The AI/Labor Report

In Today’s NewsMeta Fired 8,000 People Yesterday, From 4am OnwardAmazon’s Jeff Bezos Tries To Sell The Wonders Of AIPew Research Says Most Americans Dislike The Idea Of AIUpwork Cuts A Quarter Of Its Human LaborS&P 500 Employed Fewer Staff In 2025 Than In 2016Pharma On A Layoff SpreeMeta LayoffsYesterday morning, Meta began executing the largest single-day workforce reduction in its history. Notifications went out at 4 a.m. local time, rolling across time zones from Singapore to Europe to the United States. By the end of the day, 8,000 people had lost their jobs, 6,000 open positions had been cancelled, and 7,000 remaining workers had been redirected into newly created AI-focused units.The specific teams cut first tell you something about the company’s strategy going forward. Workers on Meta’s integrity team, the group responsible for removing hate speech and malicious content, were among the first to go. So were members of the cybersecurity team and the content design division. Meta had already moved in March to replace third-party contractors handling content moderation with AI systems.Listen on Apple PodcastsThe May 20 layoffs formalized what the March contractor transition had already begun. The workers who kept the platforms safe from manipulation are now the workers AI displaced first.Zuckerberg’s memo to staff that morning read: “Success isn’t a given” in the AI era. Meta’s CFO told investors during the Q1 earnings call that executives “don’t really know what the optimal size of the company will be in the future.” That admission came from a company in the middle of cutting 10 percent of its workforce and committing up to $145 billion in capital spending this year, most of it on AI infrastructure.The total displacement at Meta since 2022 now stands at roughly 25,000 workers. More cuts are planned for the second half of 2026.Jeff Bezos Went on CNBC the Same MorningWhile Meta’s notifications were going out, Amazon founder Jeff Bezos appeared on CNBC’s Squawk Box and told viewers that workers worried about AI displacement are “dead wrong.”“If you’ve been digging out a basement for your house with a shovel and somebody’s about to hand you a bulldozer, you should be so happy,” Bezos said. He predicted that AI will produce so much productivity and economic abundance that the real problem will be a labor shortage, not unemployment.He added that housing will get cheaper, food will get cheaper, and that households with two earners will voluntarily see one person leave the workforce. Asked directly whether Amazon has laid off workers due to AI, Bezos said there have been no AI-related layoffs at the company. Amazon has cut at least 30,000 workers since October 2025.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.The timing of the interview and the layoffs was not coordinated. That makes it more instructive, not less. The same morning that thousands of workers learned by email that their jobs were gone, the founder of one of the largest employers in America described the situation as a gift.Nevertheless, an October 2025 New York Times article cites that Amazon expects to sell roughly twice as many products by 2033, yet its internal robotics team aims to avoid hiring more than 600,000 U.S. workers who would otherwise be needed to handle that volume.In other words, Amazon is describing jobs that will never be created, not jobs being eliminated from existing workers.A Pew Research Center survey cited in coverage of the Bezos interview found that half of U.S. adults are more concerned than excited about AI. Among employed workers specifically, 52 percent say they feel worried about the future impact of AI in the workplace, 33 percent feel overwhelmed, and 32 percent believe AI will lead to fewer job opportunities for them long-term. The workers in that survey are not describing an abstract future. They are describing the labor market they are already in.Upwork Cuts a Quarter of Its Workforce. Its Product Is Human Labor.On May 7, Upwork CEO Hayden Brown announced the company would cut roughly 25 percent of its workforce, writing in a memo to employees: “Two pizza teams are dead. AI means smaller, differently resourced teams in product and engineering can make a bigger impact than ever.”Upwork is a marketplace that exists to connect businesses with freelance human workers. The platform is now cutting its own human staff while routing more work through AI agents. The company’s stock fell 19 percent on the announcement. Upwork’s CEO framed the cuts as structural, not cyclical, built around the premise that AI permanently reduces the number of people needed to produce a given output.Coinbase, PayPal, Cloudflare, Freshworks, and Block all announced similar double-digit cuts in the same two-week window, each citing AI efficiency as the primary driver. The pattern across the cohort is consistent: companies with flat-to-rising revenue are using AI as the stated reason for headcount reductions, not weak demand.The S&P 500 Employed Fewer People in 2025 Than in 2016The layoffs at Upwork, Meta, and the May cohort are not isolated decisions. S&P 500 total headcount fell in 2025 for the first time since 2016, with the combined workforce of America’s largest public companies dropping by roughly 400,000 workers and ending eight consecutive years of employment growth.BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time.The companies that define American corporate employment are collectively employing fewer people.Despite a growing economy and record capital spending, humans are mere collateral to be shed.The capital is going up into AI infrastructure. The headcount is going down.Biopharma Layoffs Are Up 24 Percent Year Over YearBiopharma companies cut 14,167 workers in the first four and a half months of 2026, up 24 percent from the same period in 2025. Takeda Pharmaceutical’s 4,500-person reduction drove much of the increase.The AI/Labor Report is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The biopharma sector employs large numbers of administrative, operational, and support workers who have no particular reason to identify with the tech layoff narrative. They are in it anyway.Fifty-two biopharma companies made cuts in the first four and a half months of 2026, compared to 114 in the same period of 2025. Fewer companies are cutting, but each cut is larger. The layoff wave is consolidating into bigger, more deliberate restructurings, the kind that reflect strategic decisions rather than quarterly belt-tightening.The picture across all of these stories is the same one the Bureau of Labor Statistics data confirmed last Friday. The headline economy looks stable. Underneath the headline, though, the sectors where most workers actually earn their living are contracting. The companies doing the contracting are reporting that this is the plan.More StoriesProduction support from Eleven Labs Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Eight Thousand Jobs Disappear at Meta Tomorrow. Federal Data Shows the Pattern Runs Far Deeper.Wednesday morning, Meta begins cutting roughly 8,000 employees, or 10 percent of its global workforce. The company is also cancelling plans to fill 6,000 open roles it had already posted. That is 14,000 fewer jobs at a single company in a single week.Meta has signaled more rounds are coming in the second half of the year. The stated reason is the same one you have heard all year: the company needs to redirect money toward AI infrastructure.It would be easy to read this as a story about one technology giant. Federal data published Friday by the Bureau of Labor Statistics makes clear the story runs much wider than that.The Government’s Own Numbers Now Show the DisplacementAccording to Bloomberg, a group of 18 occupations the BLS identifies as exposed to AI. Data shows 10 million workers lost employment between May 2024 and May 2025.Those 18 occupations fell 0.2 percent while overall employment rose 0.8 percent. That gap of one full percentage point is the distance between the economy workers live in and the economy the headlines describe.Listen on Apple PodcastsThe workers absorbing the biggest losses hold everyday service and office roles. Customer service representatives lost 130,180 jobs, a 4.8 percent drop in a single year. Secretaries and administrative assistants outside medical, legal, and executive offices fell 1.8 percent.Wholesale and manufacturing sales representatives fell 2.3 percent. Since ChatGPT launched in late 2022, credit authorizers and checkers are down 26.2 percent, broadcast announcers and radio disc jockeys down 20.8 percent, and sales engineers down 13.2 percent.These are roles that exist in every mid-sized American city. The BLS data confirms what many workers in these fields have been experiencing directly: their occupations are contracting while the broader job market expands around them.Goldman Sachs Identifies the Mechanism: It Starts With Job Postings, Not LayoffsOn Thursday, Goldman Sachs economists published a report that explains how displacement happens before it appears in unemployment statistics. Occupations highly exposed to AI substitution have seen job openings fall below pre-pandemic levels. Occupations where AI augments workers have seen openings fall more gradually.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.That means that when a company stops posting for customer service or administrative coordinator positions, those jobs do not appear in layoff announcements. They generate no WARN Act filings and no press releases. They disappear because the company simply stops hiring.The worker whose contract ends, whose temp assignment concludes, or whose entry-level role goes unfilled after a colleague leaves is not counted in the unemployment rate. The role simply disappears.What Meta Is Actually DoingMeta’s cuts beginning Wednesday touch teams across Reality Labs, the Facebook social division, recruiting, sales, and global operations. California WARN Act filings confirm cuts at Meta’s Burlingame and Sunnyvale offices, with the majority of the 8,000 positions spread across the company’s global workforce.Mark Zuckerberg has said AI will write four times more code than human engineers at Meta this year. The company is spending between $125 billion and $145 billion on capital expenditures in 2026, most of it on AI infrastructure. Meta is cutting workers to fund systems currently being built to replace the work those workers perform.UnitedHealth Is Now Tracking Whether Workers Use AI Each DayThis past Friday, Bloomberg described what comes just before the cuts at companies still in the adoption phase. UnitedHealth Group is monitoring whether some workers in its Optum division perform at least one AI query per day, using tools such as ChatGPT or Microsoft Copilot. The company has an internal engagement dashboard tracking usage, training completion, and what it calls “adoption gaps.”BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time.When AI use becomes a measurable daily metric, it quickly becomes a performance criterion. The question workers at any large employer should ask is direct: if your company tracks whether you use AI tools often enough, what happens to the workers who use them less? The answer to that question is likely what drives the next round of staffing decisions.In America, Workers Displaced by AI Have Almost No Legal RecourseBloomberg reported last week that the legal framework protecting American workers from AI-driven displacement is thin to the point of nonexistence.There is no federal law requiring companies to disclose that a layoff was caused by AI adoption. State responses range from robot taxes under consideration in New York to skills grants in New Jersey and Utah. Illinois and Oregon are looking into protections for specific occupations.No comprehensive federal framework exists.The contrast with Europe is jarring. The EU AI Act reached a political agreement on May 7. Transparency rules take effect in August 2026.Employers operating across EU member states face mandatory consultation with worker representatives before deploying AI systems with significant employment consequences.American workers facing the same technologies have a patchwork of limited state-level options and nothing equivalent on the federal level.Why the Official Statistics Miss What Workers Are ExperiencingThe Budget Lab at Yale published research on May 7 there is no statistically clear AI-driven effect on unemployment in current federal data, even using methods that compare AI-exposed and unexposed occupations directly. Headline unemployment and layoff rates look stable.So why do employment numbers over all look stable? Workers displaced from AI-exposed roles are often contractors whose assignments end without notice, gig workers whose platforms reduce volume, or employees who accept early-exit packages that do not register as layoffs.The unemployment insurance system counts people who lose W-2 jobs. It was not built to count the structural narrowing of hiring pipelines that Goldman Sachs documented this week.The BLS data, the Goldman Sachs report, the Meta layoffs, and the Yale analysis describe the same economy from four different angles. The headline numbers look stable. The sectors where millions of service and office workers earn their living are contracting.The legal structures that might slow that contraction do not exist in the United States. And companies that have not yet cut are already measuring how often their employees use the tools that will eventually make those cuts possible.Eight thousand people at Meta learn this Wednesday whether they still have jobs. Some how, some way, the employment numbers will remain level, unflinching. Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

A class-action lawsuit filed January 20 in California names Eightfold AI as a defendant and alleges that the company scraped social media profiles, location data, internet activity, and tracking data on over one billion workers without their knowledge.Listen on Apple PodcastsEightfold’s AI then generated “Match Scores” that ranked applicants from zero to five. Lower-ranked candidates were filtered out before any human being ever reviewed their application.The platform is used by Microsoft, PayPal, Morgan Stanley, Salesforce, Starbucks, Chevron, and Bayer. The named plaintiffs, Erin Kistler and Sruti Bhaumik, are both California residents with STEM backgrounds and more than a decade of experience. Neither was ever interviewed.The lawsuit was brought by former Equal Employment Opportunity Commission (EEOC) chair Jenny R. Yang and the nonprofit Towards Justice.The lawsuit does not claim the algorithm was biased. It claims instead the algorithm operated in secret. That distinction matters more than it might appear.Previous AI hiring lawsuits have argued that the algorithm produced discriminatory outcomes. The Eightfold case argues that workers have a right to know an algorithm evaluated them at all — the same transparency right that governs credit scoring under the Fair Credit Reporting Act.If the court accepts that logic, every AI-gated hiring process in the country faces disclosure requirements. The case does not need to win to change industry practice. It needs only to survive long enough to reach discovery.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.The Eightfold lawsuit is not alone. The Mobley v. Workday case, proceeding in California federal court, alleges discrimination through an AI-powered hiring system and is expected to produce the first major ruling on AI hiring vendor liability in 2026.The EEOC filed its own AI hiring discrimination case in January 2025. A Missouri state case against Starbucks over AI-assisted hiring decisions is also pending. Multiple litigation tracks are converging simultaneously, and they are converging around a single underlying question: when an algorithm decides your application never reaches a human, who is accountable for that decision?The legal context gives IBM’s announcement this week a significance that the company’s press coverage has mostly missed. IBM announced plans to triple its U.S. entry-level hiring in 2026. The company described the move as a direct response to the AI transition rather than a reversal of it.IBM’s Chief Human Resources Officer (CHRO) Nickle LaMoreaux said at Charter’s “Leading With AI Summit:” “We are tripling our entry-level hiring, and yes, that is for software developers and all these jobs we’re being told AI can do.”BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time.She added that entry-level jobs from two to three years ago can now largely be performed by AI. She insisted that companies must rewrite every entry-level role to reflect what human workers are actually better at. At IBM, that means junior developers now spend less time on routine coding and more time in direct client engagement and product development.IBM’s reasoning is partly strategic pipeline management. Cutting entry-level hiring today creates a future shortage of mid-level managers. Poaching experienced workers from competitors costs more and integrates more slowly. Younger workers who enter the workforce during an AI transition tend to be more AI-fluent than mid-career workers who built their skills before the tools existed.IBM is betting on building internally rather than buying externally. Dropbox has announced a 25% expansion of its internship and graduate programs on the same logic.So IBM has already confirmed that its HR department shifted from 700 staff to 50 using AI. The 650 displaced workers were described as “freed up” for higher-value work. Actually, the 50 who remained are a different, more specialized population than the 700 who preceded them.The AI/Labor Report is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.IBM’s new entry-level hires will step into roles that have been rewritten around AI oversight and customer interaction. Those roles are not the roles that existed before. They pay differently, require different skills, and serve a different organizational function. AI makers are marketing to a different tune in light of the revelation (to them).The Fortune Workplace Innovation Summit opens in Atlanta next week. Anthropic’s CHRO and the CEO of AI workplace platform Glean are scheduled to present AI agents as teammates rather than replacements.Of course, the final decision as to how to deploy AI lays with corporate executives under pressure from shareholders. Which path do you think they’ll choose: pro-worker or replace-worker? Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Klarna replaced approximately 700 customer service workers in 2024 with AI. Klarna is primarily known for its "buy now, pay later" business model. The company CEO, Sebastian Siemiatkowski, trumpeted through every communications channel (including in-person conferences) the move as evidence that AI could perform at human-equivalent quality.By early 2026, the company reversed course by rehiring staff, with all the effort in interviews, re-training, and on-boarding that entails.Customer satisfaction scores deteriorated on complex service interactions. AI handled volume but not complexity. Edge cases, emotionally charged conversations, and multi-step problem resolution overwhelmed systems trained for routine queries. The cost savings projected at announcement did not materialize.Rehiring costs exceeded the original savings estimate. The story that was supposed to demonstrate AI’s capacity to replace human workers became the clearest illustration of why full replacement strategies fail.The Gartner data released last week provided the statistical frame: 80% of companies that cut workers for AI saw no correlation between workforce reduction and ROI. Klarna turns that statistic into a story. Together they describe a corporate AI labor strategy that is executing at scale while failing at the level of individual firms in measurable and documented ways.The companies that are not reversing course are the ones that never had the option of reversal. Cognizant is preparing to eliminate between 12,000 and 15,000 positions globally under a restructuring initiative called Project Leap, built on the premise that AI-augmented teams can deliver what large legacy workforces once required.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.Over 250,000 of Cognizant’s 357,000 employees are based in India. Average compensation levels make workforce reduction more financially efficient there than in higher-cost geographies.Cognizant’s labor reduction program targets application maintenance, business process outsourcing, and traditional IT support. These are exactly the functions in which automation tools have the most mature capabilities.So while India is expected to absorb the majority of the cuts from AI, Cognizant’s CEO framed the restructuring as moving toward a “broader and shorter pyramid.” Translation: fewer entry-level workers, more AI-augmented specialists.Industry executives are now openly stating what the Cognizant announcement confirms: clients are no longer willing to finance the traditional pyramid staffing model that depends on large cohorts of entry-level service workers.The IT outsourcing model that built India’s technology middle class for over 30 years has run its course. That is, we are seeing the twilight of a sector built on shipping large batches of recent Indian graduates to perform routine services work for Western clients.The European picture adds a longer-horizon frame to what is happening in real time. The German Institute for Employment Research projects that 1.6 million jobs in Germany could be reshaped or lost to AI over the next 15 years.A Carnegie Endowment analysis released in February 2026 warns that the disruption is unlikely to arrive as sudden mass redundancy, though. The more probable mechanism is incremental task substitution that progressively hollows out the scope of existing roles.Jobs would shrink before disappearing to create prolonged insecurity rather than visible unemployment. The same German analysis found women are nearly twice as likely as men to work in a role with high AI exposure.The most useful data point for understanding the week arrives from an unexpected direction. The Yale Budget Lab released new econometric research on May 7 found that the current weakening of the U.S. labor market cannot yet be statistically attributed to AI.BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time.Net payroll growth has run at only about 20,000 jobs per month over the prior year. The unemployment rate has risen from 3.4% in April 2023 to 4.3% in March 2026. Layoffs are low. Hiring is low. Unemployed job seekers are having a particularly difficult time finding work.The Budget Lab concludes “AI seems quite likely to eventually leave its mark on the labor market, even if it has not already.”The U.S. labor market’s net job creation has run near zero since early 2025 while unemployment holds at 4.3%. That is a labor market that is neither growing nor collapsing. It is compressing.The statistical methods that measure unemployment register job loss.They do not register job shrinkage.The AI Labor Report is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.A worker whose role has had 40% of its tasks automated away does not appear in the unemployment data.The gap between what the data currently shows about AI-related job loss and how corporate is reshaping hiring pipelines points in the direction of what will likely com.what is forming inside corporate hiring pipelines is an indication of what will likely come. Klarna’s experience is a prime example of AI “irrational exuberance.”Klarna clearly implemented AI corporate-wide prematurely. Is the rest of the corporate world, globally, intent on following Klarna’s example? Or will AI irrational exuberance unravel the labor markets before before Wall Street understands what’s happening? Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

UC Berkeley found that employees who embraced AI tools most enthusiastically did not work less. They worked more.The research team tracked workers at a 200-person technology firm over eight months, and published their findings in The Harvard Business Review.The AI tools made more work feel doable. So, workers did more.They expanded their to-do lists to fill every hour AI freed up, and then kept going. Lunch breaks disappeared. Evenings shortened.One engineer told researchers: “You had thought that maybe, because you could be more productive with AI, you could save some time and work less. “You just work the same amount or more.”An ActivTrak analysis of 10,584 workers measured what actually happened to time allocation after AI adoption. Time spent across every job responsibility rose between 27% and 346%. Focused work sessions fell 9%.Time spent on email doubled. Researchers at Boston Consulting Group named the resulting condition “AI Brain Fry.” Companies are seeing a pattern of cognitive overload in workers who must supervise multiple AI systems simultaneously. About one in seven workers surveyed reported mental fatigue from juggling AI tools. The workers most affected are the early adopters, the employees companies most want to retain.The UC Berkeley researchers identified that AI expands a worker’s sphere of accountability. It allows one person to take on tasks that previously required three. Organizations register the output gain and quietly raise their expectations for what a single employee can produce.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.The worker does not receive a reduced workload. The worker receives a larger one, denominated in fewer hours, with no additional compensation and no reduction in the performance bar.That is a productivity gain for the company and a sustained increase in cognitive load for the individual. It tends to produce, over time, the conditions that precede burnout.Nevertheless, companies are making workforce decisions based on the assumption that AI-enabled employees will be more productive and that fewer employees will therefore be needed.A Gartner survey of 350 global business executives, though, found that 80% of those companies reported workforce reductions after adopting AI or autonomous technology. All at companies with annual revenues of at least $1 billion.Workforce reduction rates were nearly identical among companies that reported high ROI from AI and companies that reported marginal gains or negative outcomes from AI-use. Cutting workers and keeping AI returns did not correlate.Companies that showed the strongest AI returns were those that used the technology to amplify their existing workforce rather than shrink it.Gartner’s lead analyst, Helen Poitevin, stated the conclusion directly: “Workforce reductions may create budget room, but they do not create return.”Organizations that improved ROI were those that invested aggressively in skills, roles, and operating models that allow workers to guide and scale AI systems — that is, they invested in organizational change management.The companies cutting their way to AI returns are, by Gartner’s data, pursuing a strategy with a poor track record.The Wall Street Journal framed the same tension as a stark CEO choice: lay off workers or make them do more. Most companies have chosen the former.The Gartner data suggests that choice is producing short-term budget relief and limited long-term value. The companies choosing to make workers do more are generating the returns. Those companies are pursuing a so-called “Human Amplification” model.BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time.The companies choosing layoffs are generating headlines.The human cost of the amplification model is visible in the burnout data above.The human cost of the layoff model is visible in labor market data emerging from South Korea. The consequences of AI-driven displacement are measurable in South Korean business in a way that U.S. aggregate statistics have so far obscured.A Bank of Korea analysis finds that 98.6% of the 211,000 jobs lost by workers aged 15 to 29 over the past three years were concentrated in sectors with high AI exposure.Employment in professional services like law, accounting, management consulting, fell 8.8% over the same period. Of the 1,200 people who passed South Korea’s CPA exam last year, only 338 had secured jobs as of October.That is a passage rate for a demanding professional qualification translating into a 28% employment rate for newly credentialed accountants. The shortfall is attributed partly to the rapid adoption of AI tools by accounting firms that now require fewer junior staff to process the same volume of work.South Korea’s data is a leading indicator, not an outlier.The AI Labor Report is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The country has one of the highest robotics densities in the world and an early-adopting professional services sector. What is visible there in employment statistics is likely forming in U.S. and European labor markets in ways that headline unemployment rates do not yet capture.The Gartner finding and the Korean data point in the same direction: AI layoffs are producing budget room. However, they are not producing returns.The workers left behind through layoffs, and those retained, are bearing human costs that company balance sheets do not record.Most Popular Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

The tech sector has shed more than 100,000 workers in 2026 alone, running at roughly 864 job cuts per day as of early May. A separate analysis finds that 275,000 AI jobs sit open while laid-off workers lack the skills to fill them. Customer support, quality assurance, content moderation, and middle management roles are going.Google, Amazon, Microsoft, and Meta collectively plan to spend $725 billion on AI capital expenditures in 2026, a 77% increase over last year’s already-record $410 billion. These four companies are now committing more capital to AI infrastructure than the entire global oil and gas industry spends on exploration.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.Nevertheless, machine learning engineers and AI safety researchers are in short supply. The workers being cut and the workers being hired are two different populations, and the gap between them is widening.Zuckerberg was bald-faced about AI elbowing headcount off the ledger. He told Meta employees that the company’s planned layoffs of roughly 8,000 workers are a direct consequence of its AI infrastructure budget. Meta’s capex now sits at between $125 billion and $145 billion for 2026. Meta’s AI infrastructure budget runs at four to five times what the company spends on its entire human workforce.Meanwhile, new research finds that women make up approximately 86% of the workers most exposed to AI displacement, concentrated in computer programming support, marketing, financial analysis, and customer service roles.The researchers note these workers “may be out of sight and out of mind” for policymakers. The feminization of AI risk is a structural feature of where automation lands first: routine, digital, and heavily female roles that receive far less attention than the aggregate job loss statistics.The roles at highest risk are also the roles that have historically served as the primary economic entry points for women without advanced technical degrees. Automating them closes two doors simultaneously: the job itself and the career ladder it was supposed to start.The human cost of these structural shifts shows up plainly in a Gallup World Poll released today. Only 43% of Americans aged 15 to 34 say it is a good time to find a job locally. Among adults 55 and older, 64% say the same.BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time.That 21-point gap makes the United States one of only five countries among the 141 surveyed where younger people are at least 10 points more pessimistic about work than older people.In every other advanced economy, younger adults are more optimistic than their elders, or the generations hold similar views. The U.S. pattern is, by Gallup’s own assessment, globally unique.The biggest drop in confidence falls among college graduates who have not yet found full-time employment. This is the exact population that AI is squeezing out of the entry-level job market. Gallup’s analyst notes that AI-driven anxiety over entry-level roles likely contributes to the decline.CNN reports that the full picture is more complicated than a straightforward jobs-replaced-by-AI narrative. Companies are automating specific tasks within jobs rather than eliminating entire positions outright. A software engineer’s work now involves more system design and less boilerplate coding. The title may survive even as the entry pathway narrows.The AI Labor Report is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The distinction between the actual work and the title matters for experienced workers already inside companies. For the young graduate standing outside trying to get in, the pathway compression is the entire problem.However, the $725 billion capital reallocation, the Zuckerberg admission, the 86% female displacement risk, and the Gallup generational pessimism gap are all readings of the same underlying shift.CAPITAL IS MOVING AWAY FROM HUMAN LABOR AT A SPEED AND SCALE THAT LABOR MARKETS, TRAINING SYSTEMS, AND SOCIAL SAFETY NETS WERE NOT BUILT TO ABSORB SUDDENLY.The historical parallel that comes to mind is the Enclosure Movement in 16th and 17th century England. Parliament found it in its best interests to enforce a law that saw common land fenced off by large landowners who had determined that sheep farming was more profitable than tenant farming.The Enclosures increased agricultural productivity and made certain landowners and parliamentarians very wealthy. They also displaced a rural working class with no alternative employment and no political voice.The structural logic through economics history is identical: a resource that was previously shared — in our case, knowledge and creative work — is being consolidated by those with capital, and the workers who depended on open access to it are finding the gates closed.What is different today is that the displaced workers are highly educated, living in cities, and connected to each other in real time. The Gallup pessimism data show that young Americans have already registered what is happening, even if the official unemployment statistics have not caught up yet.A generation that was told education was the path to economic security is discovering that the jobs that education was supposed to unlock are the first ones being automated.That is a credibility problem for every institution that made that promise, from universities to employers to the federal government. When credibility gaps of that size open up, they they take far more work to close.The political consequences of that gap are still forming, unfortunately. They will arrive before the retraining programs do.Production: Assistance from 11 Labs Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

The tech sector has shed more than 100,000 workers in 2026 alone, running at roughly 864 job cuts per day as of early May. A separate analysis finds that 275,000 AI jobs sit open while laid-off workers lack the skills to fill them. Customer support, quality assurance, content moderation, and middle management roles are going.Google, Amazon, Microsoft, and Meta collectively plan to spend $725 billion on AI capital expenditures in 2026, a 77% increase over last year’s already-record $410 billion. These four companies are now committing more capital to AI infrastructure than the entire global oil and gas industry spends on exploration.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.Nevertheless, machine learning engineers and AI safety researchers are in short supply. The workers being cut and the workers being hired are two different populations, and the gap between them is widening.Zuckerberg was bald-faced about AI elbowing headcount off the ledger. He told Meta employees that the company’s planned layoffs of roughly 8,000 workers are a direct consequence of its AI infrastructure budget. Meta’s capex now sits at between $125 billion and $145 billion for 2026. Meta’s AI infrastructure budget runs at four to five times what the company spends on its entire human workforce.Meanwhile, new research finds that women make up approximately 86% of the workers most exposed to AI displacement, concentrated in computer programming support, marketing, financial analysis, and customer service roles.The researchers note these workers “may be out of sight and out of mind” for policymakers. The feminization of AI risk is a structural feature of where automation lands first: routine, digital, and heavily female roles that receive far less attention than the aggregate job loss statistics.The roles at highest risk are also the roles that have historically served as the primary economic entry points for women without advanced technical degrees. Automating them closes two doors simultaneously: the job itself and the career ladder it was supposed to start.The human cost of these structural shifts shows up plainly in a Gallup World Poll released today. Only 43% of Americans aged 15 to 34 say it is a good time to find a job locally. Among adults 55 and older, 64% say the same.BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time.That 21-point gap makes the United States one of only five countries among the 141 surveyed where younger people are at least 10 points more pessimistic about work than older people.In every other advanced economy, younger adults are more optimistic than their elders, or the generations hold similar views. The U.S. pattern is, by Gallup’s own assessment, globally unique.The biggest drop in confidence falls among college graduates who have not yet found full-time employment. This is the exact population that AI is squeezing out of the entry-level job market. Gallup’s analyst notes that AI-driven anxiety over entry-level roles likely contributes to the decline.CNN reports that the full picture is more complicated than a straightforward jobs-replaced-by-AI narrative. Companies are automating specific tasks within jobs rather than eliminating entire positions outright. A software engineer’s work now involves more system design and less boilerplate coding. The title may survive even as the entry pathway narrows.The AI Labor Report is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The distinction between the actual work and the title matters for experienced workers already inside companies. For the young graduate standing outside trying to get in, the pathway compression is the entire problem.However, the $725 billion capital reallocation, the Zuckerberg admission, the 86% female displacement risk, and the Gallup generational pessimism gap are all readings of the same underlying shift.CAPITAL IS MOVING AWAY FROM HUMAN LABOR AT A SPEED AND SCALE THAT LABOR MARKETS, TRAINING SYSTEMS, AND SOCIAL SAFETY NETS WERE NOT BUILT TO ABSORB SUDDENLY.The historical parallel that comes to mind is the Enclosure Movement in 16th and 17th century England. Parliament found it in its best interests to enforce a law that saw common land fenced off by large landowners who had determined that sheep farming was more profitable than tenant farming.The Enclosures increased agricultural productivity and made certain landowners and parliamentarians very wealthy. They also displaced a rural working class with no alternative employment and no political voice.The structural logic through economics history is identical: a resource that was previously shared — in our case, knowledge and creative work — is being consolidated by those with capital, and the workers who depended on open access to it are finding the gates closed.What is different today is that the displaced workers are highly educated, living in cities, and connected to each other in real time. The Gallup pessimism data show that young Americans have already registered what is happening, even if the official unemployment statistics have not caught up yet.A generation that was told education was the path to economic security is discovering that the jobs that education was supposed to unlock are the first ones being automated.That is a credibility problem for every institution that made that promise, from universities to employers to the federal government. When credibility gaps of that size open up, they they take far more work to close.The political consequences of that gap are still forming, unfortunately. They will arrive before the retraining programs do.Production: Assistance from 11 Labs Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

The week’s defining story arrived on May 8, when Cloudflare announced it was cutting 1,100 workers — roughly 20% of its workforce — on the same day it reported its best revenue quarter in its 16-year history. The company posted $639.8 million in quarterly revenue, a 34% year-over-year increase. CEO Matthew Prince told investors that internal AI usage had risen more than 600% in three months and that highly productive, AI-augmented employees simply need fewer support staff around them. When an analyst asked why the company needed to cut so deeply during its strongest quarter on record, Prince said: “Just because you’re fit doesn’t mean you can’t get fitter.”So, Cloudflare’s layoffs are a business strategy choice, and an explicit one. The company is converting staff positions into AI infrastructure capability at the moment of maximum financial strength, before any share price pressure forces the decision. Every publicly traded company watching Cloudflare’s stock price on Thursday now has that calculation sitting on its desk.Cloudflare is not alone in this decision. Nearly 38,000 American workers were cut in the first ten days of May, across technology, finance, media, and aviation. PayPal announced plans to eliminate roughly 20% of its 23,800-person workforce over the next two to three years, citing AI adoption and the removal of organizational layers.BILL Holdings said it would cut headcount by up to 30%. Coinbase announced a 14% reduction, framed as a move toward smaller, AI-augmented teams. Challenger, Gray & Christmas reported that AI was the top stated reason for layoffs in April for the second straight month, with employers attributing more than a quarter of all April cuts to AI and automation.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.Upwork, the freelance platform that connects companies to human contract workers, announced a 24% workforce cut the same week. The structural irony is direct. The platform built on human gig work is replacing its own staff with AI while routing more business through automated systems. This is Upwork’s third major workforce reduction in three years.On May 5th, Anthropic launched 10 AI agent templates aimed directly at the daily work of finance professionals. Products cover pitchbook creation, Know Your Customer screening, and month-end close work. The agents are designed to operate inside the software finance teams already use — Excel, Word, Outlook — with context moving automatically between applications. Anthropic described the templates as built for “the most time-consuming work in financial services.”While the framing is accurate, it is also a precise description of what junior analysts are paid to do.While the layoff numbers dominate the headlines, a quieter mechanism is doing comparable damage further down the hiring chain.BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time.Recruiters are retreating to degree and GPA screening as the primary filter for entry-level candidates, specifically because AI-generated résumés have made most applications look identical.A 2025 survey found that 26% of companies were recruiting from a narrow shortlist of schools, up from 17% in 2022. McKinsey has committed to in-person recruiting at just 20 universities and removed language from its career page that previously said “We hire people, not degrees.”The workers hurt by this shift are the same workers already squeezed by the collapse of entry-level hiring — people without elite-school credentials who relied on demonstrated skills and experience to get in the door.The AI Labor Report is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.That door is closing, and Yale researchers published a useful name for the mechanism this month: the “big freeze.” Companies are not firing at unusual rates. They are simply stopping new hiring. Existing employees get more productive with AI tools. Output holds. Headcount requirements shrink. The career ladder that entry-level workers were supposed to climb is being withdrawn from the bottom while appearing, in the aggregate unemployment statistics, to be perfectly intact.Unemployment among recent graduates has climbed to nearly 6%, rising twice as fast as the rest of the workforce since 2022. The headline unemployment rate reads stable. The entry-level labor market reads something else entirely. Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

The headline unemployment rate is 4.3%. Jobless claims hit their lowest level since 1969. By every standard measure, the American labor market is healthy. That is the story the statistics tell. The story underneath them is different.Economists have a term for the current condition: low-hire, low-fire. Truflation’s analysis, published this week, names it more precisely: a frozen labor market. Hiring is suppressed. Firing is suppressed. Quit rates are suppressed. The economy is not in a hiring boom or a recession. It is in a freeze.Also on Apple PodcastsAI does not need to eliminate jobs to damage the labor market. It suppresses hiring by absorbing the codifiable tasks that entry-level and mid-level positions were built around. Companies retain existing staff while letting attrition quietly shrink headcount. The door does not close loudly. It simply stops opening.The Class of 2026 is finding that out this month. Junior-level job postings fell 7% last year. The unemployment rate for recent graduates hit 5.7%, a four-year high. Nine in ten graduates say they are worried AI is closing the entry-level door. One in three say college prepared them to use AI at work. Those two numbers together describe the week’s most personally recognizable story for middle-American families.The organizational logic producing the freeze became visible this week in Coinbase’s layoff announcement. CEO Brian Armstrong cut 700 workers and published one of the most explicit descriptions of AI-native organizational design yet written by a public company executive.The company is eliminating all pure managers, capping management layers at five, and experimenting with one-person teams where a single AI-fluent employee handles what previously required an engineer, a designer, and a product manager.BUY it NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.Armstrong’s description of Coinbase as “an intelligence with humans around the edge aligning it” is the clearest public statement to date of what AI-native organizational design looks like in practice. Meta is running a 50-to-1 employee-to-manager ratio. Microsoft used a formula, age plus years of service equaling 70, to identify which experienced workers to offer buyouts. The design logic is spreading across industries. Workers in coordination, administrative, and management roles should recognize the pattern.The week’s most reported story was the New York Times investigation confirming what The AI Labor Report has argued all year: the people building AI privately believe the disruption will be severe, and their public optimism is shaped by their economic position.Sources inside frontier AI labs told the reporter they expressed “more extreme concern about the labor market impacts of AI in private conversation, but suddenly became optimists once I turned on the mic.” The San Francisco consensus is real. The gap between what the builders know and what they say is not hypocrisy: it’s the logic of the stock markets.BUY it NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time.The rest of the world is responding to that logic with policy.Italy’s Law No. 132/2025 bans fully automated employment decisions and requires employers to consult trade unions before deploying AI in the workplace. China’s Ministry of Human Resources announced an employment stabilization strategy built around AI upskilling and worker transition support.Meanwhile, South Korea’s 2026 National AI Action Plan funds regional AI competency hubs and an Inclusive Labor Transition National Strategy with compensation plans for AI-driven job loss.The AI Labor Report is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.In the United States, at least Connecticut passed worker protection legislation requiring employers to disclose AI’s role in hiring, promotion, and termination decisions. The regulation includes a mandate that WARN notices identify whether AI caused the layoff.The EU, Italy, China, South Korea, and one American state are building frameworks that treat AI displacement as a policy problem requiring a policy response.The United States federal government, though, is working to prevent states from requiring employers to disclose whether AI caused a layoff.The frozen labor market does not fire people. It simply stops letting new ones in. The question for the week ahead is whether the institutions making decisions about the freeze are building systems that protect the people most exposed to it, or systems that protect the people most exposed to accountability for it. Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Graduation season has arrived, and the Class of 2026 is walking into the worst entry-level job market in four years. The unemployment rate for recent college graduates hit 5.7% in the fourth quarter of last year. Junior-level job postings fell 7% in 2025. Indeed’s Director of Economic Research Laura Ullrich confirmed this week that conditions have not improved: “We remain in a low-hire, low-fire environment. I think for the graduates of 2026, they enter a labor market that’s very similar to the one that their peers who graduated last year in 2025 are entering.”Nine in ten graduates say they are worried AI will replace entry-level roles. Only one in three say college is preparing them to use AI in the workplace. That gap between anxiety and preparation is the condition graduates are walking into this month, in cities and towns across the country.Also on Apple PodcastsThe mechanism producing that gap has a name: Economists call it the low-hire, low-fire labor market. A Truflation analysis published today names it more precisely: a frozen labor market. The Bureau of Labor Statistics reports 6.9 million job openings, layoffs unchanged at 1.9 million, and quits stable at 3.2 million. The headline unemployment rate sits at 4.3%. Those numbers look healthy. They are misleading.AI does not need to fire workers to damage the labor market. It suppresses hiring. Companies retain existing staff while letting natural attrition shrink headcount. They do not replace the roles that open up.Entry-level postings fall because AI absorbs the codifiable tasks those roles were built around. Quit rates fall because workers fear what is outside. The result is a labor market that produces stable unemployment statistics and simultaneously closes the door on anyone trying to enter it or move within it.The frozen labor market is the statistical equivalent of the Ghost GDP pattern The AI Report documented in May: growth and stability at the aggregate level, real damage accumulating in the populations the aggregate cannot see.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.The April 2026 Challenger, Gray & Christmas report adds a specific data point to that picture. Job cuts rose 38% from March to April. AI was cited as a factor in a growing share of those announcements. Year-to-date cuts remain down 50% from the same period last year. That combination tells the same story as the unemployment statistics: fewer dramatic layoff events, but a labor market that is quietly contracting at the entry level and the middle while producing no alarm signal in the headline numbers.The most advanced version of that dynamic is already visible in the United Kingdom. Morgan Stanley research shared with Bloomberg finds that UK companies which have used AI for at least a year reported net job losses of around 8% over the past 12 months. That is the steepest decline among comparable economies including the United States, Germany, and Japan. British firms report AI productivity gains estimated above 11%. Those gains have not been matched by job creation. Companies are banking the efficiency as margin.BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time. The UK data is the leading indicator for where the United States is heading. British companies are further along the AI adoption curve. They have restructured around the technology.The result is net job loss, not neutrality, and productivity gains that flow to shareholders rather than to the workforce that generated them.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The Class of 2026 is not graduating into a labor market that is collapsing. The unemployment statistics will confirm that next month. They are graduating into a labor market that has stopped expanding at the level where they were supposed to enter it, for reasons that will not show up clearly in any single data release.The frozen labor market does not fire people. It simply freezes new ones out. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

On Monday, Coinbase CEO Brian Armstrong published one of the most explicit descriptions of AI-driven organizational redesign yet written by a public company executive.The company cut 700 employees, roughly 14% of its workforce, and eliminated all “pure managers” in favor of what Armstrong calls “player-coaches” who manage 15 or more direct reports while doing individual work alongside their teams.The average American manager now oversees 12.1 direct reports, up from 10.9 in 2024. Meta’s new applied engineering team already runs a 50-to-1 employee-to-manager ratio.Also on Apple PodcastsCoinbase is experimenting with one-person teams where a single AI-fluent employee handles what previously required an engineer, a designer, and a product manager. Armstrong wrote that Coinbase is “rebuilding as an intelligence, with humans around the edge aligning it.”So, the Coinbase business design goal is: AI at the center, humans at the edge, and no organizational layer in between that AI can handle itself.The workers most immediately at risk in that design are middle managers and coordination roles. They are also the workers who have no clean path to the human-edges Armstrong describes.A CBS News report published this week catalogues AI-attributed cuts at Pinterest, Dow Chemical, Chegg, Indeed, and Glassdoor alongside the larger announcements at Amazon, Block, and Oracle.BUY NOW! Get the NEW Book that exposes the Narratives Tech uses to build its AI Empire. $4.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required.3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.Oxford Economics director Ben May told CBS that some firms are using AI as “a pretext for job cuts,” describing it as a way to “dress up layoffs as a good news story.” The AI-jobs attribution is running across an oil company, a brewer, a chemical giant, a legal education platform, and a crypto exchange simultaneously.The pattern is not a technology sector story. It is an economy-wide story about what companies say when they restructure.The workers absorbing these cuts are not passive. Forrester Research’s 2026 workforce forecast tracks a segment it calls “coasters,” defined as employees who do not believe their employer deserves their full effort.That group stood at 27% of workers in 2024 and is projected to reach 28% in 2026. The mechanism is documented: workers watch colleagues cut for AI capabilities that have not materialized, see entry-level positions eliminated, and observe offshore arbitrage described as innovation.Forrester finds that only 16% of workers had high AI readiness in 2025. Organizations are cutting staff before training the people who remain. The result is a workforce that is simultaneously smaller, less experienced, and less engaged. No AI deployment compensates for that combination at scale.BUY NOW! Get the book that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for Kindle, Nook, Tablets, and Mobile. No subscription required. 2-hr reading time. The sharpest contrast to all of this comes from East Asia. Governments are working from a fundamentally different premise.A Carnegie Endowment for International Peace analysis published last week documents that South Korea, Japan, China, Taiwan, and Singapore all treat AI primarily as a solution to labor scarcity rather than a source of displacement.Japan anticipates a 3.39 million worker shortfall in AI and robotics by 2040. China’s Ministry of Human Resources announced an employment stabilization strategy built around AI upskilling.Korea’s 2026 National AI Action Plan funds regional competency hubs and an Inclusive Labor Transition National Strategy that includes compensation plans for AI-driven job loss.That policy orientation produced a development reported today by the Korea Times. South Korean labor unions, employers, and government researchers are in active negotiations over what experts are calling a new “survival pact” for the AI era.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The talks center on mandatory retraining rights, stronger safety nets for displaced workers, and ethical guardrails on AI use in hiring and performance evaluation.South Korea has the highest robot density in the world at 1,012 robots per 10,000 workers. Its government chose negotiation over displacement as its primary policy frame.The United States has no comparable federal transition framework.The American equivalent of the Korean survival pact conversation is currently happening in the pages of the New York Times and in Signal chats that executives delete before journalists can read them. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

A New York Times investigation published this week titled “Silicon Valley Is Bracing for a Permanent Underclass” documents something the AI industry has kept carefully managed: the people building these systems hold far bleaker views about what they will do to workers than their public statements suggest.Sources inside frontier AI labs told the reporter, Jasmine Sun, they expressed “more extreme concern about the labor market impacts of AI in private conversation, but suddenly became optimists once I turned on the mic.”Also on Apple PodcastsThe piece names this the San Francisco consensus.” The Consensus is a shared private belief among engineers, venture capitalists, and founders that advanced AI will displace millions of jobs, concentrate wealth in AI companies and capital owners, and produce lasting inequality.Anthropic CEO Dario Amodei has said publicly that AI may create an unemployed or very-low-wage underclass. Sam Altman predicted in 2021 that without aggressive policy action, most people will end up worse off than they are today. These are the optimists. They are the ones willing to speak for attribution.The investigation also documents the institutional mechanism that keeps the public conversation sunnier than the private one. When a veteran lobbyist joined OpenAI’s leadership in April 2024, the company deprioritized research that could produce unflattering findings. OpenAI has excluded public discuss of studies on the gender gap in AI’s labor market effects and on long-run economic forecasting, among others.The company’s messaging shifted toward GDP growth stories. The progressive proposals in OpenAI’s April white paper are real ideas. Nevertheless, the absence of any specific legislation the company has committed to speaks volumes.Get the eBook that exposes the Narratives Tech uses to build its AI Empire. $4.95 SPECIAL SALE PRICE for PDF or ePUB formats; no subscription required. 3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.The people with the clearest understanding of the problem are the people whose economic position makes pessimism about it most costly. For instance, Anthropic’s annualized revenue has surged to $30 billion, driven by Claude Code, an agent that automates knowledge work. The rewards for optimism, in other words, are tremendous; transparence, not so much.Palantir CEO Alex Karp named the underlying concern plainly to a panel audience in March. “The biggest challenge to AI in this country is political unrest. If I were sitting here in private with my peers, I’d be telling them the country could blow up politically and none of us are going to make any money when the country blows up.”Karp frames AI impact as a risk management issue rather than worker protection problem. That’s is precisely what makes the Connecticut legislation passed last Friday so significant.Connecticut’s Senate Bill 5, now the Connecticut Artificial Intelligence Responsibility and Transparency Act, cleared the House 131-17 and the Senate 32-4. Governor Lamont confirmed he will sign it, reversing his position from 2025.The bill requires employers to disclose when AI tools are used in hiring, promotion, discipline, or termination. It amends anti-discrimination law to confirm that deploying an AI tool is not a legal defense against a discrimination claim.Get the eBook that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for PDF or ePUB; no subscription required. 2-hr reading time.The provision with the broadest labor market implications takes effect October 1, 2026. Any employer filing a federal WARN notice in Connecticut must disclose whether the layoffs are related to AI or technological change. The Worker Adjustment and Retraining Notification Act of 1988 is a U.S. labor law that protects employees, their families, and communities by requiring most employers with 100 or more employees to provide notification 60 calendar days in advance of planned closings and mass layoffs of employees.That single requirement could begin to close the measurement gap the AI Labor Report has documented throughout 2026. Connecticut passed its bill by a margin of 131-17.Meanwhile, a federal executive order directs the attorney general to challenge state AI legislation as an obstacle to national policy.The contrast between the State and Federal approaches is sharpest when set against what Italy has already put in place.Italy’s Law No. 132/2025 became fully operational in October 2025. The law bans fully automated employment decisions. Every employment-related decision made with AI input requires meaningful human oversight.Before deploying any AI system in the workplace, employers must consult with trade unions. Workers receive advance disclosure when AI tools are used in hiring and evaluation and retain the right to challenge AI-driven decisions and request human review.Italy is the first EU member state with comprehensive national AI legislation. Its union consultation requirement is the strongest worker protection provision currently in force anywhere in the developed world.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The gap between the Italian framework and the American federal posture is a gap in whose interests the regulatory architecture is designed to serve. Italy requires employers to consult trade unions before deploying AI that affects workers. The United States federal government is working to prevent states from requiring employers to disclose whether AI caused a layoff.The San Francisco consensus says the disruption is coming. The policy question is whether the institutions making decisions about it are building the regulatory infrastructure that protects the people most exposed to the disruption — or the systems that protect the people who are accountable for the AI rollout.Connecticut and Italy chose one answer; The federal government is choosing another. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Glassdoor’s Employee Confidence Index shows that the tech sector recorded the largest year-over-year drop in worker confidence of any industry in March, falling 6.8 percentage points to 47.2%. Less than half of tech workers now express confidence in their employment situation.Glassdoor chief economist Daniel Zhao identified a dynamic that goes beyond the headline number. Fewer workers are quitting, because they fear what is outside the door more than what is inside it. That reluctance to leave creates a paradox that works against the worker.Apple PodcastsWhen natural attrition slows, companies become more aggressive about pushing people out through performance management and structured layoff rounds. Workers are staying put out of fear, and their employers are treating that immobility as an opportunity to cut on the company’s terms rather than the worker’s.The speed of the underlying change helps explain why the confidence collapse is so sharp. Cognizant’s “New Work, New World 2026” report, published this week, reassessed 18,000 tasks across 1,000 occupations and reached a finding that deserves wide attention. The average AI exposure score across all jobs is now 39%. That figure is 30% higher than Cognizant’s own forecast for where exposure would stand in 2032.The technology arrived roughly six years ahead of schedule.The percentage of tasks that AI cannot automate has dropped from 57% in 2023 to 32% today. That is a 25-point shift in approximately two years. The conventional assumption that AI displacement would be a slow-moving story is now contradicted by one of the largest occupational analyses in the field.One specific finding in the Cognizant data should disrupt the dominant narrative about who is at risk. AI exposure in transportation jobs jumped from 6% to 25%. In construction, it rose from 4% to 12%. The assumption that AI is a white-collar problem and physical work is protected is losing its empirical foundation.Get the eBook that exposes the Narratives Tech uses to build its AI Empire. $4.95 SPECIAL SALE PRICE for PDF or ePUB formats; no subscription required. 3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.The people who were told to learn a trade as a hedge against AI displacement are looking at a narrower window than they were promised.The courts are beginning to grapple with what that acceleration means for workers who have already been displaced.An appeals court in China ruled last week that a tech worker’s dismissal was unlawful after his company replaced his role with AI and offered him a reassignment at a 40% pay cut. The worker refused the demotion and was terminated.He won at arbitration; lost the company’s appeal of that decision; and the appellate court finally affirmed: AI adoption does not automatically justify terminating a labor contract or significantly reducing a worker’s compensation.The ruling came from one of China’s leading AI development centers, which gives it weight beyond a single employment dispute. The court’s reasoning is straightforward.A company’s decision to adopt AI is a business strategy. That strategy does not transfer its costs to individual workers through unilateral pay cuts or forced terminations.No court in the United States has yet reached a comparable holding. The Chinese ruling sets a precedent that American labor advocates and policymakers will watch closely.Get the eBook that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for PDF or ePUB; no subscription required. 2-hr reading time.The human stakes of that legal question are most visible at scale in India. A CNBC analysis published this week, drawing on Bernstein research and industry data, documents that India’s top IT firms are downisizing. They hired roughly 170,000 workers in the fiscal year ending March 2026, down from a five-year average of 230,000. Tata Consultancy Services plans to hire only 25,000 fresh graduates this year, against a three-year average of 40,000.Bernstein sent an open letter to India’s Prime Minister Modi warning of a deepening employment crisis. The letter proposed that India’s IT and BPO sector is not just an industry.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.It is the economic foundation of the country’s aspirational middle class, anchoring consumption in real estate, education, and services across dozens of cities. When IT hiring contracts, the effects ripple through the broader economy in ways that employment statistics in the sector alone do not capture.The Glassdoor confidence collapse, the Cognizant acceleration data, the Hangzhou ruling, and the India hiring contraction are four different readings of the same underlying shift. The AI transition is arriving faster than projected. Global institutional responses — in courts, in corporate HR policy, and in national economic strategy — are running behind it.Most Popular AI Labor Report Podcasts Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

A new report from payroll platform Gusto finds that small businesses will hire roughly 974,000 new graduates aged 20 to 24 between April and September. The report defines small businesses as firms with one to 49 employees . The fastest-growing job titles at those firms fall into two categories that sit at opposite ends of the skills spectrum: founding engineers and AI engineers on one side, and field managers and service technicians on the other.Financial analysts and software engineers have seen the sharpest declines in their share of new-grad hiring. The pattern is a labor market splitting along a clear line.AI-native technical roles and jobs requiring physical presence are growing. Generalist white-collar roles are contracting. The reasons for that shift are arriving in waves.Also listen on Apple PodcastsMeta confirmed this week that its first round of layoffs begins May 20, cutting approximately 8,000 employees across every major division of the company, including Facebook social, Reality Labs, recruiting, sales, and global operations.The company is also canceling 6,000 open positions it had planned to fill.The effective reduction is 14,000 positions. A second round of cuts is planned for the second half of the year.The cuts are structural, not performance-based.Meta is reorganizing its teams into AI-focused units. New internal role categories have been created: “AI builder,” “AI pod lead,” and “AI org lead.” Engineers from across the company are being moved into the Applied AI organization. The workers being cut are not underperformers. They are people whose roles no longer fit the organizational design Meta is building around AI.Meta generated $201 billion in revenue in 2025, up 22% year over year. Its 2026 capital expenditure guidance runs as high as $135 billion. The company is not cutting from financial weakness.Instead, it is converting payroll budgets into AI infrastructure budgets, and it is doing so while its stock trades near record levels. For workers, the financial health of their employer provides no protection against structural reorganization.Meta is one data point in a larger pattern, though.Updated tracking from Layoffs.fyi and Nikkei Asia puts the 2026 tech sector total above 95,000 job cuts across 247 layoff events, averaging 882 workers per day. Nearly half of those cuts are attributed to AI or workflow automation. The cumulative total since 2020 is approaching 900,000. The cuts are arriving ahead of the operational justification for them.Get the eBook that exposes the Narratives Tech uses to build its AI Empire. $4.95 SPECIAL SALE PRICE for PDF or ePUB formats; no subscription required. 3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.Cognizant’s chief AI officer told Nikkei Asia this week that real productivity gains from AI are still six to twelve months away for most companies. That gap between the cuts and the demonstrated productivity gains is where the most serious long-term damage is accumulating.A Fortune piece this week, drawing on MIT research, warns that companies eliminating junior roles to extract short-term AI efficiency gains may be destroying their own future leadership pipelines. The mechanism is straightforward.Entry-level positions are where workers develop the tacit knowledge that eventually makes them valuable at senior levels. AI can handle the codifiable tasks those positions require. It cannot transfer the judgment and pattern recognition that come from years of doing the work.Companies that stop hiring junior workers today will face a leadership gap in five years that they cannot quickly or cheaply reverse.Get the eBook that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for PDF or ePUB; no subscription required. 2-hr reading time.IBM reached that conclusion and responded by tripling its entry-level hiring in 2026 against the prevailing industry trend. The question is whether the companies eliminating entry-level positions now are making a short-term efficiency calculation that will cost them more than it saves.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The Gusto hiring data and the MIT warning are two sides of the same problem. The labor market is reorganizing around a rationale that rewards physical presence, AI fluency, and deep domain expertise while compressing the middle.Workers building careers in that middle need to understand the reorganization clearly. The companies making the cuts are counting on the fact that most of them do not. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Nvidia’s VP of Applied Deep Learning Bryan Catanzaro stated publicly that the cost of compute at his company now exceeds the cost of employees. Uber’s CTO told The Information that the company burned through its entire 2026 AI budget on token costs before the year reached its midpoint.The entire justification workers have been given for their displacement is that AI is cheaper and more efficient than people.The workers who lost jobs to that cost assumption have no mechanism for recourse while the economics get worked out.Amazon made the most consequential single announcement of the week for middle-American workers. The company launched Connect Talent, an agentic AI system that conducts voice job interviews around the clock, scores candidates on competency, and prepares recruiter notes entirely without human intervention. Amazon built the system to handle 250,000 seasonal hires.It is now selling that system to retailers, manufacturers, logistics operators, and hospitality companies. The human job interview is now an optional feature. The human recruiter is the first professional role Amazon has automated and packaged for sale at scale to the industries where most middle-American service workers are employed.Also listen on Apple PodcastsThe macro picture around those two stories is built on a set of numbers that do not fit together easily. The BEA reported Q1 2026 GDP growth of 2.0%. Jobless claims dropped to 189,000, the lowest level since 1969. Corporate earnings across the Magnificent Seven were strong.Also, the same quarter produced the largest single-week cluster of AI-attributed layoff announcements in corporate history, with 92,000 tech workers cut so far in 2026 and nearly half of those cuts attributed to AI.The economy is growing. Workers are being cut. The headline statistics look healthy because the workers absorbing the displacement are contractors, gig workers, and early-exit buyout takers — populations the unemployment system was never designed to count.Get the eBook that exposes the Narratives Tech uses to build its AI Empire. $4.95 SPECIAL SALE PRICE for PDF or ePUB formats; no subscription required. 3.5-hr reading time.Available on GumroadThe people building artificial intelligence did not invent their ideas. They inherited them.The Citrini Research bit of speculative fiction that moved markets in February called this “Ghost GDP”: growth that shows up in national accounts but never circulates through the people who used to earn it. This week’s data made that speculative scenario visible in actual earnings filings and government statistics, simultaneously.Meanwhile, Anthropic’s March 2026 labor market research measured actual AI task coverage in real workplace deployments. Computer programmers show 74.5% observed task coverage. Customer service representatives are at 70.1%. The most exposed workers are more likely to be female, over 40, more educated, and better compensated.The entire “get a degree and move into knowledge work” strategy a generation of middle-American workers followed is contradicted by the actual usage data from the largest AI deployment in the world.Regardless, workers using AI daily are producing more output and losing underlying competency. A January 2025 controlled study found that participants who received AI assistance during training performed substantially worse on subsequent independent assessments.Senior workers who built expertise before AI became ubiquitous can use AI as an augmentation layer because they understand their domain well enough to evaluate its output.Get the eBook that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for PDF or ePUB; no subscription required. 2-hr reading time.Junior workers building careers on top of AI from day one are building on a foundation they have never been required to develop independently.What the week’s stories mean togetherThree trends are now running simultaneously and reinforcing each other: The first is that AI costs more than projected, organizational cuts are made in anticipation of savings that have not yet arrived, and workers bear the cost of that gap.Further, the measurement architecture — unemployment claims, GDP, monthly jobs reports — was built for a workforce that no longer describes the majority of American workers. The contractor economy absorbs displacement in silence.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.And then, the workers most at risk are precisely the workers who followed the advice they were given: get educated, move into knowledge work, build credentials.More practical advise would be: do what AI cannot do for at least a generation into the future. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

A Substack finance writer at Citrini Research published a speculative essay in February framed as a dispatch written from June 2028. It described an economy where aggressive AI adoption initially drove record corporate profits but ultimately hollowed out the American consumer base. The mechanism was what the author called “Ghost GDP”: economic output inflated by AI productivity that never circulates through the real economy, because machines spend nothing on discretionary goods.The essay was speculative fiction. It was also the most widely read piece of financial writing this year, and the reason it resonated is visible in this week’s data.The companies that reported earnings this week posted strong results. Meta raised its full-year AI capital expenditure guidance to between $125 and $145 billion while confirming 8,000 layoffs beginning May 20. The Bureau of Economic Analysis (BEA) advance estimate released Thursday shows the economy grew at an annualized rate of 2.0% in Q1 2026, a meaningful rebound from Q4 2025’s weak 0.5% expansion.Also listen on Apple PodcastsA significant driver of the growth was from construction of data warehouses.The economy is growing. Corporate profits are strong. And the same quarter produced the largest single-week cluster of major AI-attributed layoff announcements in corporate history.The Ghost GDP speculation describes something real: the gap between aggregate economic growth and the experience of workers inside that growth. The GDP number does not contradict the job displacement story. It sharpens it.Growth driven by AI infrastructure investment and productivity gains flowing to shareholders does not automatically reach the worker whose coordination role just became unnecessary.Get the eBook that exposes the Narratives Tech uses to build its AI Empire. $4.95 SPECIAL SALE PRICE for PDF or ePUB formats; no subscription required. 3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.That gap is precisely what economist Claudia Sahm has been warning about for months. Sahm, the inventor of the Sahm Rule recession indicator, describes three forces converging on the same population in the same quarter: AI displacement of white-collar roles; federal workforce reductions under DOGE; and broader economic uncertainty suppressing private-sector hiring.Federal workers pushed into early retirement or layoffs are now competing for private-sector jobs in a market where white-collar hiring has been contracting on net for three consecutive years.Both forces are hitting educated professionals with credentials who assumed knowledge work was structurally protected.Sahm does not describe this as a crisis that has fully arrived. She describes it as a convergence that 2026 could make visible in the labor data for the first time. The GDP growth number makes that convergence harder to see, not easier. A 2.0% growth rate absorbs a great deal of localized professional pain without registering it.The jobless claims number released Thursday morning makes the same point from a different direction. Initial claims dropped to 189,000, the lowest level since 1969. Economists had forecast 212,000.Claims, though, count W2 employees who lose jobs and file for benefits. The job displacement wave documented this week in The AI Labor Report runs significantly through channels that claims data cannot reach: contractors whose engagements end quietly, entry-level positions that go unfilled rather than eliminated, freelancers whose work volume compresses without a termination, and senior workers who accept a voluntary buyout and exit on their own terms.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Meta’s 8,000 layoffs begin May 20. Those workers have not filed claims yet.GDP growth, jobless claims, and Big Tech earnings all look reassuring in isolation. Together, they describe an economy that is producing growth and cutting workers at the same time, in a way that the standard measurement architecture was not designed to capture.That is not a contradiction.The Ghost GDP essay was fiction. The economic dynamic it described is documented in this week’s data releases, across four separate government and corporate sources, on the same Thursday morning.Audio Production: Eleven Labs Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Anthropic’s March 2026 research report, Labor Market Impacts of AI: A New Measure and Early Evidence, is the first major analysis of AI’s workforce effects built on actual usage data rather than theoretical projections.Previous studies estimated AI’s labor impact by asking what AI could theoretically do. Anthropic’s researchers asked a different question: what is AI actually doing in professional settings right now?Also listen on Apple PodcastsThey combined occupational task data, capability estimates from prior research, and real usage data from Claude deployments across enterprise environments. The result is a metric they call “observed exposure” — a measure of how much of a job’s actual task load AI is already handling today.Computer programmers show 74.5% observed task coverage. Customer service representatives follow at 70.1%. Data entry operators are at 67.1%. The data are measurements of what AI is doing right now in real workplaces, on real Tuesday afternoons, for real employers.The report documents an early labor market signal that has not yet appeared in unemployment statistics. The unemployment rate for workers in highly exposed occupations shows no spike since ChatGPT’s launch in late 2022.The hiring rate for workers aged 22 to 25 entering those same occupations has slowed by approximately 14%. The signal is appearing in hiring before it appears in unemployment. Workers are not being fired at unusual rates.Get the eBook that exposes the Narratives Tech uses to build its AI Empire. $4.95 SPECIAL SALE PRICE for PDF or ePUB formats; no subscription required. 3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.They are simply not being replaced when they leave, and the entry-level pipeline is quietly closing.The Yale Budget Lab’s April 2026 update, which incorporates Anthropic’s February usage data, reaches a consistent conclusion.Occupational patterns remain within historical ranges.Unemployed workers are in occupations with roughly 25 to 35 percent AI task exposure; the same share as employed workers. The aggregate unemployment statistics show no AI displacement signal yet.In other words,the labor market headline numbers are stable.Both observations are true simultaneously: The aggregate statistics show stability; the corporate earnings calls last night offered something else entirely.Meta raised its full-year AI capital expenditure guidance to $125 to $145 billion on the same call where it confirmed 8,000 layoffs beginning May 20. The company’s earnings announcement cited “higher component pricing” as a primary driver of that upward revision — a direct reference to tariff-driven hardware cost increases.Alphabet, Microsoft, Meta, and Amazon are collectively spending close to $700 billion on AI infrastructure this year. Each of those companies confirmed last night, on earnings calls, on the record, to Wall Street analysts, that the spending and the cutting are two sides of the same strategic decision.Workers are being cut to fund infrastructure that is itself getting more expensive because of trade policy.Get the eBook that examines how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for PDF or ePUB; no subscription required. 2-hr reading time.The Anthropic report’s most counterintuitive finding ties all of this together. The workers with zero observed AI exposure in the data include cooks, motorcycle mechanics, lifeguards, bartenders, and dishwashers.The workers with the highest exposure are educated, experienced, and well-compensated knowledge workers. The most exposed group is more likely to be female, over 40, more educated, and better paid than the zero-exposure group.The entire “AI will take blue-collar jobs first” manufacturing narrative is contradicted by the actual usage data from the largest AI deployment in the world.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The practical implication for middle-American service workers is that the people ahead of them in the layoff queue are the white-collar professionals they were told to aspire to become.The aggregate unemployment statistics are stable. The hiring pipeline for young workers is narrowing. The companies doing the cutting are raising their AI spending guidance on the same earnings calls. And the workers most exposed are the ones nobody expected.It’s all part of the same story. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Amazon announced a product today that makes the direction of AI and hiring about as explicit as it has ever been stated in public. Amazon hired roughly 250,000 seasonal workers last year with humans in the loop. This year will be different.The company launched Connect Talent, an agentic AI system that conducts voice job interviews around the clock, scores candidates on skills, and prepares recruiter notes.All without without human intervention.Names and resumes are stripped from the process. Recruiters receive anonymized competency scores and transcripts. The face-to-face job interview is now an optional feature.Also listen on Apple PodcastsThe company is now packaging the system to sell to retailers, manufacturers, logistics operators, and hospitality companies — every industry that hires large numbers of workers at once.The human recruiter is the first professional role Amazon has fully automated and then offered for sale at scale to other industries. The product is live today.The announcement arrives on the same morning that a more uncomfortable AI economics story is breaking across the business press.Axios reported that Nvidia’s VP of Applied Deep Learning, Bryan Catanzaro, told reporters that the cost of compute for his team now exceeds the cost of employees. The company whose chips power most of the AI economy.Uber’s CTO told The Information that the company burned through its entire 2026 AI budget on token costs before the year reached its midpoint. The culprit was coding tools.Get the eBook of the Substack series that dissects the narratives Tech uses to build its AI Empire. $4.95 SPECIAL SALE PRICE for PDF or ePUB formats; no subscription required. 3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.The assumption behind most AI-driven workforce reduction has been that software is cheaper than people. That assumption is now under direct pressure from the people inside the industry who know the costs best.Human payroll is a fixed and predictable expense. AI costs, though, scale with usage. Every query, every agent action, and every model call generates an invoice. Companies that made permanent workforce decisions based on projected AI cost savings are discovering that the operational math is more complicated than the original pitch.An AI and finance professor at the Swiss Institute of Artificial Intelligence told Fortune the situation reflects a “short-term mismatch” between current compute costs and the productivity gains companies projected when they made those cuts. The workers who lost their jobs to that mismatch have no mechanism for recourse while the labor market responds to economic realities.The economic context around all of this shifted this morning. The Bureau of Economic Analysis released its advance estimate for Q1 2026: U.S. GDP contracted 0.3%. *Into that landscape steps a story that has received less attention than it deserves. Fortune today profiles Clara Shih, the former head of AI at both Meta and Salesforce.She describes watching AI agents outperform her top human workers on measurable tasks in real enterprise settings. She describes the experience as having “radicalized” her.Get the eBook compilation of Substack articles examining how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for PDF or ePUB; no subscription required. 2-hr reading time.She has since left corporate AI work and built a nonprofit aimed at helping Gen Z workers find jobs before those jobs disappear.Shih’s account matters because was a senior executive describing what she saw inside two of the largest technology companies in the world: AI agents beating experienced human workers on real work products in direct comparisons.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The pattern running through today’s news is that AI technology is advancing faster than anyone — including its builders, investors, employers, and workers — had planned for.*CORRECTION: The BEA's advance estimate released Thursday, April 29, 2026 actually shows the economy grew at an annualized rate of 2.0% in Q1 2026, rebounding from Q4 2025's weak 0.5% expansion, due mostly to investment in data center construction. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

The most revealing number in the technology industry this week came from Google CEO Sundar Pichai. He disclosed at Google Cloud Next 2026 that 75% of all new code at Google is now AI-generated and reviewed by human engineers. The figure was 50% last fall and 25% in October 2024. That trajectory — a tripling in eighteen months — matters more than the number itself.Google engineers are no longer prompting AI to help them write code. They are directing autonomous AI agents that plan, generate, test, and iterate across entire projects.Pichai described a complex code migration that agents and engineers completed together six times faster than the same work would have taken a year ago with engineers alone. Google has also tied AI adoption goals to engineer performance reviews. Using these tools has become a job requirement.The direct question for every software professional reading this: if the world’s largest engineering organization no longer needs engineers to write most of its code, what does it need them for — and how many of them does it need?Get the eBook of the Substack series that dissects the narratives Tech uses to build its AI Empire. $9.95 flat fee for PDF or ePUB formats; no subscription required. 3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.The Google disclosure lands alongside a body of research that is now documenting a quieter and more insidious workplace transformation. Researchers and employers have given it a name: AI deskilling.The pattern is consistent across software engineering, financial analysis, legal research, and medical diagnostics. Workers who rely on AI for core job functions produce more output in less time. Their productivity metrics look strong. Underneath those metrics, their ability to perform the same functions independently is deteriorating.A January 2025 study found that participants who received AI help during training performed substantially worse on subsequent independent assessments than those who worked through tasks without assistance. The AI completed the task. The worker never learned how to do it.A Microsoft Research controlled experiment found that developers using GitHub Copilot completed coding tasks 55.8% faster. A separate Microsoft and Carnegie Mellon study of 319 knowledge workers found that AI tool use reduces critical engagement and raises concerns about long-term reliance and diminished independent problem-solving.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Andrea Olson, writing in Inc. Magazine, frames the structural problem clearly: productivity dashboards stay green while the foundation erodes. The dashboards track output. They do not track whether a financial analyst still understands the assumptions behind the model AI just built for her. They do not flag that a junior lawyer can no longer construct a legal argument from scratch because he has been reviewing AI-generated briefs for two years.Senior workers who built deep expertise before AI tools became ubiquitous retain that knowledge for now. They can use AI as a genuine augmentation layer because they understand their domain well enough to evaluate, correct, and direct AI output.Junior workers are building their careers on top of AI from day one. Controlled studies suggest many are building on sand. When the tools change, workers without underlying domain expertise will find themselves stranded.Also listen on Apple PodcastsThe deskilling problem connects directly to a structural shift in how AI companies are now selling their products. A 2026 industry analysis documents the emergence of what analysts are calling vertical AI: companies selling the outcome of labor rather than tools to help humans work.Insurance, legal, logistics, and healthcare administration are the primary target sectors. The AI coding tools market alone reached $12.8 billion in 2026 revenue, more than double the $5.1 billion generated in 2024.So, the dollar amount a company previously paid a human worker becomes the revenue target for a vertical AI startup. The labor budget becomes a software subscription.MIT Technology Review’s roundup of the ten most consequential AI trends of 2026 identifies something the displacement data alone cannot capture: a global backlash is building.Get the eBook compilation of Substack articles examining how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for PDF or ePUB; no subscription required. 2-hr reading time.Labor unions, artists, conservative legislators, and progressive activists are converging on AI regulation from different directions and for different reasons. Small regulatory wins are accumulating.Connecticut passed worker-protection legislation this month. Colorado’s AI law takes effect in June. The federal government has produced a framework with no binding obligations, and states are filling the vacuum.The backlash is the political story running underneath all the economic data. Workers are sensing displacement before the aggregate statistics confirm it.A Mercer survey of 12,000 workers and executives globally found that concern about AI-driven job loss rose to 40% in 2026, up from 28% in 2024. Ipsos data on U.S. public opinion finds that almost three in four Americans believe the government should act to prevent AI-induced job losses.The gap between that sentiment and the current state of federal policy is the space where the next few years of labor politics will be challenged. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Microsoft has done something in its 51-year history that it has never done before: offered its own employees a buyout to leave.The company announced last Thursday that roughly 8,750 U.S. workers — about 7% of its American workforce — are eligible for a voluntary retirement program. The offer targets employees at or below the senior director level whose combined age and years of service add up to 70 or higher. Eligible workers and their managers will receive details on May 7.The formula has a name now: the Rule of 70. It targets mid-to-late career employees, often the people who carry the most institutional knowledge in a company. In most previous periods of technological transition, that knowledge was precisely the thing that protected those workers. In an environment where AI systems can process decades of documentation in seconds, that protection is dissolving.Get the eBook of the Substack series that dissects the narratives Tech uses to build its AI Empire. $9.95 flat fee for PDF or ePUB formats; no subscription required. 3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.The program is voluntary, which gives Microsoft legal and reputational cover that a direct layoff round would not. It is also, by the analysis of several HR observers, the most efficient way to reduce a high-salary workforce without age-discrimination exposure. Other large employers are almost certain to follow the same template.The Microsoft buyout is the most visible single story of the past week. The broader numbers behind it are larger and grimmer. According to data tracked by Layoffs.fyi, over 92,000 tech workers have been laid off so far in 2026. The cumulative total since 2020 stands at nearly 900,000.Of the 78,557 tech cuts recorded from January through early April, 47.9% have been attributed to reduced need for human workers because of AI and workflow automation, according to Nikkei Asia’s tracking.Cognizant’s chief AI officer told Nikkei that real productivity gains from AI are still six months to a year away for most companies. The cuts are arriving ahead of the operational justification for them.Get the eBook compilation of Substack articles examining how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for PDF or ePUB; no subscription required. 2-hr reading time.That gap between the cuts and the demonstrated productivity gains shows up most visibly at the entry level. The Stanford 2026 AI Index found that employment among software developers aged 22 to 25 has fallen nearly 20% since 2024, even as older colleagues’ headcount continues to grow. The same pattern is appearing in customer service and other AI-exposed occupations.The mechanism for the disruption is straightforward. AI now handles the codifiable tasks that entry-level jobs were built around: drafting standard documents, running routine analysis, producing basic reports.Employers are retaining experienced workers and letting AI absorb the on-ramp that younger workers used to climb. The headline unemployment rate holds steady. The entry-level job market is contracting.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The Stanford data adds precision to something The AI Labor Report has tracked all year: the career ladder is being pulled up from the bottom, and the official statistics are not built to show it.Workers in companies that have already adopted AI are absorbing this reality in real time. A new Gallup survey of 23,717 U.S. employees found that 23% of workers in AI-adopting organizations say it is very or somewhat likely their job will be eliminated within the next five years due to AI or automation. Among all U.S. workers, that share is 18%.Gallup also found that 27% of employees in AI-adopting organizations say their workplace has changed in disruptive ways over the past year, compared to 17% in organizations that have yet to adopt AI. The disruption is real and measurable.So is the productivity improvement: 65% of workers in AI-adopting organizations say AI has improved their efficiency.The combination of higher disruption and higher productivity in the same organizations is the central tension of the current moment. The companies that are furthest along in AI adoption are producing more output per worker and cutting workers at the same time.The workers who remain are doing more. The workers who leave are being converted into infrastructure budgets.The Microsoft Rule of 70, the 92,000 layoffs, the collapsing entry-level hiring pipeline, and the Gallup anxiety numbers are all expressions of the same underlying pattern: AI is raising the output ceiling while narrowing the floor for who gets to stand on it. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Meta is logging employee keystrokes, mouse movements, and periodic screen snapshots to train AI agents, the company confirmed to staff in internal memos first reported by Reuters this week. The program is called the Model Capability Initiative.It runs on a list of work-related apps and websites and captures screen content for context. Meta’s stated purpose is to improve AI performance on specific tasks where models still struggle, such as navigating dropdown menus and using keyboard shortcuts.Also listen on Apple PodcastsMeanwhile, Meta is preparing to cut as much as 20 percent of its workforce, with the first layoffs reportedly set to begin in May. Workers are being recorded doing their jobs in order to teach systems the work those same workers currently perform.The company has committed up to $135 billion in capital expenditure for 2026, most of it directed toward AI. The workers generating the training data are not receiving additional compensation for it. There is no reported opt-out mechanism.Every office worker reading this should ask one question: is my employer doing this too?The scale of what employers are planning clarifies why that question matters. A working paper published by the National Bureau of Economic Research, drawing on a survey of nearly 750 corporate executives conducted with Duke University and the Federal Reserve Banks of Atlanta and Richmond, projects AI-driven job cuts in 2026 at approximately 502,000 roles. The 2025 figure was roughly 55,000. The projected 2026 number is nine times higher.Get the eBook of the Substack series that dissects the narratives Tech uses to build its AI Empire. $9.95 flat fee for PDF or ePUB formats; no subscription required. 3.5-hr reading time.The people building artificial intelligence did not invent their ideas. They inherited them.The researchers also document what they call a productivity paradox: executives perceive AI’s productivity gains as larger than the data actually shows. Companies are cutting based on expectations that have not yet materialized in their revenue figures.That gap between expectation and reality shapes the bind workers currently face. A survey of 2,400 knowledge workers across the U.S., the U.K., and Europe — conducted by enterprise AI firm Writer and research firm Workplace Intelligence — found that 29 percent of employees admit to actively sabotaging their company’s AI rollout. Among Gen Z workers, that figure rises to 44 percent.The most common reasons cited are fear of job loss and frustration with tools that do not work as promised. The sabotage takes forms ranging from refusing to use approved tools to entering proprietary information into public AI platforms without authorization.However, workers who resist AI adoption face termination risk: 60 percent of executives surveyed said they are considering cutting employees who refuse to adopt AI tools.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Workers who embrace the tools and demonstrate their capabilities face a different risk — they may be accelerating their own replacement. Seventy-seven percent of executives said workers who remain AI-resistant will be excluded from promotions and leadership consideration.The person building the technology making the most widespread use of it has his own assessment of where this leads. Anthropic CEO Dario Amodei warned at Davos in January 2026 that AI’s reach across cognitive work is categorically different from earlier automation waves.Factory workers displaced by industrial automation could, in theory, move into service or office roles. If AI is moving into office roles simultaneously, Amodei argued, the adjacent sector that absorbed earlier displacement does not exist. “The technology is not replacing a single job,” he said, “but acting as a general labor substitute for humans.”So, one of the people most responsible for building the technology is the one making the case that the safety valve is gone.Get the eBook compilation of Substack articles examining how the AI invasion already happened. You just weren’t invited. $9.95 flat fee for PDF or ePUB; no subscription required. 2-hr reading time.Comments Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

The Connecticut Senate passed Senate Bill 5 on Tuesday by a vote of 32 to 4. The bill requires employers to notify workers when AI is used in hiring, promotion, or termination decisions.It prohibits employers from deploying AI tools that produce discriminatory outcomes. It funds an AI literacy program for workers and small businesses and creates a state regulatory sandbox where companies can test new AI tools under oversight.The bill’s sponsor, Senator James Maroney, was direct about the federal vacuum it fills: “We can no longer wait for DC to act.” The bill now moves to the House before a May 6 deadline.Also listen on Apple PodcastsHere’s why the timing matters: The White House published a “National AI Legislative Framework” in March calling for a unified federal approach to AI regulation. The document contains no binding obligations on employers. It signals that the administration wants to preempt state laws while producing no federal replacement.Connecticut’s Senate passed its worker protection bill two days after that framework circulated widely. The collision between a federal preemption posture and accelerating state legislation is now the central regulatory story in AI and employment.Workers in Connecticut may know by May 6 whether their employer must tell them an algorithm screened them out. Workers in most other states have no such right.The urgency behind Connecticut’s bill becomes clearer when set against what is happening to the managers who are supposed to be implementing AI at the team level.Fortune reported on April 7, drawing on Bureau of Labor Statistics data, that the average American manager now oversees 12 direct reports. That figure has nearly doubled since Gallup began tracking it in 2013.Companies have spent three years gutting middle management and leaving whoever survives with a dramatically larger portfolio of people. Gartner found that 75% of HR leaders believe managers are already overwhelmed by their expanding responsibilities.Yesterday’s AI Labor Report established that workers are 8.7 times more likely to say AI has transformed their work when their direct manager actively supports adoption. The managers capable of driving that transformation are being eliminated or buried under workloads that make mentorship and coaching impossible.A Harvard Business Review piece published this month, co-authored by Wharton researchers, puts a name on the resulting organizational failure. Senior executives experience AI as a strategic advantage. Middle managers confront its actual failures inside real workflows, under real constraints, without adequate support or time.AI initiatives stall because the people charged with making them work see a fundamentally different reality than the people who approved the budget.The Wharton authors are direct: companies are treating AI adoption as a top-down mandate and skipping the operational burden in the middle. The result is billions in investment producing the outcome Gallup The AI Labor Report discussed this week — widespread individual use, almost no organizational transformation.Into that gap steps Jack Dorsey. In a post published April 1 with Block’s lead independent director Roelof Botha,Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Dorsey argued that AI should replace middle management entirely.The post describes AI handling coordination, task assignment, project tracking, and real-time business insights — the core functions that management layers have historically performed.Block cut 40% of its workforce before publishing the piece. Dorsey’s post is one of the first explicit executive statements treating middle management elimination as an organizational design goal rather than an unfortunate side effect of restructuring.The three stories are connected.The managers who would implement AI humanely are being removed.The executives who remain are treating AI as a mandate from above.The workers who bear the cost of both decisions are now waiting to see whether state legislatures will step in with the transparency and protections that the federal government has declined to provide.So the AI deployment battleground narrows from ructions between labor-and-industry to workers-and-management.Check out the Future Forwarded Collections of its most popular Substack series. Each collection is $9.95 flat fee, in PDF or ePUB formats. No subscription required. Each collection takes about two- to three-hours to read. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Gallup’s latest workforce survey, published this week, cited that half of all U.S. workers now use AI at work.Meanwhile, only 12% of workers say AI has fundamentally transformed how their organization actually operates. Workers are using AI tools individually, for their own tasks, in their own workflows.Their employers have not figured out how to translate that individual use into organizational change. A separate survey of nearly 6,000 executives by the National Bureau of Economic Research found that 89% report no measurable effect of AI on their company’s labor productivity over the past three years.Gallup’s own analysis points to the reason. Employees are 8.7 times more likely to say AI has genuinely changed how their work gets done when their direct manager actively supports and champions AI adoption.The barrier is managerial. Manager engagement in the U.S. has fallen from 31% in 2022 to 22% in 2025. The people structurally positioned to drive AI adoption at the team level are the most disengaged group in the American workforce.The gap between adoption and transformation matters because it shapes who bears the cost of AI’s disruption and who captures its gains. The workers absorbing the most pressure right now are young workers trying to enter the labor market.Anthropic’s own research team published findings in March showing that hiring into AI-exposed jobs fell 14% for workers aged 22 to 25 since ChatGPT’s release in late 2022. Unemployment for that group is flat.The hiring door is simply closing. Young workers are being excluded from the front end of the career ladder at precisely the moment when AI is absorbing the entry-level tasks those jobs used to require.The emotional response to that exclusion is showing up in data. A Gallup survey released April 9, conducted for the Walton Family Foundation, found that 31% of Gen Z workers now report outright anger toward AI, up from 22% a year ago.Excitement fell 14 points. Hopefulness fell 9 points.Weekly AI use among Gen Z (those born from 1997 to 2012) grew only 4 points over the past year, well below the pace of prior years. The generation widely described as AI’s natural beneficiaries and most fluent early adopters is turning against the technology. The reason is straightforward.They are watching it close the doors they expected to walk through.The Stanford 2026 AI Index, released April 13, documents what is opening on the other side of those closed doors.Demand for “Agentic AI” skills in U.S. job postings jumped 280% in a single year. These are skills related to managing and directing autonomous AI systems, not simply using AI tools.AI skills now appear in 2.5% of all U.S. job postings, up 55% from the prior year. That hiring is concentrated in California, Texas, and New York. Singapore leads globally at 4.7% of postings.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The Stanford data also captures a broader divide that runs through all of this. Among AI experts, 73% expect AI to have a positive impact on how people do their jobs. Among the general public, only 23% agree.That 50-point gap appears consistently across the economy and healthcare as well. The U.S. recorded the lowest trust in its own government to regulate AI of any country surveyed, at 31%.So, 73% of experts expect AI to improve how people do their jobs; 31% of the people those jobs were supposed to belong to are angry.The gap between techie expectations and worker realities demarcates the battleground for the next great political fight between labor and industry.A compilation of the Substack articles examining how the invasion already happened. You just weren’t invited. $9.95 flat fee for the bundle (PDF, ePUB), no subscription required. 2-hr reading time. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

On the morning of March 31, 2026, tens of thousands of Oracle employees opened their email to find a five-line message from “Oracle Leadership.” It told them their role had been eliminated and that today was their last working day. System access cut off within minutes.No call from a manager. No meeting with HR. Just a brief email and a locked screen.The story spread across Reddit, LinkedIn, and Blind within hours, as roughly 30,000 employees globally — about 12,000 of them in India — tried to make sense of what had just happened. The specific detail that traveled furthest was the lockout itself.Workers described finishing their morning coffee and finding themselves locked out of the tools they had used that morning.For anyone who has ever held a job and worried about losing it, that detail feels different than reading a headcount number.It seems Oracle borrowed $58 billion in new debt over two months to fund data center construction for AI clients, including OpenAI, Meta, and Nvidia. The layoffs are expected to free up $8 to $10 billion in cash flow, according to TD Cowen analysts.Oracle is not cutting because AI made those workers redundant today. Oracle is cutting because it took on massive debt and needed the payroll budget to service it. The workers are not being replaced by machines. They are being converted into debt payments.Underneath the headline numbers, a Brookings Institution study published in January draws a distinction that most AI coverage misses entirely.An important aspect of the the study is the concept of “AI exposure:” How much of your job AI can technically perform. The study relates AI exposure to “adaptive capacity:” a person’s actual ability to find new work if they lose theirs.Most of the 37 million highly exposed U.S. workers have reasonable adaptive capacity. They have savings, transferable skills, and labor markets dense enough to absorb a transition. But 6.1 million workers have high exposure and low adaptive capacity simultaneously. Those workers are primarily in clerical and administrative roles. They are secretaries, HR clerks, medical assistants, and tax preparers. Roughly 86 percent of them are women.They tend to be older, have limited savings, and live in smaller labor markets in the Western Rocky Mountain states and Midwest where retraining options are thin.A follow-up Brookings analysis published last week sharpens the picture further. Of the workers with both high exposure and low adaptive capacity, 67 percent are: workers who built their skills through trade, military service, or on-the-job experience rather than a four-year degree. These are workers who used entry-level and mid-level positions as rungs on a ladder toward economic stability.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.AI is not just threatening their current jobs. It is eliminating the pathway itself. The routes that allowed a skilled worker without a college degree to move up through an organization are narrowing precisely as the jobs at the bottom of those routes disappear.The population most at risk, in other words, is older women in administrative roles in smaller American cities who built their careers through experience rather than credentials.That is a specific, recognizable group of people. They are the workers least equipped to absorb the cost and least visible in the aggregate statistics that currently show a stable labor market.A compilation of the Substack articles examining how the invasion already happened. You just weren’t invited. $9.95 flat fee for the bundle (PDF, ePUB), no subscription required. 2-hr reading time. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Snap announced on April 15 that it will cut roughly 1,000 employees and cancel more than 300 open positions, reducing its global workforce by 16 percent. CEO Evan Spiegel told staff the company expects to save more than $500 million annually from the cuts. Snap’s stock rose on the news.The company said the savings will fund AI infrastructure investments. The news fits a market pattern: Snap’s stock rose on the announcement, which means investors are rewarding the conversion of payroll into AI spending. That financial incentive now applies to every publicly traded company watching Snap’s share price.The broader jobs picture looks calmer on the surface. The Bureau of Labor Statistics reported that the U.S. economy added 178,000 jobs in March, and the national unemployment rate edged down to 4.3 percent. Those headline numbers are healthy by recent standards.Underneath them, though, the Federal Reserve Bank of New York found that workers aged 22 to 27 face an unemployment rate of 5.6 percent, well above the national figure.The reason is structural. AI now handles the codifiable tasks that entry-level jobs used to provide: drafting basic documents, producing standard reports, running routine analysis.Employers are keeping experienced workers and letting AI absorb the on-ramp that younger workers traditionally climbed. The headline unemployment rate looks fine. The entry-level job market is a different story entirely.IBM is reading that situation as a strategic risk. The company has tripled its entry-level hiring in 2026, bucking the prevailing industry trend.IBM argues that eliminating junior roles produces short-term savings but destroys the pipeline that generates experienced workers and managers five years down the road.A company that stops hiring entry-level workers today will face a serious leadership gap in the future. IBM is also arguing that AI tools still need human direction, judgment, and context.The tripled hiring is a bet that applied AI literacy combined with human judgment produces better outcomes than AI operating without new staff.Whether other major employers follow that reasoning, or continue optimizing for immediate cost reduction, will shape the career prospects of an entire generation.The European Central Bank published research this week drawing on surveys of more than 5,000 euro-area firms. The finding is that companies actively investing in AI are 4 percent more likely to add headcount than their non-AI peers.The employment benefit shows up primarily at small firms. Large firms show a neutral effect. The ECB’s explanation is that AI investment tends to accompany business growth, and growing businesses hire people.That dynamic holds in Europe’s current environment. The important caveat is the phrase “for now.” The ECB economists are describing short-term outcomes in firms that are still early in their AI adoption. The same firms that are hiring today may face different pressures once AI capabilities mature further.The most striking labor story of the week came out of China. A Shanghai engineer built a tool called Colleague Skill, reported today by MIT Technology Review.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The tool works by ingesting an employee’s work chat history and internal documents. It then produces a detailed profile of how that person does their job, including their reasoning patterns, communication style, and decision-making approach.The stated purpose is to allow a company to automate that employee’s role. The tool went viral on Chinese social media, initially as dark humor. Workers joked about automating their coworkers before their coworkers automated them. The debate that followed turned serious quickly.Legal scholars pointed out that a work chat history may belong to the employer, but the judgment, tone, and professional instincts embedded in it belong to the person. Colleague Skill forces a question that no labor law in any country has yet answered cleanly: when AI learns how you think from materials you produced at work, who owns that knowledge?A compilation of the Substack articles examining how the invasion already happened. You just weren’t invited. $9.95 flat fee for the bundle (PDF, ePUB), no subscription required. 2-hr reading time. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

The economists who understand technology best cannot agree on whether AI is the sixth act in a 250-year story of progress, or the first act of something history has no name for yet.It is the central fact of the labor market in 2026. On one side, Morgan Stanley published a careful analysis this week tracing five major innovation waves across 250 years.Chief U.S. Economist Michael Gapen is explicit that those waves “are disruptive, capital-intensive and often volatile. They can displace workers, concentrate gains early and provoke political backlash. But over time, they raise productivity, restructure labor markets, expand output and, when institutions adapt, improve living standards broadly.”The phrase “when institutions adapt” is doing enormous work in that sentence. The history bears the caveat out. Real wages in Britain barely moved during the first 80 years of industrialization, a period Acemoglu and Johnson document in Power and Progress as a sustained collapse in working conditions for the people inside the transition.Child labor, 14-hour shifts, and unsafe factories were the daily reality, not a deviation from it. The right to organize, factory safety laws, and meaningful limits on working hours took another 50 years to win after that.The “long run” in Morgan Stanley’s framing was, for actual workers, roughly a century and a half of paying the cost for gains that would eventually reach their great-grandchildren.On the other side of the argument, three of the most influential labor economists alive, Daron Acemoglu, Simon Johnson, and David Autor, published a direct challenge to the historical optimism this week. Their argument is that “pure automation technologies” do the opposite of collaborating with workers. They “commodify human expertise, rendering it less valuable and potentially superfluous.” If they are right, the institutional adaptations that eventually rescued workers in previous waves may not have the same leverage this time.The distinction Morgan Stanley draws between augmentation and substitution is real and matters for how you read the current data. Morgan Stanley Research Economist Diego Anzoategui says: “The same technology that automates tasks can also augment workers, increase productivity and boost demand in AI-exposed sectors. So far, the data suggest early, narrow displacement, more visible among younger workers, while overall disruption remains limited.”That framing is accurate as a description of what the aggregate data currently shows. The Acemoglu et al paper does not dispute the current data. It disputes the inference that current patterns will hold as AI capabilities accelerate.The historical record they rely on, the same record Morgan Stanley cites, suggests that even when the long-run outcome is positive, the transition itself can immiserate two or three generations of workers before institutions catch up.The gender dimension of this debate has received far less attention than it deserves. A research brief published in March by the International Labour Organization, drawing on data from 436 occupations across dozens of countries, established a finding that changes the shape of the entire conversation.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Female-dominated occupations are almost twice as likely to be exposed to generative AI as male-dominated ones. Around 29% of female-dominated occupations are exposed to generative AI, compared to just 16% of male-dominated occupations.The difference is even starker at the highest automation risk: 16% of female-dominated occupations fall into the highest exposure categories, compared to only 3% of male-dominated ones.The International Labor Organization (ILO) traces this gap to a structural feature of the labor market that predates AI entirely. Women are heavily concentrated in clerical, administrative, and business support roles, such as secretaries, receptionists, payroll clerks, and accounting assistants. Many of the tasks are routine and codifiable and therefore at higher risk of substitution by generative AI.By contrast, men are more represented in construction, manufacturing, and manual trades, where tasks are less easily automated.The problem compounds at the other end. The jobs being created by AI adoption, the ones carrying wage premiums and growing demand, are concentrated in engineering, cloud architecture, and AI development.Globally, women accounted for only about 30% of the AI workforce in 2022, only 4 percentage points higher than in 2016. The displacement risk is concentrated where women work. The opportunity is concentrated where women are underrepresented.That structural mismatch does not resolve itself through retraining programs: of the workers most at risk of losing their jobs due to AI, more than 6 million would likely struggle to cope because they are older, have limited savings, and face other barriers.Most of those workers are in clerical and administrative jobs, roles that have historically been dominated by women.The ILO’s senior economist Janine Berg put the core policy question plainly: The impact of generative AI on women’s jobs is not predetermined. “With the right policies, social dialogue and gender-responsive design, we can avert reinforcing existing discrimination,” she said.If the policy choices are not made, the default outcome is an AI transition that widens the existing gender wage and employment gap.The Morgan Stanley historical analysis and the Acemoglu et al warning are not actually incompatible once the timeline is named honestly. They operate at different scales. Morgan Stanley’s data describes what aggregate labor markets are showing right now, and what historical patterns suggest about century-scale outcomes.Acemoglu et al are describing the mechanism by which this wave could compress or extend the brutal middle period, the part where workers absorb the cost while waiting for institutions to catch up.Both can be true simultaneously: the long-run historical record is broadly positive, and the transition itself can take three generations and require sustained political struggle to make those gains reach ordinary workers.The American Enterprise Institute frames the burden of proof as belonging to what it calls “the discontinuity camp,” whose case “rests more on what AI could theoretically do than on what labor markets are actually showing.”That framing is fair given the current aggregate data. The ILO gender numbers suggest, however, that for specific populations of workers, the discontinuity may already be arriving. Whether the institutional adaptations Morgan Stanley’s Gapen names actually happen in time, and for whom, is the political question that historical optimism cannot answer on its own.A compilation of the Substack articles examining how the invasion already happened. You just weren’t invited. $9.95 flat fee for the bundle (PDF, ePUB), no subscription required. 2-hr reading time. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

Two developments this week force a question that labor economists have mostly avoided: what happens when AI stops assisting human workers and starts replacing the judgment calls at the core of their jobs?The first development is a legal one; the second, a technology one.In the first instance, plaintiffs in the landmark case Mobley v. Workday, Inc. filed an amended complaint in late March 2026. The complaint revived California state claims and a physical disability discrimination count after a federal judge’s ruling kept core federal age discrimination claims alive.The case involves Derek Mobley, an African-American man over 40 with anxiety and depression. He applied for more than 100 jobs through companies using Workday’s AI-powered applicant screening tools. He was rejected every time, sometimes within minutes of applying.A federal court has allowed discrimination claims against Workday’s AI screening tools to proceed on an unprecedented “agent” liability theory. The case is advancing primarily on age discrimination under the Age Discrimination in Employment Act. The outcome of the case could impact the lives of hundreds of millions of job applicants.The case is the first major test of whether AI vendors — not just employers — can be held directly liable for algorithmic hiring bias under federal anti-discrimination law. The legal significance here is structural, not just factual. AI hiring tools are used by thousands of companies as a cost-saving measure.87% of companies are now using AI-driven tools to save time and money in the hiring process. When those tools discriminate, they do so at scale, across every employer using the same platform simultaneously.The Workday case tests a theory that has major consequences for anyone in the job market over age 40: that the vendor of the discriminating tool shares legal liability with the employer.If the court upholds that theory, it opens class-action exposure for every major HR software company operating AI screening at scale.A University of Washington study found that recruiters using biased AI tools mirrored the tool’s inequitable choices up to 90% of the time. The study illustrates that both the AI vendor and the employer carry liability.If your company runs AI applicant tracking systems without documented bias testing, adverse impact analysis, and a human-in-the-loop override, the Board is sitting on a legal exposure it did not budget for.The second development connects to the first at the level of capability.OpenAI’s GPT-5.4, released in early March, achieves a new state of the art on GDPval. GDPval is a benchmark that tests AI agents on well-specified knowledge work across 44 occupations.GDPval measures real work products: sales presentations, accounting spreadsheets, urgent care schedules, manufacturing diagrams. It is not a test of abstract reasoning. It is a test of the actual output that knowledge workers produce on a given Tuesday.OpenAI’s 5.4 model matches or exceeds industry professionals in 83% of comparisons. That’s up from 70.9% for its predecessor, GPT-5.2.On an internal benchmark simulating tasks that a junior investment banking analyst might perform, GPT-5.4 scored 87.3%, up from 68.4% for GPT-5.2. Tasks include spreadsheet modeling, scenario analysis, and data extraction.The improvement represents a 28-point gain in under four months. The rapid improvement suggests accuracy could reach human professional-levels in the high 80s or low 90s within the next year if the trend holds.So, AI tools are now being used to screen job applicants, manage HR workflows, and conduct tasks previously performed by junior knowledge workers. The Workday case reveals that those tools carry discrimination risks that no one has adequately audited.The GPT-5.4 benchmark results reveal that those tools are improving fast enough that the category of “tasks requiring human judgment” is shrinking.AI is not merely replacing tasks, but deconstructing occupations into automated and human-centric components.“Deconstructing occupations” describes something more precise than replacement. A job that used to require a human is being split into its component tasks. Some tasks go to AI.The remaining tasks stay with humans; those activities that require judgment, relationship management, or physical presence. The human does fewer things. Their employer employs fewer people.In the Gulf region, financial institutions are deploying autonomous agents to handle 80% of routine compliance and reporting. The agents enable human staff to focus on high-stakes advisory and regional strategy.The most notable change in 2026 is the move toward agentic workflows. Modern AI agents can now coordinate across departments. They can manage complex projects with minimal human oversight.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.According to PwC, roughly 44% of core worker skills have been disrupted in the last 24 months. The new gold standard for the global workforce includes:* strategic prompting and orchestration* the ability to manage multiple AI agents simultaneously* AI ethics and bias mitigation* and complex emotional intelligence , or EQSo, the Workday case is working through a legal system designed for a world where a human manager made hiring decisions. The AI tools now making those decisions at scale were designed by engineers optimizing for efficiency.The discrimination they produce is not intentional. That makes it harder to detect, harder to litigate, and harder to remedy.Colorado’s AI law, set to take effect at the end of June 2026, will require employers in the state that deploy high-risk AI systems to take “reasonable care” to protect consumers from discrimination.HR software that screens candidates, scores performance, or ranks employees is classified as high-risk AI under Colorado’s law. Colorado is the first state to impose that standard.Whether other states follow suit before the tools spread further is an open question. The outcome has real consequences for every worker who will be filtered by an algorithm in the next job search.A compilation of the Substack articles examining how the invasion already happened. You just weren’t invited. $9.95 flat fee for the bundle (PDF, ePUB), no subscription required. 2-hr reading time. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

The Indian IT outsourcing industry has been the backbone of American corporate technology for three decades. When U.S. banks, insurance companies, and healthcare systems needed to build and maintain software at scale, they turned to Indian firms like Tata Consultancy Services, Infosys, and Wipro. That model is now fracturing, and the fracture line runs directly through AI.An analysis of regulatory filings shows that Indian IT and business process outsourcing firms may have laid off more people in the U.S. in the first three months of 2026 than in all of 2025.WARN notices, required by U.S. law for large layoffs, have been filed by Infosys, HCL Technologies, and Hinduja Global Services across Florida, Texas, and Pennsylvania. WARN notices are the formal legal mechanism companies use to notify state governments of mass layoffs 60 days in advance.The spike in filings is a documented, verifiable acceleration, not a trend based on projections. In 2024, Indian IT firms filed four WARN notices. In 2025, only Genpact filed one. But in the first quarter of 2026 alone, multiple notices have already been filed.This is a red flag for United States AI-related job cuts: Indian nationals likely do not show up in layoff statistics, as Indian IT firms may have hired them as contractors and not employees. Laid off employees can claim unemployment benefits, which appear in state and federal registers; contractors have to troll for their next gig.Indian IT companies are cutting more jobs in the U.S. mainly because AI is making some roles less necessary and big tech deals are slowing down. Most of the layoffs hit on-site workers tied to huge transformation projects.The old model worked like this: a major U.S. bank would sign a multi-billion dollar, multi-year outsourcing contract. The Indian IT firm would deploy hundreds of engineers on U.S. soil to manage the project.AI is shrinking the headcount those projects require, though. Productivity gains of up to 30% mean fewer people are needed for the same work. The industry is shifting from execution to collaboration, and the old model of deploying thousands of engineers onsite is fading.The human consequence of this shift is not simply that Indian workers lose U.S.-based jobs. While not impossible, career transitions are difficult and require time — a precious commodity in any labor market.A mid-level programmer whose role is automated may not easily transition to becoming an AI architect or a strategic advisor. The reskilling challenge is enormous. While companies are investing billions in training programs, the question is whether those programs can scale fast enough to meet the needs of displaced workers.Business Process Outsourcing — or BPO — presents the same problem at larger scale. India employs roughly 1.65 million workers in voice support, data processing, and administrative BPO roles.Startups like Bengaluru-based LimeChat are deploying AI agents that can handle up to 95% of customer queries without human assistance. “Once you hire a LimeChat agent, you never have to hire again,” said Nikhil Gupta, co-founder of LimeChat.For the businesses buying this technology, the appeal is lower costs and higher scalability. The business opportunity foreshadows lower headcounts for the 1.65 million workers whose livelihoods depend on those call center roles.Entry-level BPO roles, the foundation of the offshore talent pyramid, sit squarely in the line of fire, mirroring broader warnings that AI could dramatically shrink India’s BPO workforce by 2030.The question now being asked across the sector is whether that displacement accelerates the transition toward higher-value knowledge process outsourcing, or KPO. KPO refers to higher-complexity work like legal research, financial analysis, and medical coding. AI already handles routine data entry and customer service calls more cheaply.Stilll, human judgment still commands a premium, even if AI hollows out the talent pipeline that feeds it.The question is whether enough KPO work exists to absorb the workers displaced from the lower tier.The picture from South Asia is not entirely negative, which provides indicators for the United States labor market. In South Asia, AI-related job postings have increased, offering wages roughly 30% higher than comparable white-collar jobs.The premium for AI skills is real and documented. The problem, however, is the gap between who is losing routine BPO work and who is positioned to capture AI-adjacent roles. Those are largely different people with different educational backgrounds and different geographic locations within India.LinkedIn’s 2026 Labor Market Report, released in January and drawing on data from over 1.3 billion users globally, offers a frame for understanding the new job categories being created.AI has created demand at scale, including more than 600,000 new AI-enabled data center jobs and 1.3 million new roles.Some of the new roles include: AI engineers, forward-deployed engineers, and data annotators. AI Engineer is one of the fastest-growing jobs on LinkedIn over the past three years.This mix of uneven hiring and AI-driven job creation marks what LinkedIn among others are calling the new-collar era: a workforce that blends knowledge work, advanced technical skills, and distinctly human strengths.Take, for instance, the forward-deployed engineer role. It did not exist as a job title five years ago. The function is to take AI systems that work in a controlled technical environment and make them actually function inside a specific company’s existing workflows, systems, and culture.Future Forwarded is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Building AI turns out to be considerably easier than deploying it successfully. The demand for people who can bridge that gap is real.So, AI is creating a class of premium new roles while simultaneously eliminating a much larger class of routine roles.The new roles pay more. They require different skills. They are concentrated in different geographies.The consensus emerging from buyers and analysts is that what remains after AI automation is precisely where specialist human partners add the most defensible value. We’re talking , complex judgment calls, sensitive customer interactions, and regulated processes,The question arises, though: how many of the 1.65 million displaced BPO workers, or the thousands of Indian IT engineers losing on-site U.S. contracts can retool before their windows of opportunity close.A compilation of the Substack articles examining how the invasion already happened. You just weren’t invited. $9.95 flat fee for the bundle (PDF, ePUB), no subscription required. 2-hr reading time. Get full access to Future Forwarded at futureforwarded.substack.com/subscribe Get full access to The AI/Labor Report at ailabor.substack.com/subscribe

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