history to measure up to those benchmarks, by the vast majority of expert estimations. Though Trump intends to repatriate manufacturing in the US with his sweeping tariffs, he seems to be learning just what other phone companies already know. It is complicated and limiting to make a phone solely in the US, and doing so forces severe constraints on the final product. Read last week’s newsletter about the gold Trump phone. … and online age checks View image in fullscreen Photograph: Matt Cardy/Getty Images Last week, I wrote about Pornhub’s smutty return to France after a law requiring online age verification was suspended there. This week, the US supreme court ruled in favor of an age-check law passed in Texas. Pornhub has blocked access to anyone in Texas in protest for the better part of two years, as it did in France for three weeks. Clarence Thomas summed up the court’s reasoning: “HB 1181 simply requires adults to verify their age before they can access speech that is obscene to children,” Clarence Thomas wrote in the court’s 6-3 majority opinion. “The statute advances the state’s important interest in shielding children from sexually explicit content. And, it is appropriately tailored because it permits users to verify their ages through the established methods of providing government-issued identification and sharing transactional data.” Elena Kagan dissented alongside the court’s two other liberal justices. The ruling affirms not only Texas’s law but the statutes of nearly two dozen states that have implemented online age checks. The tide worldwide seems to be shifting away from allowing freer access to pornography as part of a person’s right to free expression and more towards curtailing. Experts believe the malleable definition of obscenity – the Texas law requires an age check for any site whose content is more than a third sexual material – will be weaponized against online information on sexual health, abortion or LGBTQ+ identity, all in the name of child protection. “It’s an unfortunate day for the supporters of an open internet,” said GS Hans, professor at Cornell Law School. “The court has made a radical shift in free speech jurisprudence in this case, though it doesn’t characterize its decision that way. By upholding the limits on minors’ access to obscenity – a notoriously difficult category to define – that also creates limits on adult access, we can expect to see states take a heavier hand in regulating content.” I’ll be closely watching what happens in July when Pornhub willingly implements age checks in compliance with the Online Services Act. Read more: UK study shows 8% of children aged eight to 14 have viewed online pornography Read more AI news This week in AI: new WhatsApp summaries and Nobel winners’ genomic model View image in fullscreen Meta’s WhatsApp will begin showing you AI-generated summaries of your unread messages. Photograph: Martin Meissner/AP New features are a dime a dozen, but even a small tweak to the most popular messaging app in the world may amount to a major shift. Meta’s WhatsApp will begin showing you AI-generated summaries of your unread messages, per the Verge. Apple tried message summaries. They did not work. The company pulled them. For a firm famed for its calculated and controlled releases, the retraction of the summaries was a humiliation. The difference between Apple and Meta, though, is that Meta has consistently released AI products for multiple years now. In other AI news, I am rarely captivated by new technologies, but a recent release by Google’s DeepMind AI laboratory seems promising for healthcare. AlphaGenome is an AI meant to “comprehensively and accurately [predict] how single variants or mutations in human DNA sequences impact a wide range of biological processes regulating genes”, per a press release. The creators of AlphaGenome previously won the Nobel prize in chemistry for AlphaFold, a software that predicts the structures of proteins. A major question that hovers over Crispr, another Nobel-winning innovation, is what changes in a person when a genetic sequence is modified. AlphaGenome seems poised to assist in solving that mystery. The wider TechScape	2025-06-30T00:00:00	2025/06/30	https://www.theguardian.com/technology/2025/jun/30/ai-techscape-copyright	[ { "date": "2025/07/01", "position": 59, "query": "AI employers" } ]
AI, community building and the future of journalism	AI, community building and the future of journalism	https://wtop.com	[ "News Traffic Weather" ]	Hanna Rifaey, head of strategic partnerships at the Online News Organization, and Meghan Murphy, ONA's director of programs, talk about the state of ...	Hanna Rifaey, head of strategic partnerships at the Online News Organization, and Meghan Murphy, ONA’s director of programs, talk about the… Listen now to WTOP News Hanna Rifaey, head of strategic partnerships at the Online News Organization, and Meghan Murphy, ONA’s director of programs, talk about the state of digital news, sustainability and ONA’s AI in Journalism Initiative. Visit the It’s All Journalism website to find more episodes like this one. Learn more about your ad choices. Visit podcastchoices.com/adchoices See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info. Listen to more from the show: It's All Journalism	2025-04-24T00:00:00	2025/04/24	https://wtop.com/podcast/its-all-journalism/ai-community-building-and-the-future-of-journalism-2/	[ { "date": "2025/07/01", "position": 71, "query": "AI journalism" } ]
Google's AI Overviews accused of 'obscuring' journalism ...	Google’s AI Overviews accused of ‘obscuring’ journalism, harvesting data	https://www.mlex.com	[]	Publishers accused Google of sidelining quality journalism and undermining copyright protections in the rollout of its new AI Overviews, which present rich ...	By Lewis Crofts ( July 1, 2025, 14:37 GMT \| Insight) -- Publishers accused Google of sidelining quality journalism and undermining copyright protections in the rollout of its new AI Overviews, which present rich answers at the top of a search page. Google told a hearing hosted by the European Commission that it had a long history of enriching its services through AI features and the latest innovation was bringing significant benefits to users. It stressed it obtains consent for data usage and the market for AI tools was highly competitive.Publishers accused Google of sidelining quality journalism and undermining copyright protections in the rollout of its new AI Overviews, which present rich answers at the top of a search page.... Prepare for tomorrow’s regulatory change, today MLex identifies risk to business wherever it emerges, with specialist reporters across the globe providing exclusive news and deep-dive analysis on the proposals, probes, enforcement actions and rulings that matter to your organization and clients, now and in the longer term. Know what others in the room don’t, with features including: Daily newsletters for Antitrust, M&A, Trade, Data Privacy & Security, Technology, AI and more Custom alerts on specific filters including geographies, industries, topics and companies to suit your practice needs Predictive analysis from expert journalists across North America, the UK and Europe, Latin America and Asia-Pacific Curated case files bringing together news, analysis and source documents in a single timeline Experience MLex today with a 14-day free trial.	2025-07-01T00:00:00		https://www.mlex.com/mlex/antitrust/articles/2359807/google-s-ai-overviews-accused-of-obscuring-journalism-harvesting-data	[ { "date": "2025/07/01", "position": 76, "query": "AI journalism" } ]
IBM used AI to fire 8000 people. What happened next will ...	IBM used AI to fire 8,000 people. What happened next will surprise you!	https://content.techgig.com	[]	That move saved billions and sparked a hiring wave in roles AI couldn't handle. What looked like mass layoffs turned into something very unexpected. Let's dig ...	From pink slips to promotions: IBM’s surprising next move AI didn’t kill jobs at IBM—it created better jobs instead AI boosts service, but human skills still seal the deal Why this shift matters for the global tech workforce The bottom line: This whole circumstance is unique and could surprise you. You need to understand everything right from the beginning to grasp it. However, IBM's new strategy has changed the entire tech hiring scene. IBM used AI to wipe out thousands of HR jobs.But instead of shrinking, the company started hiring again. AskHR, its AI tool, took over routine tasks like payroll and leave tracking. That move saved billions and sparked a hiring wave in roles AI couldn't handle. What looked like mass layoffs turned into something very unexpected.Let’s dig deeper into this whole sequence of events to understand it completely:IBM didn’t just cut costs; it reshaped its workforce, which could be an inspiring move in the future. Instead of just decreasing their workforce, the company used its AI savings to hire smarter.Which resellted opportunities in engineering, sales, and marketing grew fast. Freed-up budgets were redirected into jobs that require human creativity, strategy, and decision-making. It meant IBM leaders weren’t just cutting but rebuilding with purpose.Automation cleared out the repetitive work but didn’t erase careers. Instead, it created room for human skills to shine. Creativity, problem-solving, and relationship-building became essential again.Tech giants noticed the trend. Companies now blend AI efficiency with roles only humans can master. The result? Smarter workflows and stronger teams. The whole hiring process seems so revolutionary in many ways, and IBM could be the trend setter with this brilliant move.IBM's AskHR handled over 11.5 million queries 2024, pushing satisfaction scores from 35 to +74. But even with that leap, 6% of cases still needed a human touch. That gap reveals the real story: AI excels at scale and speed, but empathy, judgment, and trust still come from people.The smartest companies now blend both. They use automation to handle the heavy lifting, then reinvest in creative, problem-solving roles where human expertise leads. It's not about replacing teams; it's about elevating them.Automation isn’t killing jobs; it’s changing them. Across the world, from Bangalore to Berlin, tech teams are seeing demand rise for skills AI can’t replicate. Roles that blend creativity, product thinking, and human insight are gaining value.Startups, developers, and innovators now have a chance to lead by building tools, solving problems, and focusing on what machines can’t do. The message is clear: upskill, adapt, and step into the future of work.IBM's story isn't about cutting jobs or removing people from its workforce. It's about changing how work gets done. Automation handled the routine, but people powered the progress. Every tech leader should aim for that balance between speed and skill, machine and human, code and creativity.Globally, this shift reshapes how companies build, hire, and grow. So, whether you're a developer, manager, or founder, one truth stands out: The winners won't be those who fear AI but those who learn to lead with it.	2025-07-01T00:00:00		https://content.techgig.com/technology/ibm-ai-layoffs-hiring-shift-2025/articleshow/122177817.cms	[ { "date": "2025/07/01", "position": 62, "query": "AI layoffs" } ]
Microsoft Mandates AI Tools for Employee Success Amid ...	Microsoft Mandates AI Tools for Employee Success Amid Rising Competition	https://opentools.ai	[]	Microsoft's decision is part of a strategy to bolster internal adoption of AI and navigate the complex relationship with OpenAI, despite looming layoffs. Table ...	OpenAI stands at the forefront of AI innovation, and its evolving dynamics with Microsoft highlight the challenges companies face when managing partnerships amid sectoral transformations. Microsoft's internal mandate to leverage its AI capabilities comes as both a response to competition and a strategic measure to enhance productivity. However, as OpenAI charts its course towards potential acquisitions like Windsurf, Microsoft's investment in OpenAI transforms into a complex entanglement of interests. This acquisition not only enhances OpenAI's offerings but also sets the stage for a possible showdown in the AI tool market. These developments underscore the fluidity of tech alliances where partner capabilities could simultaneously be seen as an asset and a threat. As the tech giant navigates these waters, it must consider the long-term implications of OpenAI's autonomy and its pursuit of success in the AI realm.	2025-07-01T00:00:00		https://opentools.ai/news/microsoft-mandates-ai-tools-for-employee-success-amid-rising-competition	[ { "date": "2025/07/01", "position": 93, "query": "AI layoffs" } ]
Entry-level jobs down since ChatGPT launch, research ...	Entry-level jobs down since ChatGPT launch, research shows	https://www.hrmagazine.co.uk	[ "Claire Muir" ]	Entry-level jobs in the UK have dropped by almost a third (32%) since the launch of ChatGPT in November 2022, according to research by job search site Adzuna. ...	Entry-level jobs in the UK have dropped by almost a third (32%) since the launch of ChatGPT in November 2022, according to research by job search site Adzuna. We asked commentators how HR can redesign entry-level jobs and futureproof graduate recruitment. Graduate jobs, apprenticeships, internships and junior roles now account for 25% of the UK job market, down from 28.9% in 2022, Adzuna's research, published yesterday (30 June), highlighted. Global hiring platform Indeed’s Mid-Year Labour Market Update, released on 25 June, confirmed that graduates are facing the toughest job market since 2018: in absolute terms, there are 33% less graduate roles compared with the same period last year. However, it is “too early for AI to impact graduate job numbers”, according to Stephen Isherwood, joint CEO at early talent support network, the Institute of Student Employers. Instead, he told HR magazine, “a flat economy combined with rise in employers' national insurance contributions is having the biggest impact” on these vacancies. Jack Kennedy, senior economist at Indeed, agreed that the eight-year low “can't be attributed solely to the rise of AI” but stressed that employers should “think seriously about how these roles are designed". Read more: Exclusive: Eight in 10 business leaders use AI for mentorship Kennedy told HR magazine: “HR teams have a critical opportunity to reshape entry-level jobs; building in meaningful tasks, development opportunities and exposure to new technologies like GenAI.” Karie Willyerd, chief learning officer at virtual IT lab Skillable, warned HR magazine that “soon, every job description will assume AI capability not as a separate skill, but woven into the fabric of daily work”, making it crucial for HR to test for “the ability to work alongside AI". Willyerd continued: “Everyone is becoming a manager, not of people but of AI outputs” so entry-level workers now need skills in “critical thinking and feedback for their ‘AI direct reports’”. Similarly, Anastasia Pshegodskaya, director of talent acquisition at HR platform Remote, recommended offering “early-career roles that combine AI-enabled tasks with real-world problem solving” and highlighted to HR magazine that entry-level roles could now transform from “stepping stones” into “foundational development opportunities”. Read more: Fewer women plan to upskill in AI than men Looking at HR processes, EY Foundation CEO Lynne Peabody said they must avoid “embedding unintended biases that can hold back young people from more marginalised communities”. The charity chief recommended “involving young people at risk of being negatively impacted in the development and implementation of AI-based recruitment”. Raoul Gabriel-Urma, CEO of AI training business Cambridge Spark, discussed the impact on businesses’ talent pipelines with HR magazine: “Entry-level employees are the next generation of C-suite leaders. “And if their roles are increasingly being automated, HR leaders must ensure those still making the cut are the assets they need for today's AI-powered workplace.”	2025-07-01T00:00:00	2025/07/01	https://www.hrmagazine.co.uk/content/news/entry-level-jobs-down-since-chatgpt-launch-research-shows	[ { "date": "2025/07/01", "position": 22, "query": "ChatGPT employment impact" } ]
Job maker or job taker? How artificial intelligence is ...	Job maker or job taker? How artificial intelligence is defying the doomsayers	https://www.iese.edu	[ "Philippe Aghion" ]	When people speak about AI and employment, they often raise the specter of it aggravating inequality. It may be true that, because of AI, companies seek to hire ...	Here is what is needed to harness the full potential of artificial intelligence. Act now or get left behind. By Philippe Aghion Artificial intelligence (AI) is an unavoidable technological revolution. And like any revolution, its impact on the economy, employment, public services, the environment, information, culture and society will be immense, both now and even more so in the future. This fact alone should inspire neither excessive pessimism nor excessive optimism. Instead, it should inspire companies and governments to mobilize their collective resources to accelerate the adoption and deployment of AI in ways that serve individual and societal needs based on shared values and principles. This was the message of a report I co-authored with Anne Bouverot, board chair of École Normale Supérieure (ENS), for the French Government’s AI Commission. AI: Our Ambition for France made 25 key recommendations to ensure France — and Europe — step up investments in training, innovation, computing power, data access and R&D so as not to miss out on the opportunities of the AI revolution. This informed the AI Action Summit held in Paris in February 2025. Here, I summarize my own research perspective on AI and share some of the recommendations that demand our immediate attention if we are to stay in the game and help shape AI’s future direction. For the purposes of this article, I will focus my comments on employment, productivity and growth — areas where I am cautiously optimistic that AI has positive potential, but it requires appropriate policies for it to succeed. Should we fear AI? There exists in the popular imagination the fear that AI is going to replace all our jobs, amplified by a highly cited 2013 paper by Frey and Osborne that ominously predicted 47% of total U.S. employment was at risk of being replaced by computerization within the next 10-20 years. That has not happened. My own research challenges the view that AI robotization or automation is bad for employment. Instead, I argue that AI has considerable potential to generate employment and productivity. In a joint paper with Ben Jones and Chad Jones, we modeled AI’s ability to automate tasks. When you automate the production of goods and services, you replace labor with physical capital, i.e., more machines. But that’s only one side of it. AI doesn’t just facilitate the production of goods and services. We considered how it also facilitates the production of ideas through its ability to imitate, learn and become self-improving. This can lead to more labor productivity without any more physical capital, and a high number of human jobs can be automated without changing the labor share. This is in line with a famous economic insight from Baumol that, even in sectors like manufacturing or agriculture that have gotten highly automated over time, the labor share remains substantial because “growth is determined not by what we are good at but rather by what is essential and yet hard to improve.” So, even if automation keeps pushing ahead, our modeling shows a constant and positive labor share for essential tasks that remain hard to improve without continued human input. To this point, Erik Brynjolfsson and co-authors performed a micro analysis that illustrates the empowering effects of AI on labor. They looked at a U.S.-based Fortune 500 company that employed customer support agents in the Philippines. The company rolled out a generative AI tool with these agents to assist them with answering customer queries via chat windows. Of the 5,179 agents studied, some had access to the AI tool while others didn’t, so the authors could compare each group’s productivity. They found that the number of issues resolved per hour by agents using the AI tool went up by around 14%. Also, the customers helped by AI-assisted agents came away satisfied and were less likely to ask for the help of a supervisor compared with the agents not using AI. But here’s the other really interesting piece: Among the less experienced, lower skilled agents, they saw productivity gains of 35%. When people speak about AI and employment, they often raise the specter of it aggravating inequality. It may be true that, because of AI, companies seek to hire more high-skilled workers over low-skilled ones, and these hiring preferences might perpetuate inequality. Yet the Brynjolfsson study offers a riposte to that. There, the AI actually helped the newer hires and the lower performers get up to speed faster, and the less experienced workers ended up becoming even more productive than their experienced counterparts. This is the remarkable feature of generative AI: it mimics the actions of the best performers, so even those initially less productive can lift their performance to match or exceed the top employees. Scale effects: more automation creates more employment In other research with Celine Antonin (Sciences Po), Simon Bunel (Banque de France) and Xavier Jaravel (London School of Economics), we compared employment in two identical firms in France — one that automated and one that didn’t — and found the firm that automated created more employment. You might think that’s paradoxical, given that automation means replacing people with machines. However, you have to realize that firms that automate become more productive: they produce cheaper and/or better quality for the same cost, and as demand for that cheaper/better product goes up, they increase their market size, leading them to hire more employees. We see this dynamic consistently. When you automate sales, your sales go up, and that leads to more employment. This is why I am against the idea of taxing robots, because putting a tax burden on a firm for becoming more productive is essentially inhibiting employment. We’re now repeating our French study in Denmark, comparing firms that adopt AI with similar firms that don’t. Again, we’re finding a positive effect of AI on employment for exactly the same reasons. Admittedly, the employment effect is not uniform across all types of jobs and professions. For any job, it’s important to decompose the tasks and analyze which ones have a small, medium or high risk of replacement by AI. What’s interesting is that, so far, many managerial tasks seem to be at low risk of replacement, and those tasks that can be replaced are usually the more mundane ones, freeing up managers’ time for more creative, higher level tasks. For managers, this is good news. For others, like administrative assistants or legal secretaries, AI adoption may not create more employment, yet this is not to say those jobs will disappear entirely. Rather, certain tasks within those jobs will become redundant and you may have to rethink the job a bit. In the same way as more automation can increase employment because you have a higher demand for your product and therefore you employ more of it, we generally find most employment skills are benefiting because of these scale effects. This is an important distinction. AI may put certain tasks at risk but not generate mass unemployment, despite the fearmongering. It has been the same throughout history, going back to the 19th century Luddite movement involving English factory workers who resisted and sabotaged the machines they feared would put them all out of work. As with other technological disruptions, people’s fears are often worse than the reality. Economic productivity and growth Now let’s turn to talk about AI’s potential for economic productivity and growth. MIT economist Daron Acemoglu recently published a paper in which he estimated that the macroeconomic gains as a result of AI will be modest, with GDP increasing between 1.1% and 1.6% over the next 10 years and an annual gain in productivity of roughly 0.05%. He makes AI’s impact seem much less revolutionary than it is touted to be. However, Aidan Toner-Rodgers, also at MIT, contemplated other AI scenarios and found potentially much bigger gains. He studied the introduction of an AI tool in a U.S. R&D lab to partially automate the usual trial-and-error process that scientists go through for materials discovery. He found that AI-assisted researchers discovered 44% more materials, resulting in a 39% increase in patent filings, a 17% rise in downstream product innovation and a 13%-15% boost in R&D efficiency. Granted, this is a micro-level proof. The question is whether we can extrapolate such findings to make broader claims about AI’s benefits. We could, for example, compare the growth trajectories of other technological revolutions, like the electricity wave of the 1920s in Europe or the digital technology wave of the late 1990s and early 2000s in the United States. Simon Bunel, an economist at Banque de France, and I did exactly that in a recent paper. Using these two historical comparables, we calculated that productivity growth by AI would increase by anywhere from 0.8 percentage points per year (following the pattern of ITC) to 1.3 percentage points per year (following the pattern of electricity). Both trajectories are within the ballpark of Acemoglu’s “modest” gains — and I wouldn’t characterize the impact of those other tech revolutions as “modest.” We must assume a time lag between when the technology is introduced and when its true impact is felt in terms of reorganized work processes and radical, systemic change. Bearing in mind the earlier observation — that AI automates tasks not only in the production of goods and services but also in the production of ideas — I would argue it is still too early to quantify the real magnitude of AI’s impact on economic productivity and growth. Again, using a historical parallel, 17th century advances in glass polishing eventually led to powerful microscopes capable of detecting previously unknown germs and other microorganisms. Likewise, AI’s possibilities are as yet hard to say with any certainty — although Toner-Rodgers’ paper gives us a sense of what might be on the horizon in terms of idea generation, scientific discovery and rates of innovation as AI realizes its potential. What to do: 5 urgent action items for policymakers Based on all this research and more, our AI report to the French Government proposed a series of urgent action items. Beyond calling for substantially more public investment, we urged reforms in several strategic policy areas, including the following: 1. Restructure education to improve AI training One of the top action items was to restructure education to improve AI training. Education is a key driver of social mobility. Whenever you have a good education system, you mitigate the negative socioeconomic impacts because people are better equipped to adapt to change. Having said that, as important as it is to have more AI education in schools, we must be careful not to give students access to AI too early. In that sense, I am a traditionalist. People need to spend time writing and reading books, and not be on screens all the time. They need to learn mathematical demonstration. When I was a kid, I would work on Euclidean geometry, which helps you learn how to reason. With AI, it becomes even more important to be able to write correctly, to have good mathematical reasoning, calculus and logic. People need to develop critical thinking skills. 2. Labor policies that include reskilling, upskilling and flexicurity A good education system must go hand in hand with adequate labor market policies. Personally, I am fond of the Danish system, which has a strong social safety net, so if you lose your job, the state retrains you and helps you find a new job. Contrast that with the United States, where mortality rates for unskilled, middle-aged, white men have risen sharply owing to the phenomenon of “deaths of despair.” Studies have been done on the health consequences of an employee who loses his job in, say, Denmark versus an employee identical in experience, education and age in the U.S. Their outcomes are drastically different. And these are largely the result of policy choices, not because of AI. Yes, some jobs will have to be restructured and some tasks will disappear, but there will be new jobs with fantastic potential, thanks to AI. What matters is having the appropriate education and flexicurity systems in place to harness the potential. 3. Competition policies that do not put up entry barriers to new firms Antonin Bergeaud (HEC Paris), Timo Boppart (IIES Stockholm University), Peter Klenow (Stanford), Huiyu Li (Federal Reserve Bank of San Francisco) and I looked at total factor productivity (TFP) — total outputs relative to total inputs — in the U.S. between 1988 and 2019, a period coinciding with the IT revolution. From 1988 to 1995, we saw average growth of about 0.8% per year. But from 2006 to 2019, average growth was down to just 0.4% per year. What happened in between? From 1996 to 2005, annual growth surged to 2.1% per year. This can be accounted for by the emergence of superstar firms like Google and Amazon, which harnessed technology better than others and relentlessly expanded through mergers and acquisitions. At that time, competition policy was not adapted to the IT revolution, so these firms were able to expand without constraint. They became tentacular and ended up discouraging competition. The entry rate of new firms of all sizes declined from the year 2000 onward, while the average markup went up, not within all firms but only for the winning firms, resulting in hegemony for superstar firms. This occurred because there was no effective competition policy preventing it from happening. Which brings us to today: The upstream segment of the AI value chain is dominated by a few superstar firms. That is why we dedicate a major part of our AI report to policy reforms that would foster competition. This means stopping boundless acquisition, especially if it raises entry barriers to new firms and prevents innovation by new firms. Competition policy must be determined not only according to market-share definitions but by the effect a merger could have on subsequent innovation. 4. Data policies that protect without preventing innovation I believe in “open source” all the way. We also need to relax some of the regulations on data access. On top of the EU-wide General Data Protection Regulation (GDPR), France has added its own regulation regarding the use of health data. I’m not against regulation per se, but as things stand, our current level of regulation is creating a barrier to competition, especially for smaller firms. We know from research that competition fosters innovation, especially frontier innovation like AI. The problem with regulation — whether concerning data management or competition — is always the same: technology moves very fast and our institutions move very slow. We need to find a middle ground. 5. Unified market where the EU can come together and launch innovation Among Mario Draghi’s recommendations in his must-read 2024 report on European competitiveness is that the EU needs to have a truly unified single market and financial ecosystem, able to invest in innovation akin to the Advanced Research Projects Agency (ARPA) in the U.S., to get academia, industry and government partners to work together on cutting-edge R&D and expand the frontiers of technology and science. The U.S. also has DARPA, for defense projects, and BARDA, for biomedical research. Europe does breakthrough research but the innovation tends to get done outside of Europe. We need to change that. We have world-class researchers, but we need a massive amount of capital investment in order to make the most of their research, together with a unified market where we can launch their innovations. Time to act: a coalition of the willing to get things done AI represents a turning point in our modern societies, disrupting our ways of thinking, producing and consuming — in short, our entire way of life. This is why it is vital to master these technologies and not wait. Europe tends to act only when there’s an emergency. COVID was an emergency. Ukraine is an emergency. Unfortunately, not enough European leaders perceive the concession of technological leadership to the United States and China as an emergency. In Europe, we should form a coalition of the willing — people who want to align on this agenda and get things done, collaboratively tackling key issues like unifying to develop strong capital markets to invest in innovation. Ideally, all European nations would get on board. In the meantime, let each one of us in our own sphere of influence make a purposeful start. This article is based on remarks delivered by Philippe Aghion at the Economics of AI Conference organized by the Artificial Intelligence and the Future of Management Initiative at IESE Business School in Barcelona. This article originally appeared in the annual publication, Insight for Global Leaders No. 1 (2025).	2025-07-01T00:00:00		https://www.iese.edu/insight/articles/employment-artificial-intelligence-innovation-policy/	[ { "date": "2025/07/01", "position": 38, "query": "artificial intelligence employment" } ]
The Role of Artificial Intelligence in Media Communications	The Role of Artificial Intelligence in Media Communications	https://journals.kmanpub.com	[ "Nadiya", "Faculty Of Social Communication Sciences", "Allameh Tabatabai University", "Tehran", "Navid", "Msc Information Technology", "Amirkabir University Of Technology" ]	This review aims to explore the role of artificial intelligence (AI) in modern media communications, analyzing its historical evolution, current applications, ...	Behl, A., Chavan, M., Jain, K., Sharma, I., Pereira, V., & Zhang, Z. (2021). The Role of Organizational Culture and Voluntariness in the Adoption of Artificial Intelligence for Disaster Relief Operations. International Journal of Manpower, 43(2), 569-586. https://doi.org/10.1108/ijm-03-2021-0178 Chen, J. (2024). The Application and Development of Artificial Intelligence and High Technology in Sports Event. Highlights in Business Economics and Management, 30, 247-255. https://doi.org/10.54097/n7dhp396 Chiang, T. H. C., Liao, C.-S., & Wang, W.-C. (2022). Impact of Artificial Intelligence News Source Credibility Identification System on Effectiveness of Media Literacy Education. Sustainability, 14(8), 4830. https://doi.org/10.3390/su14084830 Du, S. (2024). The Opportunities and Challenges of Theater Stage Design in the Era of Artificial Intelligence. Communications in Humanities Research, 34(1), 216-220. https://doi.org/10.54254/2753-7064/34/20240187 Esch, P. v., & Black, J. S. (2021). Artificial Intelligence (AI): Revolutionizing Digital Marketing. Australasian Marketing Journal (Amj), 29(3), 199-203. https://doi.org/10.1177/18393349211037684 Fteiha, B. (2024). Revolutionizing Video Production: An AI-Powered Cameraman Robot for Quality Content. 19. https://doi.org/10.3390/engproc2024060019 Goar, V. (2022). The Impact and Transformation of Artificial Intelligence. International Journal on Recent and Innovation Trends in Computing and Communication, 10(8), 67-75. https://doi.org/10.17762/ijritcc.v10i8.5677 Grech, A., Mehnen, J., & Wodehouse, A. (2023). An Extended AI-Experience: Industry 5.0 in Creative Product Innovation. Sensors, 23(6), 3009. https://doi.org/10.3390/s23063009 Gu, X. (2024). Enhancing Social Media Engagement Using AI-modified Background Music: Examining the Roles of Event Relevance, Lyric Resonance, AI-singer Origins, Audience Interpretation, Emotional Resonance, and Social Media Engagement. Frontiers in psychology, 15. https://doi.org/10.3389/fpsyg.2024.1267516 Kamkankaew, P. (2024). How Artificial Intelligence Is Helping Businesses Grow and Thrive: The Transformative Role of Artificial Intelligence in Thai B2C Digital Marketing. Ijsasr, 4(1), 137-164. https://doi.org/10.60027/ijsasr.2024.3651 Kar, S. (2023). Impact of Artificial Intelligence on Digital Marketing. 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Economics & Education, 8(4), 27-33. https://doi.org/10.30525/2500-946x/2023-4-4 Rožman, M., Oreški, D., & Tominc, P. (2022). Integrating Artificial Intelligence Into a Talent Management Model to Increase the Work Engagement and Performance of Enterprises. Frontiers in psychology, 13. https://doi.org/10.3389/fpsyg.2022.1014434 Salvetti, F. (2024). Fostering Inclusive Recruitment Interviews With Intelligent Digital Humans. International Journal of Advanced Corporate Learning (Ijac), 17(3), 78-84. https://doi.org/10.3991/ijac.v17i3.45431 Sayoh, M. (2023). Utilizing Artificial Intelligence in Digital Out-of-Home Advertising. التصميم الدولية, 13(4), 417-425. https://doi.org/10.21608/idj.2023.305380 Shah, N., Chauhan, H., & Shah, M. (2020). Research Trends on the Usage of Machine Learning and Artificial Intelligence in Advertising. Augmented Human Research, 5(1). https://doi.org/10.1007/s41133-020-00038-8 Ughulu, J. (2022). The Role of Artificial Intelligence (AI) in Starting, Automating and Scaling Businesses for Entrepreneurs. https://doi.org/10.14293/s2199-1006.1.sor-.pp5zkwj.v1 Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial Intelligence in Marketing: Systematic Review and Future Research Direction. International Journal of Information Management Data Insights, 1(1), 100002. https://doi.org/10.1016/j.jjimei.2020.100002 Xie, Z. (2020). The Symmetries in Film and Television Production Areas Based on Virtual Reality and Internet of Things Technology. Symmetry, 12(8), 1377. https://doi.org/10.3390/sym12081377	2025-07-01T00:00:00		https://journals.kmanpub.com/index.php/aitechbesosci/article/view/3593	[ { "date": "2025/07/01", "position": 22, "query": "artificial intelligence journalism" } ]
Whose Employment is Affected by Unions?	Whose Employment is Affected by Unions?	https://www.nber.org	[ "Karen Glenn", "Stephen Goss" ]	... employment losses associated with unions ... Generative artificial intelligence (AI) has recently emerged as a potentially transformative workplace technology.	More union involvement in wage setting significantly decreases the employment rate of young and older individuals relative to the prime-aged group. In 1973, unemployment in most European countries was modest, ranging between 2.0 and 3.2 percent, compared to 4.8 percent for the United States. By 1995, the unemployment situation for the European countries had changed dramatically, rising to an average of 10.7 percent. But in the United States, the unemployment rate rose only to 5.6 percent by 1995, roughly half that of European countries. This reversal of fortunes was concentrated on youth, older individuals, and women, rather than on prime age males: while the employment-to-population ratios (employment rates) of all groups rose in the United States relative to other Western countries, the increases were especially large for youth and older individuals, and somewhat larger for women, according to new research by Giuseppe Bertola, Francine Blau, and Lawrence Kahn. At the same time, the authors note that unionization fell in the United States compared to these other countries. In Labor Market Institutions and Demographic Employment Patterns (NBER Working Paper No. 9043), the researchers investigate the cross-country impact of labor market institutions on the relative employment rates of youth, women, and older individuals, relative to prime age males. This study overcomes the drawbacks of earlier research by examining data from a wider base of countries, 17 in all, and over a longer time frame, 1960-96. The authors focus on the wage-employment tradeoffs faced by different groups of workers. The countries included in the study were part of the Organization for Economic Cooperation (OECD): Australia, Belgium, Canada, Denmark, Finland, France, Germany, Japan, the Netherlands, Italy, Norway, Portugal, New Zealand, Spain, Sweden, the United Kingdom, and the United States. The researchers control for overall demographic factors, country effects, and institutional factors, such as collective bargaining coverage, labor tax rates, employment protection, unemployment insurance, and rates for retirement benefits, as well as the overall unemployment rate (although results were similar when the unemployment was not included as an explanatory variable). The researchers find that, for both men and women, more union involvement in wage setting significantly decreases the employment rate of young and older individuals relative to the prime-aged group (with no significant effects on the relative unemployment of these groups). In contrast, a larger role for unions has little impact on male-female employment rate differentials but raises female unemployment relative to male unemployment. The authors conjecture that unions, in determining their wage-setting policies, balance out the gains from higher wages against the losses from resulting reductions in employment. Groups with the most extensive non-market opportunities to use time productively suffer the least when they lose employment. These groups are likely to be youth, older individuals, and women, all of whom have more extensive non-market uses of time than prime age males do: household production for women (under a traditional division of labor in the family), schooling for youth, and retirement for older individuals. As a result, unions negotiate the highest wage increases for these groups, leading to larger employment reductions for them. Alternatively, it may be more socially acceptable in highly industrialized societies to concentrate employment losses associated with unions on women, youth, and the elderly. The authors' findings suggest that union wage-setting policies price the young and elderly out of employment and drive affected individuals in these groups to non-labor-force activities, leaving unemployment rates unchanged. A probable scenario for women, according to the authors, is that high union wages encourage them to enter the work force, pushing up their unemployment rates. However, the expected employment declines for women do not materialize, because women who otherwise would not be employed because of the high union wage floors find work in an unregulated work field or in the public sector. -- Marie Bussing-Burks	2025-07-01T00:00:00		https://www.nber.org/digest/dec02/whose-employment-affected-unions	[ { "date": "2025/07/01", "position": 57, "query": "artificial intelligence labor union" } ]
Future of Work Initiative	Future of Work Initiative	https://www.aspeninstitute.org	[]	AI and the Future of Work(ers) ... Algorithms are influencing decisions about hiring, firing, and worker management, yet there is rarely transparency and ...	The Future of Work Initiative empowers and equips leaders to innovate workplace structures, policies, and practices that renew rather than erode America’s social contract. About the Future of Work Initiative Work forms the backbone of America’s social contract. It defines how people access opportunity, build security, and participate in the promise of the American dream. The future of work will determine whether this social contract strengthens or erodes. That future is not decades away. Accelerated technological change and declining social trust are exposing gaps in current policies and markets right now. This creates an urgent opportunity to bring stakeholders together who can actively shape what comes next. We The Future of Work Initiative collaborates with colleagues across the Economic Opportunities Program and the broader Aspen Institute to pursue this vision. Our work centers on three core questions: What support do business and labor leaders need to advance experimentation and advocacy for shared prosperity? How can we reimagine workplace governance, protections, and benefits to build resilience against rapid change and close gaps based on place, race, education, and gender? How can structured, transparent collaboration between labor and business help restore social trust? We cultivate leadership across sectors to create specific conditions for the future. We envision businesses that value workers and their organizations as essential innovation partners. We want workers to have multiple pathways for exercising agency over their economic and technological futures. We seek business metrics that align with worker empowerment. Our goal is to equip leaders to shape the future rather than merely adapt to it. We aim to point the way toward solutions that heal America’s social divisions and strengthen the social contract that work makes possible.	2025-07-01T00:00:00		https://www.aspeninstitute.org/programs/future-of-work/	[ { "date": "2025/07/01", "position": 45, "query": "future of work AI" } ]
automation-supervisor \| Job Details tab \| Career Pages	Job Opportunities	https://www.governmentjobs.com	[]	Under general direction, supervise, plan, direct and oversee the Supervisory Control and Data Acquisition (SCADA) system, automation ...	Welcome to Irvine Ranch Water District's employment page! IRWD is dedicated to providing and maximizing the efficient use and reuse of water and renewable resources to benefit our customers and to enhance the environment. We seek highly qualified, innovative and creative people who are committed to these guiding principles and dedicated to excellence in public service. IRWD was built on values, and we weave them into the fabric of everything we do. Those values are: integrity, transparency, innovation, teamwork, collaboration, accountability, safety, opportunity, customer care, respect, kindness, and environmental stewardship. In compliance with the Americans with Disabilities Act (ADA), if you need an accommodation in the application or selection process, please contact human resources at 949-453-5436. Irvine Ranch Water District is an Equal Opportunity Employer. We promote equal employment opportunity to all qualified applicants without regard to race, color, ancestry, national origin, genetic information, religion, exercise of the right to family care and medical leave, sex, sexual orientation, gender, identity, gender expression, age, mental disability, physical disability, medical condition, military and veteran status, political affiliation, taking time off to serve on a jury trial with reasonable notice, taking time off to appear in court to comply with a court order to appear as a witness, or status as a victim of domestic violence, sexual assault or stalking.	2025-07-01T00:00:00		https://www.governmentjobs.com/careers/irwd/jobs/4710689/automation-supervisor?pagetype=jobOpportunitiesJobs	[ { "date": "2025/07/01", "position": 67, "query": "job automation statistics" } ]
AI + EQ: The Power of Emotional Intelligence in ...	AI + EQ: The Power of Emotional Intelligence in the Adoption of AI	https://www.shrm.org	[ "Eric House" ]	Explore how HR leaders can drive successful AI implementation by prioritizing emotional intelligence, transparency, and trust.	Designed and delivered by HR experts to empower you with the knowledge and tools you need to drive lasting change in the workplace. Demonstrate targeted competence and enhance credibility among peers and employers. Gain a deeper understanding and develop critical skills.	2025-07-01T00:00:00		https://www.shrm.org/topics-tools/flagships/ai-hi/power-of-eq-in-adoption-of-ai	[ { "date": "2025/07/01", "position": 31, "query": "workplace AI adoption" } ]
Hierarchical gap in workplace AI adoption	Hierarchical gap in workplace AI adoption	https://www.hcamag.com	[ "Dexter Tilo" ]	Gaps in artificial intelligence use in the workplace might be more hierarchical than generational, according to a new report, which found that people at the ...	It also found that executives are more than twice as likely to create efficiencies using AI than ICs. Among their uses include drafting emails to clients and creating presentations. "This staggering divide indicates a significant disconnect between those at the top and their employees, where those in managerial positions are in a better position to recognise the value of AI in optimising operations and decision-making processes but may be failing to communicate that value to their employees," the BambooHR report read. Beyond daily use, the gap also exists when it comes to training. According to the report, 72% of employees want to improve their AI skills, but only 32% said they had received formal AI training from their employer. Half of managers and more senior titles also received training on AI, compared to just 23% of ICs, the report added.	2025-07-01T00:00:00		https://www.hcamag.com/ca/news/general/hierarchical-gap-in-workplace-ai-adoption/541162	[ { "date": "2025/07/01", "position": 44, "query": "workplace AI adoption" } ]
Study: Over Half of Organizations Seeing ROI on AI Adoption	Over Half of Organizations Seeing ROI on AI Adoption, Study Says	https://tech.co	[ "Nicole Mousicos", "Nicole Is A Writer At Tech.Co. On Top Of A Degree In English Literature", "Creative Writing", "They Have Written For Many Digital Publications", "Such As Outlander Magazine. They Previously Worked At Expert Reviews", "Where They Covered The Latest Tech Products", "News. Outside Of Tech.Co", "They Enjoy Keeping Up With Sports", "Playing Video Games." ]	Through its research, Thomson Reuters has developed a 'pyramid for success' to enable businesses to properly adopt AI into their workplace. Most important, it ...	A new report from Thomson Reuters has revealed that over half of organizations are already seeing return-on-investment (ROI) directly or indirectly from AI adoption. The report took data from 2,275 professionals in the legal, risk, compliance, tax, accounting, audit, and trade industries. Through its research, Thomson Reuters has developed a ‘pyramid for success’ to enable businesses to properly adopt AI into their workplace. Most important, it appears, is having a strong AI strategy. Corporate AI adoption may be leveling off, but Thomson Reuters still urges businesses in its report to stay agile and adapt to the new technology.	2025-07-01T00:00:00	2025/07/01	https://tech.co/news/businesses-seeing-roi-from-ai-adoption	[ { "date": "2025/07/01", "position": 46, "query": "workplace AI adoption" } ]
Despite 62% workplace AI adoption, Filipino Workers stay ...	Despite 62% workplace AI adoption, Filipino Workers stay for friends than features, study finds	https://www.bworldonline.com	[]	In a striking contradiction to Silicon Valley's tech-first workplace revolution, new research reveals that as AI adoption soars to 62% across Filipino ...	In a striking contradiction to Silicon Valley’s tech-first workplace revolution, new research reveals that as AI adoption soars to 62% across Filipino workplaces, employee retention depends more on workplace friendships than cutting-edge features. The finding emerges from the 2025 State of HR Report prepared by Sprout Solutions and BS Works—the country’s most comprehensive workforce study involving 3,819 employees—unveiled at the State of HR Summit 2025. The research exposes what analysts call “The Great AI Retention Paradox”: while companies pour resources into AI-powered productivity tools, workers stay or leave based on fundamentally human factors. The numbers tell a compelling story: Employees with three or more workplace friendships are 40% more likely to remain beyond five years, while those citing “sadness at leaving colleagues” as a retention factor outnumber those motivated by salary increases 3:1. The connection-retention formula The research reveals “The 3 C’s of AI-Era Retention”: Connection, Contribution, and Community. Organizations scoring highest across these human-centered metrics show 35% lower turnover rates, even when offering below-market compensation. Connection: Employees embedded in one to three workplace social groups demonstrate significantly longer tenure, with each additional meaningful relationship correlating with eight months of extended employment. Contribution: Workers reporting clear purpose and meaningful contribution stay 2.3 times longer than those focused primarily on career advancement or salary growth. Community: Organizations fostering informal support networks see retention rates climb despite offering fewer remote work options than competitors. “Companies implementing AI to boost efficiency while neglecting human connection are optimizing for the wrong variables,” explained Patrick Gentry, CEO of Sprout Solutions. Generational divide reveals leadership evolution The study uncovers striking generational differences challenging traditional management. While Baby Boomers prefer independent, low-context leadership environments, Millennials and Gen Z gravitate toward collaborative, high-context workplace cultures—coinciding with AI-augmented work environments. “Gen Z workers don’t want AI to replace human interaction—they want it to enable deeper collaboration,” noted Maria Lourdes Ann “L.A.” Cruz, VP of People at Lufthansa Technik Philippines. “The most successful organizations use AI to create more time for meaningful human connection, not less.” The AI readiness gap Despite widespread adoption, research reveals a critical implementation divide. Organizations perceived as “AI-ready” show three times higher tool adoption rates and significantly better retention outcomes. However, readiness depends less on technology infrastructure and more on change management and cultural preparation. This aligns with recent MIT research showing successful AI implementation correlates more strongly with organizational culture than technical capability—positioning the Philippines data as a leading indicator for global workforce trends. Global implications for the $720B talent crisis The findings arrive as global organizations grapple with what McKinsey estimates as a $720 billion annual cost from employee turnover. While most retention strategies focus on compensation and benefits, the Philippine data suggests a fundamentally different approach. “If these patterns hold globally, we’re looking at a complete rethinking of retention strategy,” said Kislay Chandra, chief operations officer of Sprout Solutions. “The solution isn’t more sophisticated AI tools—it’s more sophisticated human connection.” Actionable framework for leaders Based on the research, Sprout and BS Works developed the “HUMAN Protocol” for AI-era retention: Host regular cross-functional social interactions Understand individual purpose and contribution motivations Measure and foster workplace friendship networks Align AI implementation with human connection goals Nurture interest-based communities and support groups Early adopters report 25% improvement in retention metrics within six months. Building on success The State of HR Summit 2025, co-presented with BS Works, brought together more than 500 HR and business leaders at Manila’s Crowne Plaza Galleria. The event featured panels on “Lead to Last: Retaining Talent Through Empowered Leadership” with executives from Tala, Canva, and Lufthansa Technik Philippines, exploring practical applications of the research findings. The summit builds on the momentum of five consecutive annual State of HR events hosted by Sprout Solutions, while introducing new data-driven insights for organizations navigating the intersection of AI adoption and human-centered workplace culture. The event also saw the unveiling of Sidekick Central, a multi-functional AI platform offering specialized AI-Sidekicks for HR, payroll, management, and employee support that will help teams achieve up to 40% productivity gains and reduce repetitive admin across operations. Spotlight is BusinessWorld’s sponsored section that allows advertisers to amplify their brand and connect with BusinessWorld’s audience by publishing their stories on the BusinessWorld Web site. For more information, send an email to [email protected]. Join us on Viber at https://bit.ly/3hv6bLA to get more updates and subscribe to BusinessWorld’s titles and get exclusive content through www.bworld-x.com.	2025-07-01T00:00:00	2025/07/01	https://www.bworldonline.com/spotlight/2025/07/01/682537/despite-62-workplace-ai-adoption-filipino-workers-stay-for-friends-than-features-study-finds/	[ { "date": "2025/07/01", "position": 58, "query": "workplace AI adoption" } ]
A strategic HR learning initiative for Gen AI adoption	A strategic HR learning initiative for Gen AI adoption	https://www.smartbrief.com	[]	Generative AI tools promise significant gains in efficiency and creativity, but for many in the workforce, navigating this new technology can feel daunting.	Peer mentoring is a transformative strategy that can revolutionize how organizations manage the adoption of generative AI (Gen AI). From a human resources perspective, leveraging personal connections and shared expertise is a powerful method to accelerate learning, foster collaboration and fuel innovation, while managing risks. In today’s competitive business environment, achieving mastery of Gen AI tools is critical, making this talent development approach essential for workforce readiness. The human-centric approach to Gen AI upskilling Generative AI tools promise significant gains in efficiency and creativity, but for many in the workforce, navigating this new technology can feel daunting. This is a key change management challenge where peer mentoring can serve as a bridge from employee uncertainty to confidence. When employees learn from colleagues who have already mastered Gen AI, they acquire not only technical skills but also context-specific insights directly relevant to their roles. An employee guided by a peer who understands the nuances of their workload will have a more effective learning experience than one attending a generic webinar. Peer mentors personalize the learning process, breaking down complex topics and demonstrating their use in real-world work scenarios. This targeted guidance makes Gen AI tools more accessible and relatable for employees. Empowering internal talent as program leaders HR departments can tap in to the goldmine of talent that organizations often possess within their ranks. The early adopters of Gen AI, those employees who have enthusiastically used these tools to improve tasks like coding, content creation and data analysis, are an invaluable resource for upskilling initiatives. A structured peer mentoring program utilizes this internal resource, positioning these employees as mentors who can guide their colleagues toward proficiency. For instance, a mid-sized professional services company with which I consulted identified its Gen AI-savvy employees as catalysts for broader adoption. These employees, previously scattered across different departments, were organized into a formal mentoring program. Their mission was to mentor colleagues who were eager to learn the new tools but were unsure how to begin. This programmatic approach ensured the company actively disseminated expertise across all teams. Designing tailored learning and development pathways The value of peer mentoring as a learning and development tool lies in its flexibility and relevance. Unlike traditional corporate training that often feels disconnected from daily work, these mentoring sessions are tailored to the specific developmental needs of each mentee. For example, a marketing employee’s learning path could focus on content creation and effective prompting, while an engineering colleague’s could concentrate on coding automation. The professional service company’s program highlighted this tailored approach. Mentors shared practical tips they had discovered, demonstrated advanced techniques and helped troubleshoot challenges their mentees faced. The program also included group workshops, which amplified knowledge-sharing and allowed mentors to present their expertise to a broader audience while building mentee confidence. A win-win for employee growth and engagement Peer mentoring programs benefit not only the employees learning Gen AI but are also highly rewarding for the mentors themselves. Early adopters receive formal recognition for their expertise, which boosts their professional visibility and their pride in their work. Mentors also cultivate their own leadership and communication skills, positioning themselves as thought leaders within the organization. At the same time, mentees undergo a significant transformation in their roles. With hands-on guidance and personalized support, they grow more confident in their ability to use Gen AI tools effectively. This confidence empowers employees to experiment, iterate and innovate, leading to tangible improvements in their productivity and innovation. The positive impact on organizational culture The effect of peer mentoring extends beyond individual skill-building to transform the entire organizational culture. During a 12-month initiative, the professional service company saw employees become not only more proficient with Gen AI tools but also more eager to share their new knowledge with others. This created a ripple effect of knowledge-sharing that fostered a culture of collaboration and continuous learning. Employees from different departments connected over these shared experiences, which strengthened professional relationships and helped break down organizational silos. The workplace became a more vibrant hub of innovation as employees actively looked for new ways to integrate Gen AI into their daily workflows. Measuring the ROI of the mentoring program The results of the peer mentoring program were undeniable and demonstrated a clear return on investment. Productivity increased as employees streamlined their workflows with Gen AI, completing tasks faster and with higher precision. The quality of work improved as employees applied advanced techniques to tasks like content creation, data analysis and client outreach. The organization’s culture shifted toward one of enthusiasm for learning and innovation. Specific metrics highlighted the program’s success: teams using Gen AI reported time savings of over 25%, and cross-departmental collaborations saw a 30% increase. Employees rated the program as one of the most effective initiatives for their professional growth, noting that it demystified Gen AI technology. Why peer mentoring is the future of workforce development As businesses face the rapid evolution of Gen AI, traditional training methods alone are insufficient. Peer mentoring offers a dynamic, scalable solution that accelerates learning while also strengthening the fabric of workplace relationships. By empowering early adopters and fostering a culture of collaboration, HR leaders can ensure their employees become pioneers of innovation rather than mere users of Gen AI tools. In an era where technology can often feel impersonal, this strategy injects a vital human element into the learning process. For organizations prepared to embrace Gen AI, it is one of the most powerful workforce development tools available. Opinions expressed by SmartBrief contributors are their own. ____________________________________ Take advantage of SmartBrief’s FREE email newsletters on leadership and business transformation, among the company’s more than 250 industry-focused newsletters.	2025-07-01T00:00:00		https://www.smartbrief.com/original/a-strategic-hr-learning-initiative-for-gen-ai-adoption	[ { "date": "2025/07/01", "position": 87, "query": "workplace AI adoption" } ]
AI Guide for Government - IT Modernization Centers of Excellence	AI Guide for Government	https://coe.gsa.gov	[]	This AI Guide for Government is intended to help government decision makers clearly see what AI means for their agencies and how to invest and build AI ...	Once you’ve identified a project, assemble the Integrated Product Team (IPT) outlined in Chapter 4: Developing the AI workforce to ensure the necessary parties are engaged and dedicated to delivering success. Whether the project is a small pilot or a full-scale engagement, moving through the AI life cycle to go from business problem to AI solution can be hard to manage. Internal prototype and piloting Internal or organic prototypes (exploration without vendor support) provide a great way to show value without having to commit the resources required for a production deployment. It allows you to take a subset of the overall integration and tackle one aspect of it to show how wider adoption can happen. This requires technical skills, but can rapidly increase AI’s adoption rate as senior leaders see the value before committing resources. Prototyping internally can help identify where in the life cycle to seek a vendor. Not all steps require vendor support (single or many). It can also show when and how to best engage a vendor. It could reveal either that you should engage early to turn an internal prototype into a pilot, or that you should develop a pilot before engaging a vendor for full-scale production. From pilot to production Once you’ve completed a successful pilot, look to evaluate its effectiveness towards your objectives. If you determine that the pilot proved enough value—with clearly defined and quantified KPIs—that your agency wants a longer term solution, then you should seek to move the pilot to production. If you need vendor support for scaling, take the key findings from the pilot and translate them into a procurement requirement so a private vendor can take over providing the service. The pilot’s success allows the work already done to serve as the starting point for the requirements document. Prototypes/pilots intentionally scale the problem down to primarily focus on the data gathering and implementation. When moving to production, you have to consider the entire pipeline. The requirements must feature the ways in which the results from the model will be evaluated, used, and updated. The three most important items to consider when moving to production are these: Project ownership What part of the organization will assume responsibility for the product’s daily continuation? Implementation plan Since the pilot addressed only a small part of the overarching problems, how will you roll out the solution to the whole organization? Sunset evaluations At what point will the organization no longer need the results coming from the AI solution? Who and how will this be evaluated? These are important questions to consider, which is why the test and evaluation process is critical for AI projects. Start building AI capabilities If there are existing data, analytics, or even AI teams, align them to the identified use cases and the objective of demonstrating mission or business value. If there are no existing teams, your agency may still have personnel with relevant skill sets who haven’t yet been identified. Survey the workforce to find this talent in-house to begin building AI institutional capability. To complement government personnel, consider bringing in contractor AI talent and/or AI products and services. Especially in the early stages, government AI teams can lean on private-sector AI capabilities to ramp up government AI capability quickly. But you must approach this very carefully to ensure sustainability of robust institutional AI capabilities. For early teams, focus on bringing in contractors with a clear mandate to train government personnel or provide infrastructure services when the AI support element has not yet been stood up. Buy or build The commercial marketplace offers a vast array of AI products and services, including some of the most advanced capabilities available. Use the research and innovation of industry and academia to boost government AI capabilities. This can help speed the adoption of AI and also help to train your team on the specific workflows and pipelines needed in the creation of AI capabilities. Agencies should focus also on building their own sustainable institutional AI capability. This capability shouldn’t overly rely on external parties such as vendors/contractors, who have different incentives due to commercial firms’ profit-seeking nature. Especially with limited AI talent, agencies should strategically acquire the right skills for the right tasks to scale AI within the agency. Agencies’ ultimate goal should be to create self-service models and shareable capabilities rather than pursuing contractors’ made-to-order solutions. Agencies must weigh the benefits and limitations of building or acquiring the skills and tools needed for an AI implementation. Answering the “buy or build” question depends on the program office’s function and the nature of the commercial offering. External AI products and services can be broadly grouped into these categories: Examples include email providers that use AI in their spam filters, search engines that use AI to provide more relevant search results, language translation APIs that use AI for natural language understanding, and business intelligence tools that use AI to provide quick analytics. Examples include tools for automating data pipelines, labeling data, and analyzing model errors. Open source Open-source software is used throughout industry and heavily relied on for machine learning, deep learning, AI research, development, testing and ultimately operation. Note, that many of these frameworks and libraries are integrated into many top “proprietary software applications”. Mission centers and program offices, the heart of why agencies exist in the first place, need to ensure a sustainable institutional AI resource by focusing on building. A team of government AI practitioners dedicated to the mission’s long-term success is necessary for building robust core capabilities for the agency. Commercial tools that enhance these practitioners’ effectiveness may be worth the cost in the short-term. However, mission centers sometimes have unique requirements that do not exist in a commercial context, which makes commercial-off-the-shelf (COTS) standalone offerings less likely to fit. Even if the agency could find an adequate COTS product, using it would be a major operating risk for an agency’s core functions to rely so much on external parties. On the other hand, business centers are likely to benefit from AI-enhanced standalone tools. Business centers often focus on efficiency while having requirements most likely to match commercial requirements, so COTS products are more likely to fit. Business centers still need government AI talent, who can evaluate and select the most appropriate commercial AI offerings. Besides products and services and their associated support personnel, contractors may also offer standalone AI expertise as contractor AI practitioners. These kinds of services are well-suited to limited or temporary use cases, where developing long term or institutional capability is not needed. In the early stages of implementing AI in an agency, contractor AI personnel can help train and supplement government AI personnel. But as with commercial AI tools, wholesale outsourcing core capabilities to contractor personnel teams creates major operating risk to an agency’s ability to perform core functions. Think in terms of Infrastructure as Code (IaC), the ability to rapidly provision and manage infrastructure, to design and build out your AI Platform, creating automations and agile pipelines that are conducive for PeopleOps, CloudOps, DevOps, SecOps, DataOps, MLOps and AIOps. Infrastructure as code (IaC) brings the repeatability, transparency, and testing of modern software development to the management of infrastructure such as networks, load balancers, virtual machines, Kubernetes clusters, and monitoring. The primary goal of IaC is to reduce error, configuration deltas and increase automations, while allowing engineers to spend time on higher value workflows. Another goal would be shareable IaC across the federal government. IaC defines what the end state of your infrastructure needs to be, then builds the resources necessary to achieve and self-heal . Using infrastructure as code also helps standardize cluster configuration and manage add-ons like network policy, maintenance windows, and Identity and Access Management (IAM) for cluster nodes and workloads in support of AI, ML, Data workloads and pipelines. Acquisition journey After your agency decides to acquire commercial products or services, consider these practices to increase your odds of success: Use a Statement of Objectives (SOO) when you are less certain of a solution’s path and want to consider innovative or unorthodox methods. Consider using a Performance Work Statement (PWS) when you have clear specifications on what the product or service needs to do. A PWS, outside of a SOO, is written incorporating measurable standards that inform the contractor of the government’s desired outcomes. How the contractor achieves those outcomes is up to them. The contractor is thus empowered to use the best commercial practices and its own innovative ideas to achieve the desired results. Include technical tests in your solicitation as evaluation criteria. These tests should allow your technical subject-matter experts on your evaluation panel to verify the ability of any suggested approaches to apply to your program’s specific circumstances. Data rights and intellectual property clauses aren’t the only ways to ensure a project can move from one team to another. You’ll want to include deliverables like product backlogs and open source repositories with the entire source code along with all necessary artifacts to create technical and process-agnostic solutions. To minimize taxpayer exposure to repetitive buys, ensure at least government usage rights to balance private-sector concerns while maximizing the government’s investments. Use retrospectives on the acquisition process to identify key clauses and language that worked and those that caused problems, both in terms of the solicitation and post-award management. Document lessons learned to allow new and inexperienced members of the team to ramp up quickly. Share the results of your experiences with your federal colleagues. There is no better way to gain knowledge and improve the experience with implementing AI in a department and agency than working with others who have similar projects. You can join the Federal AI Community of Practice to connect with other government agencies working in AI. Test and evaluation process Some agencies in the defense and intelligence community already emphasize testing and evaluating software. Due to the nature of AI development and deployment, all AI projects should be stress tested and evaluated. Very public examples of AI gone wrong show why responsibility principles are a necessary and critical part of the AI landscape. You can address many of these challenges with a dedicated test and evaluation process. The basic purpose of Test & Evaluation (T&E) is to provide knowledge to manage risk that’s involved in developing, producing, operating, and sustaining systems and capabilities. T&E reveals system capabilities and limitations to improve the system performance, and optimize system use, and sustain operations. T&E provides information on limitations (technical or operational) and Critical Operational Issues (COI) of the system under development to resolve them before production and deployment. Traditional systems usually undergo two distinct stages of test and evaluation. First is developmental test and evaluation (DT&E), which verifies that a system meets technical performance specifications. DT&E often uses models, simulations, test beds, and prototypes to test components and subsystems, hardware and software integration, and production qualification. Usually, the system developer performs this type of testing. DT&E usually identifies a number of issues that need fixing. In time, operational test and evaluation (OT&E) follows. At this stage, the system is usually tested under realistic operational conditions and with the operator. This is where we learn about the system’s mission effectiveness, suitability, and survivability. Some aspects of T&E for AI-enabled systems are quite similar to their analogues in other software-intensive systems. However, there are also several changes in the science and practice of T&E that AI has introduced. Some AI-enabled systems present challenges in what to test, and how and where to test it; all of those are, of course, dependent on the project. At a high level, however, T&E of AI-enabled systems is part of the continuous DevSecOps cycle and Agile development process. Regardless of the process, the goal of T&E is to provide timely feedback to developers from various levels of the product: on the code level (unit testing), at the integration level (system testing, security and adversarial testing), and at the operator level (user testing). These assessments include defining requirements and metrics by talking with various stakeholders, designing experiments and tests, and doing analysis and making actionable recommendations to the leadership on overall system performance across its operational envelope. T&E for Projects On a project, there are various levels of T&E; each reveals important information about the system under test: Model T&E This is the first and simplest part of the test process. In this step, the model is run on the test data and its performance is scored based on metrics identified in the test planning process. Frequently, these metrics are compared against a predetermined benchmark, between developers, or with previous model performance metrics. The biggest challenge here is that the models tend to arrive to the government as black boxes due to IP considerations. For the most part, when we test physical systems, we know exactly how each part of that system works. However, we don’t know how the models work; that’s why we test. If you want testable models, you have to make that a requirement at the contracting step. Measuring model performance is not entirely straightforward; here are some questions you might want your metrics to answer: How does the model perform on the data? How often does it get things right / wrong? How extreme are the mistakes the model makes? What kind of mistakes does the model make? Is there any evidence of model bias? Ultimately, does the model tend to do what it’s supposed to (find or identify objects, translate, etc.?) Integrated System T&E In this step, you evaluate the model not by itself but as part of the system in which it will operate. In addition to the metrics from model T&E, we look for answers the following questions: Does the model performance change on an operationally realistic system? Does the model introduce additional latency or errors? What is the model’s computing burden on the system? Is this burden acceptable? Operational T&E In this step, we collect more information on how the AI model ultimately affects operations. We do this through measuring: Effectiveness (mission accomplishment) Suitability (reliability, compatibility, interoperability, human factors) Resilience (ability to operate in the presence of threats, ability to recover from threat effects, cyber, adversarial) Ethical T&E Depending on the AI solution’s purpose, this step ensures the system does only what it’s supposed to do and doesn’t do what it’s not supposed to do. To ensure that AI tools, capabilities, and services are not only acquired, but also properly integrated into the wider program’s business goals, consider these practices to increase your chances of success:	2025-07-06T00:00:00		https://coe.gsa.gov/coe/ai-guide-for-government/print-all/index.html	[ { "date": "2025/07/06", "position": 26, "query": "government AI workforce policy" }, { "date": "2025/07/06", "position": 17, "query": "government AI workforce policy" }, { "date": "2025/07/06", "position": 22, "query": "government AI workforce policy" } ]
The algorithm will see you now? Deliberate the future of AI, youth ...	The algorithm will see you now? Deliberate the future of AI, youth and mental health	https://www.who.int	[]	Join the WHO Youth Council and the Stanford University Deliberative Democracy Lab for a global discussion on AI, youth, and digital health.	Join the WHO Youth Council and the Stanford University Deliberative Democracy Lab for a global discussion on AI, youth, and digital health. Artificial intelligence is reshaping mental health care—fast. But how can we ensure that youth and other community voices shape how these tools are developed, deployed, and governed? This side-event of the UN High-Level Political Forum is a unique opportunity to participate in informed, moderated small-group dialogue, ask questions to global experts, and influence policy during the UN High Level Meeting and beyond as we look ahead of the 2025 UN High-Level Meeting on NCDs and Mental Health. What You’ll Do: ✔️ Participate in small-group discussions with global youth ✔️ Ask real questions to top experts ✔️ Shape global health & digital policy Choose your session on 23 July: 06:00–08:00 UTC/11:30-13:30 New Delhi/16:00-18:00 Sydney 06:00–08:00 UTC/11:30-13:30 New Delhi/16:00-18:00 Sydney 13:00–15:00 UTC/14:00-16:00 London/16:00-18:00 Cairo 21:00–23:00 UTC/17:00-19:00 New York/15:00-17:00 Mexico City Register now → 23 July 2025 -- Americas -- 21:00–23:00 UTC/17:00-19:00 New York/15:00-17:00 Mexico City Hosted by: WHO Youth Council and Stanford Deliberative Democracy Lab Co-hosted by: Co-hosted with UNICEF; UNFPA; Major Group for Children and Youth (MGCY); World Organization of the Scouting Movement;; Stanford University Democracy Hub; International Federation of Medical Students’ Associations (IFMSA); International Pharmaceutical Students’ Federation (IPSF); Act4Food, a campaign of the Global Alliance for Improved Nutrition; Young WFPHA (World Federation of Public Health Associations); International Student Surgical Network (InciSioN); Universities Allied for Essential Medicines; Digital Transformations for Health Lab (DTH-Lab); International Youth Health Organization (YHO); European Network of Medical Residents in Public Health (EuroNet MRPH); Alianza Juvenil (Youth Alliance-Youth Lead Branch of CLAS); Youth and Environment Europe; Transform Health; Citizen Outreach Coalition; iCure Health International; United Nations Association of the United States of America—Stanford University Chapter; International LGBTQI Youth and Student Association (IGLYO); Climate Cardinals; Beyond Barriers; Next Gen Advocates; Grassroot Soccer Inc; and Orygen	2025-07-23T00:00:00	2025/07/23	https://www.who.int/news-room/events/detail/2025/07/23/default-calendar/the-algorithm-will-see-you-now--deliberate-the-future-of-ai--youth-and-mental-health	[ { "date": "2025/07/23", "position": 96, "query": "future of work AI" } ]

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