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        "result": "supported"
    },
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        "result": "unsupported"
    }
]

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All Sources | jobsdata.ai Research Library | jobsdata.ai

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September 2026
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The jobs apocalypse is postponed. An AI jobs boom is here
The Economist
·
Sep 2026
·
Tier
3
The Economist's own estimate that AI has created roughly 1m US jobs against about 200,000 AI-attributed lay-offs since mid-2023, built from the data-centre build-out, AI-native hiring and new AI roles at incumbents. "The Economist estimates that AI has so far created around 1m new jobs in America. That easily exceeds the roughly 200,000 lay-offs attributed to AI since mid-2023." Counter-evidence in the same piece: professional and business services hiring runs about 10% below its 2015-19 average, customer-service employment is down about 10% and secretaries and administrative assistants about 15% since January 2023.
Projected US Job Displacement from AI by 2030
Early-Career Employment Decline in AI-Exposed Occupations
White-Collar Professional Displacement by 2030
Customer Service Automation by 2028
+
1
more
RPLS US Jobs Report: The US Economy Adds 36.5k Jobs in August
reveliolabs.com
·
Sep 2026
·
Tier
2
Since before ChatGPT, employment in the most AI-exposed occupations is down around 6% relative to the least-exposed occupations, with the gap reaching 19% among workers aged 22–25
Early-Career Employment Decline in AI-Exposed Occupations
White-Collar Professional Displacement by 2030
Projected US Job Displacement from AI by 2030
AI Adoption Rate Across US Companies
+
1
more
Businesses Are Using AI to Transform Work, Not Cut Jobs
Federal Reserve Bank of New York, Liberty Street Economics (Abel, Deitz, Emanuel, Montalbano)
·
Sep 2026
·
Tier
1
Third annual AI module in the NY Fed's regional business surveys. "61 percent of service firms reported using AI this year, up from 40 percent last year and 25 percent in 2024"; manufacturers reached 51 percent, "roughly double the 26 percent from last year and triple the 16 percent in 2024." Adoption is wide but shallow: three-quarters of service firms and more than 90 percent of manufacturers call their AI investment minimal to modest, and among adopters "the median share of workers using it was just 17 percent for service firms and 7 percent for manufacturers." Only 4 percent of service adopters laid off workers because of AI, 15 percent hired fewer and 13 percent hired more, while just over a third retrained.
AI Adoption Rate Across US Companies
Projected US Job Displacement from AI by 2030
Observed AI Use at Work
Economic Scenarios for Transformative AI — modest change scenario
The Anthropic Institute (Korinek, Jones, Sacher, Cotter, McCrory)
·
Sep 2026
·
Tier
2
Modest change scenario (m2030 = 0.20, d2030 = 0.20, automation share 0.50, reinstatement 0.5). "GDP is 1.6 percent above its no-AI path in 2030... Cognitive employment is 0.5 percent below its mid-2026 level. The unemployment rate is 3.9 percent against a normal level of 3.8: the modest change scenario has only small labor market effects." The authors attach no probabilities to the scenarios: "The scenarios are not predictions, and we attach no probabilities to them; their purpose is to make the consequences of different assumptions comparable."
White-Collar Professional Displacement by 2030
Median Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
Economic Scenarios for Transformative AI — substantial change scenario
The Anthropic Institute (Korinek, Jones, Sacher, Cotter, McCrory)
·
Sep 2026
·
Tier
2
Substantial change scenario (m2030 = 0.30, d2030 = 0.40, automation share 0.75, reinstatement 0.25). "Cognitive employment is 3.9 percent below its mid-2026 level, and employment in all other occupations has risen by 4.6 percent. Because reallocation takes time, the unemployment rate of cognitive workers rises from 2.9 percent in mid-2026 to 4.5 percent in 2030." GDP is 8.3 percent above the no-AI path, the average wage 2.1 percent above it, and the labor share falls from 60 to 56 percent. The authors attach no probabilities to the scenarios.
White-Collar Professional Displacement by 2030
Median Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
Economic Scenarios for Transformative AI — extreme change scenario
The Anthropic Institute (Korinek, Jones, Sacher, Cotter, McCrory)
·
Sep 2026
·
Tier
2
Extreme change scenario (m2030 = 0.50, d2030 = 0.60, automation share 0.90, reinstatement 0). "By 2030, cognitive employment is 21.5 percent below its mid-2026 level, and the unemployment rate for workers who began in cognitive occupations is a stunning 17.9 percent, far above any postwar rate in the United States. The economy-wide unemployment rate rises to 11.9 percent." GDP is 32.4 percent above the no-AI path, the cognitive wage 11.5 percent below it, and the labor share falls from 60 to 45 percent. The authors attach no probabilities to the scenarios.
White-Collar Professional Displacement by 2030
Median Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
Economic Scenarios for Transformative AI — outcomes implied by a survey of US adults
The Anthropic Institute (Korinek, Jones, Sacher, Cotter, McCrory)
·
Sep 2026
·
Tier
2
Model outcomes run on each respondent's own five answers, for the 3,259 of 10,980 surveyed US adults who answered all five items. "Cognitive employment, pct. change since mid-2026: -4.2 [-9, -1]", with the interquartile range in brackets. "The public's answers deliver outcomes close to the substantial change scenario." Unlike the three illustrative scenarios, this is a central tendency with a stated dispersion.
White-Collar Professional Displacement by 2030
Economic Scenarios for Transformative AI
The Anthropic Institute (Korinek, Jones, Sacher, Cotter, McCrory)
·
Sep 2026
·
Tier
2
Task-based model mapping AI capability, diffusion, productivity gain, automation share and reinstatement into paths for GDP, the labor share, wages, reallocation and unemployment to 2030. Cognitive occupations are SOC 11-29, 41 and 43 (management, professional, sales and office work), 62.4 percent of employment. "In the modest change scenario, AI acts like a 'normal technology' over the next five years and has small macroeconomic effects. In the extreme scenario, AI is transformative: by 2030 GDP is 32 percent above its no-AI path and nearly one in five cognitive workers is unemployed." Reviewed by Acemoglu, Autor, Moll, Nakamura, Restrepo, Romer and Steinsson among others, who were not asked to endorse its conclusions.
White-Collar Professional Displacement by 2030
Median Wage Impact from AI by 2030
High-Skill AI Wage Premium
US Workforce AI Exposure
August 2026
22
source
s
Half the Labor Force Is Having a Very Good Year
The Burning Glass Institute (Gad Levanon)
·
Aug 2026
·
Tier
3
The 88 million US workers aged 22 and over without a bachelor's degree — more than half the labor force — sit near the strongest unemployment readings of the past twenty years, while degree-holders have weakened. Within the same age band, young college graduates aged 22-34 sit at the 70th percentile of their own history since 2003 while young non-graduates sit at the 25th; the two series decoupled in 2024 after moving together for two decades.
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
Early-Career Employment Decline in AI-Exposed Occupations
AI and Employment: So Far, So Good
Marginal Revolution (Alex Tabarrok)
·
Aug 2026
·
Tier
3
Census has twice asked firms how AI use affected their total employment over the prior six months. In December 2023 to February 2024, when about 5% of firms used AI, "2.8% increased, 2.6% decreased and 94.6% reported no change." In November 2025 to February 2026, with adoption roughly tripled, "2.3% increased, 2.0% decreased, and 95.7% reported no change." Adoption rose sharply while the share reporting any AI-attributed employment effect fell slightly.
Projected US Job Displacement from AI by 2030
Understanding AI and Productivity
Economic Innovation Group / Agglomerations (Chad Syverson, Chicago Booth)
·
Aug 2026
·
Tier
2
Guest essay for EIG's American Worker Project by Chad Syverson, co-author of the original productivity J-curve paper. On the macro series: labor productivity "grew throughout the 2010s by about 1.5 percent per year, roughly half of its growth rate during the productivity boom of 1995-2004," and "productivity from mid-2022 on has maintained a faster-than-2010s trajectory involving annual growth of about 2.2 percent." He declines to attribute this to AI: "The timing leans against AI being the sole initial cause," since the acceleration began when AI investment was small and coincided with pandemic-era churn and business formation; his stated test is duration. A sustained 1.5-to-2.2 move would leave GDP per capita "7 percent higher than otherwise" after a decade, against nearly 3.0 percent annual growth in the 1995-2004 boom and "in excess of 2.5 percent for a decade or longer" in past GPT booms. Original cross-sector analysis (Figure 2) plots each sector's change in contribution to economy-wide productivity growth (2019-25 minus 2007-19) against its employment-weighted Census BTOS 2025 AI adoption rate: the correlation is positive but "weak enough, relative to the number of sectors, that one cannot rule out chance as its source"; excluding retail it is "more than twice as large," a specification he calls "treading on thin statistical ice." On employment: "At least over the first couple years of its use, AI has had remarkably little employment effect, positive or negative." J-curve restatement: understatement periods "could extend well beyond a decade, and cumulative productivity mismeasurement of double-digits percent," and "Where are we on the AI J-curve now? It is too early to know that with much precision."
AI Adoption Rate Across US Companies
Projected US Job Displacement from AI by 2030
Artificial Intelligence (AI) exposure categories
U.S. Bureau of Labor Statistics
·
Aug 2026
·
Tier
1
BLS combined five external data sources to create a four-category classification of relative AI exposure for every detailed occupation for which projections are produced. Across 4,155 possible occupation-source combinations for the detailed occupations for which BLS publishes projections data (831 occupations times 5 sources), 3,944 were observed and 211 were imputed, affecting 75 occupations. Exposure does not imply job loss, productivity gains, automation probability, or wage effects.
US Workforce AI Exposure
AI and the City
Stripe Economics (Tedeschi)
·
Aug 2026
·
Tier
2
Stripe Economics analysis of where AI-era businesses are forming, using Stripe sign-up data by metro. "Close to 40% of new businesses on Stripe this year are in metros with fewer than one million people, up 10% relative to four years ago." "This year, twice as many new businesses were formed per person in Cheyenne, Wyoming than in New York City; in 2022, the rates of business formation in both cities were equal." Within major metros, "close to 80% of sign-ups in major metropolitan areas are outside of the city center and high-density inner ring"; Houston "saw 37% of new businesses forming in the outer suburbs this year, up four percentage points relative to 2023." The shift "is also reflected in Census data and is roughly one third as large as the COVID-era move away from major cities." Frontier AI work is the exception: "Almost 80% of AI businesses closest to the technological frontier (the labs) are in San Francisco alone," and 50% of AI product companies are in San Francisco or top-10 metros. Authors caution that AI cannot be cleanly disentangled from remote work, though formation "appears uncorrelated with work from home intensity."
AI-Driven New Business Formation
A Turbulent AI Era and Critical Choices to Make
Gates Notes (Bill Gates)
·
Aug 2026
·
Tier
4
"AI will take on work in law, customer service, medicine, software, and manufacturing. It will hit these industries rapidly, over the course of a decade rather than a few generations." "The jobs at most risk are entry- and mid-level, and the new jobs being created will mostly require skills that take many years to learn." Proposes a Human Reserved domain of jobs set aside for people, and a tax on AI tokens and robots: "if you're an employer and you hire someone, you pay payroll taxes on their earnings. But if you buy a robot, you can usually write it off right away as a business expense. The tax system nudges you toward replacing people with machines."
Early-Career Employment Decline in AI-Exposed Occupations
Projected US Job Displacement from AI by 2030
Robots & Physical Automation Displacement by 2030
What can federal data collection tell policymakers and researchers about artificial intelligence in the U.S. labor market?
Washington Center for Equitable Growth (Mary Beech)
·
Aug 2026
·
Tier
2
First of a three-part series mapping US federal labor data against the question of AI's effects. "Existing federal data sources cannot be used yet to conclusively show whether and how AI might be driving changes in the U.S. labor market." The core failure is linkage: BTOS and Annual Business Survey AI-adoption responses "are not linked to the Longitudinal Employer-Household Dynamics data, wage records, or other worker-level outcomes, even though both datasets sit within the Census Bureau." BTOS "asks firms a yes or no question... Because this is a binary measure, it does not capture how or to what extent firms use AI." A 2024 OECD survey of 6,000+ firms across six countries found 90 percent of responding US firms had adopted at least one algorithmic management tool.
AI Adoption Rate Across US Companies
Projected US Job Displacement from AI by 2030
Immiserizing Automation
CREi / Barcelona School of Economics (Asriyan, Reichardt, Shelegia)
·
Aug 2026
·
Tier
1
"Our main result is that automation of junior tasks can be immiserizing: when its cost savings are small, automation lowers long-run output." Empirically: "an industry for which the junior bias was one standard deviation stronger saw an additional decline of about 10% in employment," using US Census/ACS microdata 1970-2020 and occupation-level robot exposure from Garg et al. (2026). Calibrated to 1980, at the Acemoglu-Restrepo 30% robot cost-savings estimate the model yields a 2.6% output gain against 3.5% under output maximization, and a 4.5 percentage-point fall in labor force participation.
Early-Career Employment Decline in AI-Exposed Occupations
Entry-Level Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
Robots & Physical Automation Displacement by 2030
The Wage Effects of Generative AI
IESE Business School (Azar, Giné, Sanz-Espín)
·
Aug 2026
·
Tier
2
Continuous-treatment difference-in-differences around the 30 November 2022 ChatGPT release, across two datasets covering knowledge-intensive service industries (NAICS 51-56). "We find that moving from the 10th percentile to the 90th percentile of GenAI exposure is associated with a wage decline of 4.9% in OEWS data, with no statistically detectable change in employment. In Revelio data, moving from the 10th to the 90th percentile of exposure is associated with a decline of 8.71% in posted wages, and of 10.76% in starting wages." The seniority gradient is the paper's sharpest result: "By 2026, moving from the 10th to the 90th percentile of exposure is associated with wage declines of approximately 7.5% for junior positions, 3.2% for mid-level positions, and 1.8% for senior positions," and critically "the large junior effect is therefore not simply a young-worker effect. Wage declines appear throughout the junior age distribution and are largest among older juniors." On mobility: separations fall 3.0pp (18.6% of the pre-ChatGPT mean) and job-to-job transitions fall 2.8pp (28.8%), with "no statistically significant change in separations to persistent non-employment." The authors read this as deteriorating outside options rather than displacement: "outside opportunities deteriorate before existing jobs disappear." Separation elasticities attenuate most at high exposure, implying markdown increases of 38.2% to 75.1% across exposure quintiles under an inverse-elasticity benchmark the authors call illustrative.
Median Wage Impact from AI by 2030
Entry-Level Wage Impact from AI by 2030
High-Skill AI Wage Premium
White-Collar Professional Displacement by 2030
Goldman studied where AI is squeezing labor markets. Here's what it found
Goldman Sachs Research (via CNBC)
·
Aug 2026
·
Tier
2
Goldman's first cross-country read on AI and employment. Industries more exposed to AI automation have seen slower job-openings growth since H2 2022, most pronounced in Germany, Australia and the US. Call-center employment is 39% below trend in the US, 33% in Canada and 27% in Germany; software publishing, management consulting and advertising also fell sharply below trend. Across more than 800 occupations, a 10% occupational AI exposure is associated with a 0.1pp drag on annual headcount growth in France, Canada and the US, rising to more than 0.6pp (Australia) and over 0.2pp (US) for entry-level workers. Combining 11 adoption surveys, developed markets sit at roughly 15-20% adoption and emerging markets 10-15%.
AI Adoption Rate Across US Companies
Customer Service Automation by 2028
Early-Career Employment Decline in AI-Exposed Occupations
Projected US Job Displacement from AI by 2030
Business Trends and Outlook Survey — Biweekly AI Use (cycles 202614–202616)
US Census Bureau
·
Aug 2026
·
Tier
1
BTOS biweekly question 7: "In the last two weeks, did this business use Artificial Intelligence (AI) in any of its business functions? (Examples of AI: machine learning, natural language processing, virtual agents, voice recognition, etc.)" Share answering Yes: 21.7% for reference period June 15–28, 2026 (SE 0.31%); 21.5% for June 29–July 12, 2026 (SE 0.42%); 21.8% for July 13–26, 2026 (SE 0.33%). Expected use in the next six months reached 25.9% in the latest cycle. Values dated to reference-period end, not release date.
AI Adoption Rate Across US Companies
Worker Types, AI Exposure and the Recent Decline in Job-Finding Rates (Economic Brief 26-26)
Federal Reserve Bank of Richmond (Borovickova, Macaluso)
·
Aug 2026
·
Tier
1
Decomposes the post-2023 decline in job-finding rates by worker type and AI exposure. Entrants are not the margin: "Job-finding rates for new entrants have declined in recent years, but the drop is modest relative to the declines among job losers and job leavers." The decline concentrates instead among strongly attached incumbents in highly AI-exposed occupations, whose job-finding rate fell roughly 13 percentage points against about 2 points for marginally attached workers - a caution that entrant-focused readings of the AI evidence may be misattributing an incumbent phenomenon.
Early-Career Employment Decline in AI-Exposed Occupations
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence (August 2026)
Stanford Digital Economy Lab (Brynjolfsson, Chandar, Chen)
·
Aug 2026
·
Tier
1
August 12, 2026 revision of the Canaries study, ADP balanced payroll panel of 3.5-5 million workers per month, January 2021 through June 2026. Employment of workers aged 22-25 in AI-exposed occupations stands 19% below where it would be had it kept pace with less-exposed peers, up from 15% on the same kept-pace measure at the July 2025 data vintage; experienced workers show no comparable gap. No evidence of widespread economy-wide displacement: the ADP sample grew about 6% while the most exposed quintile grew about 4%. Adjustment operates through reduced hiring rather than separations or base compensation.
Early-Career Employment Decline in AI-Exposed Occupations
Entry-Level Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
Business Formation Statistics, July 2026 (CB26-130)
US Census Bureau
·
Aug 2026
·
Tier
1
"Business Applications for July 2026, adjusted for seasonal variation, were 578,926, an increase of 8.1 percent compared to June 2026." "Projected Business Formations (within 4 quarters) for July 2026, adjusted for seasonal variation, were 29,959, an increase of 0.7 percent compared to June 2026." Seasonally adjusted July components: High-Propensity Business Applications 151,857 (+1.4% MoM); Business Applications with Planned Wages 35,024 (-1.6%); Business Applications from Corporations 44,738 (+3.2%); Projected Business Formations within 8 quarters 40,777 (-0.7%). Next scheduled release September 11, 2026.
AI-Driven New Business Formation
Cracks in the AI Thesis (Ramp AI Index, August 2026)
Ramp Economics Lab (Ara Kharazian)
·
Aug 2026
·
Tier
2
Ramp AI Index, August 2026, based on corporate card and bill-pay transactions from more than 70,000 US businesses. Share of US businesses paying for each vendor: Anthropic 43.5% (up 1.1 percentage points month over month), OpenAI 39.7% (up 0.23 points), xAI 4.0% (up 0.94 points). The median firm spent $11.95 per employee on AI.
AI Adoption Rate Across US Companies
Global Employment Trends for Youth 2026: Back to the Future
International Labour Organization
·
Aug 2026
·
Tier
1
"The report estimates that 6.1 per cent of jobs currently held by young people aged 15 to 29 fall in the categories of those most exposed to AI" - 55.8 million of 913.8 million youth jobs globally. Under an illustrative scenario in which a tenth of those jobs disappear outright, "that would translate into 5.6 million employed youth at the global level either facing unemployment, shifting into another job or exiting the labour force." Exposure is concentrated in rich countries: 14.3 per cent of youth jobs in high-income countries and in Northern America, versus 0.9 per cent in low-income countries. ILO cautions that "the degree to which risk translates to job loss is still debatable."
Early-Career Employment Decline in AI-Exposed Occupations
US Workforce AI Exposure
Labor Automation Forecasting Hub (commentary updated August 10, 2026)
Metaculus
·
Aug 2026
·
Tier
2
"Overall employment is projected to fall 1.3% by 2030 and fall 3.7% by 2035 relative to 2025 due to AI-driven displacement. This sharply contrasts with government baselines projecting +3.1% growth over the decade when accounting for aging-adjusted population trends." Community forecast timeline readings: 2027 +0.365%, 2030 -1.28%, 2035 -3.73%. This revises the April 2026 vintage of the same forecast (-1.9% by 2030, -3.4% by 2035).
Projected US Job Displacement from AI by 2030
BLS Employment Situation: July 2026 (series CES0000000001, LNS14000000)
US Bureau of Labor Statistics
·
Aug 2026
·
Tier
1
BLS Employment Situation, July 2026, seasonally adjusted, retrieved from the BLS Public API v2 on August 20, 2026. Total nonfarm payroll employment was 158,858,000 in July, down 23,000 from June (158,881,000). June's gain was revised to +20,000 from the +57,000 initially reported. The unemployment rate was 4.1% in July, down from 4.2% in June and 4.3% in May. Month-over-month by sector: professional and business services +18,000 (22,518,000); information +11,000 (2,780,000); health care and social assistance +22,600 (23,912,200); leisure and hospitality -40,000 (16,931,000).
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
Challenger Report: Layoffs Fall, Hiring Picks Up; AI Leads For Fifth Straight Month
Challenger, Gray & Christmas
·
Aug 2026
·
Tier
2
"U.S.-based employers announced 33,429 job cuts in July", the lowest monthly total in two years. "Artificial Intelligence (AI) led all reasons for job cuts, with 10,970 announced during the month, or 33%". "So far this year, AI has been cited in 112,713 job cut announcements, approximately 24% of all cuts." "Technology again led all sectors, announcing 9,867 job cuts in July for a total of 149,023 in 2026." "Through July, employers have announced 477,033 job cuts, down 41% from the 806,383 cuts announced in the first seven months of 2025."
Projected US Job Displacement from AI by 2030
Tech Sector Displacement by 2030: Uneven by Experience Level
AI's Impact on Labor and Hiring
Federal Reserve Bank of New York — Liberty Street Economics (Athreya)
·
Aug 2026
·
Tier
2
while AI adoption is rising quickly across industries, firms report very few AI-driven layoffs
AI Adoption Rate Across US Companies
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
Time Travel on Professional Profiles
NBER (Bloom, Moore, Simon, Wilkie-Rogers)
·
Aug 2026
·
Tier
1
Using monthly vintages of Revelio Labs data from 2020-2026, the authors show public professional profiles "are not fixed historical snapshots, but mutable accounts that workers revise over time." They find "19.7 percent of established U.S. LinkedIn users retroactively edit the title or description of a job they have already left," that such users "are much more likely to change employers as compared to later-editing users," and that "this mutability can bias historical measures of skills." Retroactive edits show sharp post-2022 increases in AI-related language.
What Work Does Generative AI Do?
nber.org
·
Aug 2026
·
Tier
1
current adoption is widespread but shallow: genAI is used across many occupations and tasks, yet within most of them, fewer than half of workers adopt
Generative AI Adoption
US Workforce AI Exposure
July 2026
29
source
s
The Impact of AI on the U.S. Labor Market: Early Evidence from Observed Adoption
Apollo Global Management
·
Jul 2026
·
Tier
2
Difference-in-differences across 321 matched occupations (BLS OEWS 2015-2025, n=3,296 occupation-years) using observed Anthropic Economic Index usage rather than theoretical exposure. High-exposure occupations saw real wage growth 6.7 percentage points slower after 2023 with no detectable employment effect. 5.8 million workers (3.7% of the labor force) are in high-exposure occupations.
Entry-Level Wage Impact from AI by 2030
High-Skill AI Wage Premium
Median Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
+
1
more
AI Labor Market Tracker: July 2026
Revelio Labs
·
Jul 2026
·
Tier
2
Inaugural edition of Revelio Labs' monthly AI Labor Market Tracker, built on online professional profiles, job postings, salaries, employee reviews and WARN notices. Five headline gauges: CS/IT enrollment supply -28% since 2022; demand for the most AI-exposed roles -42% vs least-exposed since Oct 2022; adopting-firm headcount +27% vs non-adopters; activity-mix dissimilarity +8.4pp yoy; 5.05 postings per hire. Early-career (22-25) employment in most-exposed occupations is down 13% relative to least-exposed since pre-ChatGPT — an independent replication of Brynjolfsson, Chandar & Chen (2025) on non-payroll data. Firm AI adoption reaches ~5.9% of eligible hiring firms; the AI-exposure wage premium has eroded from ~2% to roughly zero.
AI Adoption Rate Across US Companies
Early-Career Employment Decline in AI-Exposed Occupations
High-Skill AI Wage Premium
Projected US Job Displacement from AI by 2030
+
1
more
Work at the Frontier: How AI is expanding what people do at work
OpenAI Economic Research (Chin, Richmond)
·
Jul 2026
·
Tier
2
OpenAI Economic Research, 'Work at the Frontier: How AI is expanding what people do at work' (Chin & Richmond, Jul 27 2026). Random sample of 800,000+ work-related messages from individual ChatGPT accounts of US users whose occupations were linked via ChatGPT Business role data, across eight occupation groups (customer experience, design, engineering, finance, HR, legal, marketing, sales). Each message is classified to a single O*NET detailed work activity and compared with the sender's stated occupation. Headline: '16.8 percent of all work-related messages—and 43.5 percent of occupation-specific messages—concern tasks historically associated with another occupation'; 21.8% are within-occupation and 61.5% generic. Cross-occupation is a majority of occupation-specific messages in five of eight groups: customer experience 77%, design 75%, HR 69%, legal 56%, marketing 53%. Direction of travel differs from volume of borrowing: 'About 35.2 percent of messages sent by designers involve work usually associated with another occupation. But design tasks make up only 1.7 percent of the messages sent by workers in other fields.' Engineering is the inverse (18.5% borrowed in, 7.4% traveling out); marketing leads both directions (24.3% in, 8.9% out — 'the highest share in the sample'). Recurring borrowed tasks: calculating financial data and troubleshooting computer applications each rank top-three in all seven non-native occupation groups. Smaller workspaces show more crossover among typical-volume users: 18.9% at 2-5 seats vs 16.3% at 101+ seats. The report explicitly disclaims employment inference: 'This study maps AI-aided work; it does not estimate AI's effect on employment or productivity,' and the unit of analysis is 'a message, not an hour of work, a completed project, or a job.'
US Workforce AI Exposure
What is really happening to jobs? Separating AI hype from reality
Stanford Institute for Economic Policy Research (SIEPR)
·
Jul 2026
·
Tier
1
Stanford SIEPR policy brief reviewing observed AI labor market effects. Using IPUMS-CPS data, the unemployment rate for the top quintile of AI-exposed workers has risen by 0.77 percentage points since 2022, while the unemployment rate for the least-exposed workers rose slightly more, by 0.85 percentage points over the same period — a differential implying no measurable net AI displacement in aggregate US employment. Employment growth in coding-heavy occupations has slowed somewhat but remains positive, and online job postings for software developers have grown faster than for other occupations over the last year. Among firms that adopted enterprise AI, employment grew by 10 percent in the two years following adoption. In Census BTOS data only 5 percent of firms report any employment impact, with equal numbers reporting gains and losses. New-graduate unemployment reached 5.6 percent in early 2026, up 1.6 percentage points from three years earlier.
Projected US Job Displacement from AI by 2030
FRED Adds Data About the Adoption of Generative Artificial Intelligence (Real-Time Population Survey, Category 8)
Federal Reserve Bank of St. Louis (FRED)
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Jul 2026
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Tier
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FRED has incorporated '137 data series about the adoption of generative artificial intelligence (AI) technology in the United States, reported by Alexander Bick, Adam Blandin, and David Deming' (FRED Announcements, Jul 24, 2026). The RPS GenAI module, fielded quarterly since August 2024, now publishes as official FRED series covering usage rates (overall, work, nonwork), time savings, and adoption compared with the PC and internet, with industry and occupation breakdowns. Latest FRED readings: work adoption 43.4% and overall adoption 57.9% of working-age adults in Q1 2026 (RPSGENAIUSAGESHAREWORK, RPSGENAIUSAGESHAREALL); GenAI-assisted work hours 6.3% in Q2 2026, up from 4.1% in Q4 2024 (RPSGENAIASSISTWRKHRSALL); reported time savings 2.2% of work hours in Q1 2026 (RPSGENAITSALL).
Generative AI Adoption
Google's AI & Economy ATLAS v1.0: Mapping Gemini Usage in the Economy
Google / Google DeepMind (Iscenko, Strand, Imas, Manyika et al.)
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Jul 2026
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Tier
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Google's AI & Economy ATLAS v1.0 (Iscenko, Strand, Chen, Imas, Manyika et al., Google/Google DeepMind, Jul 23 2026; reviewed by Diane Coyle and David Autor). 15M de-identified interactions across Gemini App, AI Mode, and Gemini API (Apr 6-19, 2026), mapped to 800+ occupations, 4,000 O*NET tasks, 300 ATUS activities, 150 countries, 140 languages. Work: 'AI adoption spans occupations covering just above 88% of US employment' (68% of detailed occupations) but 'penetration remains shallow' — 'AI is used for only 21% of total tasks in the median occupation with any AI use'; only 3% of occupations show usage for >75% of tasks. 'Attempts to automate tasks end-to-end represent less than 10% of AI conversations in non-routine cognitive work'; >25% for routine cognitive work. Non-routine cognitive tasks = 35% of O*NET universe but 65% of work interactions. Wages: 'a 1% increase in an occupation's median earnings is associated with a more than 2.5% increase in AI usage intensity'; Gemini-weighted median salary $82,919 vs $62,252 employment-weighted national median. Home: 86% of conversational use is non-work; government/civic queries over-represented ~20x vs time spent; household time-savings valued at $14.9B-$149B/yr (0.5-5% scenarios). Global: 1% GDP/capita ↑ → 0.9% usage ↑; English only ~1/3 of conversations across 143 languages.
Generative AI Adoption
High-Skill AI Wage Premium
Projected US Job Displacement from AI by 2030
US Workforce AI Exposure
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AI and Productivity
Stripe Economics (Tedeschi)
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Jul 2026
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Stripe Economics analysis arguing that accelerating US macro productivity is not yet traceable to AI. "US labor productivity has grown at roughly 2.5% over the past year—a meaningful outperformance over the 1.6% annual average of the last two decades," and a Markov-switching model "suggests a 93% probability the US has moved into a 'high' productivity period." But: "TFP growth has been near zero over the past year" under the Fernald/San Francisco Fed estimates, with "a less-than-20% probability the US is in a high-TFP-growth period." Combining Census BTOS adoption rates with Chicago Fed industry productivity, sectors with heavy AI adoption also showed stronger productivity growth in 2016-2019 before generative AI existed; stripping out those pre-existing trends, "the residual correlation between AI adoption and recent productivity growth falls to essentially zero." Cites Bank of Korea (Suh et al. 2026) finding generative AI adoption "reduces work time by 3.8% (about 1.5 hours per week)" with "essentially no relationship with realized output growth unless workers have autonomy or strong incentives to reallocate the saved time productively."
AI Adoption Rate Across US Companies
Stanford DEL Canaries Dashboard: July 2026 Update
Stanford Digital Economy Lab / ADP Research
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Jul 2026
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Tier
1
July 22, 2026 monthly refresh of the Canaries Dashboard (ADP payroll sample, 4.6M workers, 730+ occupations), data through June 2026. All-ages employment in the most-exposed quintile: -0.2% YoY, +1.1%/yr annualized since ChatGPT vs +2.0%/yr least-exposed. Early-career (22-25) most-exposed: -3.5%/yr annualized, -4.3% past year. New gender analysis: early-career women in the most-exposed quintile contracting 4.5%/yr vs 2.5%/yr for men; 43.8% of early-career women work in the most-exposed occupation category vs 32.4% of men.
Early-Career Employment Decline in AI-Exposed Occupations
Projected US Job Displacement from AI by 2030
Tech Sector Displacement by 2030: Uneven by Experience Level
White-Collar Professional Displacement by 2030
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Generative AI floods and dilutes the market for books
Chakrabarty, Liu, Ginsburg & Dhillon (arXiv preprint)
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Jul 2026
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Full-text AI detection across 14,419 self-published genre-fiction books sold on Amazon 2023-2026, matched to daily sales through June 2026: "the number of books with observed sales in a quarter grew 19.2-fold, while quarterly revenue grew only 8.9-fold. The market therefore added selling books faster than it added revenue, and revenue per selling book fell across most genres." "Books with no AI text lose the most ground in genres with high AI diffusion, and most of all where Kindle Unlimited availability is high."
Creative Industry Displacement by 2030
Why hasn't AI increased unemployment?
X (Peter McCrory, Head of Economics, Anthropic)
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Jul 2026
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Tier
4
A long-form essay synthesizing Anthropic's economic research to argue that GenAI has so far been a skill-biased, labor-augmenting technology. "In my view, AI has caused no material increase in the unemployment rate to date. Even if we focus on workers with high exposure to current patterns of AI automation, we don't see unexpected increases in unemployment in recent years." On the early-career evidence, McCrory offers a macro confound: "from 2022 to now, the US experienced the largest non-recessionary labor market slowdown on record (the 'immaculate disinflation'). This coincided with a 'low hire, low fire' labor market. This kind of labor market hits early-career entrants hardest. Right now, young workers may be struggling to find jobs for macroeconomic reasons other than AI." On software: "Software Engineering job posts have broadly rebounded since May 2025, compared to all other job posts," and "a 10-20x increase in lines of code generated after the introduction of coding agents yielded only a 30% increase in software releases, and no total increase in app usage." He closes: "I don't expect unemployment to be noticeably higher a year from now - at least not because of AI."
Early-Career Employment Decline in AI-Exposed Occupations
Tech Sector Displacement by 2030: Uneven by Experience Level
White-Collar Professional Displacement by 2030
Wage Growth Is Increasingly Concentrated at the Top
Revelio Labs (Jesse Wheeler)
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Jul 2026
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Tier
2
Revelio Labs analysis of advertised salaries on new job postings from its COSMOS dataset. "Between Q2 2025 and Q2 2026, advertised salaries for bottom-decile jobs actually fell 2.2% in real terms (after adjusting for 3.8% CPI inflation), while ninth-decile jobs rose 7.5% and the top decile rose 6.4%." The measure tracks "what employers are offering today, rather than what current workers already earn." The piece argues against an AI-driven white-collar shock: "Recent Revelio Labs research shows that AI adoption is more strongly associated with weaker wage growth at the bottom of the pay distribution than at the top. In addition, we find that firms investing most heavily in AI continue to expand headcounts." Attributed growth is sectoral, concentrated in Professional & Business Services, Information, and Education & Health.
Entry-Level Wage Impact from AI by 2030
AI Revolution Helps Fuel Surge In US Small Business Formation
IBTimes (Pham Binh, citing US Census BFS + Bloomberg + Apollo)
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Jul 2026
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3
IBTimes (Pham Binh, Jul 20 2026) synthesis of US Census Business Formation Statistics + Bloomberg analysis. Headline: '~29,700 new employer businesses are expected to form each month nationwide over the next year, a 17% increase compared to 2025 estimates.' Professional services sector (legal, architectural, advertising) forming at '>5,000 companies per month, a 24% year-over-year increase.' Bloomberg reporting: 'Since the launch of ChatGPT in 2022, new business filings in professional services grew four times faster than in construction.' Torsten Slok (Apollo Global chief economist): 'We've never created as many businesses. It does tell you that AI is playing a very big role.'
AI-Driven New Business Formation
Organizational AI Adoption Jumps Six Points
Gallup (Andy Kemp)
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Jul 2026
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Tier
2
"More than half of U.S. workers (52%) now use AI in their role, with 30% using it frequently (a few times a week or more). Fifteen percent use it daily." 47% of employees say their organization has integrated AI tools, up from 41%. Fielded May 6-20, 2026 among 22,573 employed U.S. adults, margin of error +/-0.9 percentage points. The 52% figure counts anyone using AI at least a few times a year, a looser threshold than the quarterly survey charted on the generative AI adoption graph.
AI Adoption Rate Across US Companies
Generative AI Adoption
The AI Buildout and the Economy: Publicly Available Data to Assess AI's Impact
Board of Governors of the Federal Reserve System (Soto, Thieu, Allen)
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Jul 2026
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Tier
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Federal Reserve Board FEDS Note cataloguing publicly available indicators for tracking the generative AI buildout across three stages: capabilities and costs; firm investment and adoption; and productivity and labor. Notes that headline adoption figures do not reflect usage intensity, which surveys suggest remains shallow even where reported adoption is broad, and that the absence of a large aggregate signal as of 2026 would not necessarily invalidate future productivity impacts given that shallow adoption. Tracks sectoral productivity by AI exposure level, unemployment and labor force participation for workers aged 20-24 against prime-age workers, and layoffs, discharges and job openings in information-processing sectors as a white-collar displacement signal. Methodological reference rather than a source of new estimates.
Projected US Job Displacement from AI by 2030
AI isn't destroying entry-level jobs. It's changing them
Financial Times
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Jul 2026
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Tier
3
FT opinion piece (mid-July 2026) synthesizing the PwC 2026 Global AI Jobs Barometer findings on entry-level work. Argues AI is not eliminating entry-level jobs but transforming them: newcomers previously learned by doing simple, repetitive tasks — the apprenticeship rung — but AI has automated that rung. What remains for entry-level workers now leans on judgment, idea generation, and interpersonal capability — historically senior skills. The piece frames the 'seniorisation' finding (entry-level roles 7x more likely to need senior skills; seniorised roles +35% since 2019 vs -10% for other entry-level roles) as a collapse of the traditional learning-by-doing path, not a jobs bloodbath.
The Future Workforce Index 2026: AI, Freelancing, & the New Value of Work
Upwork
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Jul 2026
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Tier
2
Freelancers performing AI work on Upwork earn 34% more per hour than those not incorporating AI. GenAI/creative production contracts grew 90% YoY in contract starts but per-contract earnings fell 13% — a signal that 'lower-complexity AI execution may become less lucrative as it scales.' Freelancers doing more complex work with AI saw earnings rise 45% YoY; AI-augmented professional services grew 72% in volume with 22% earnings gains. Skilled freelancers now represent 38% of U.S. knowledge workers, up from 28% (a 10pp increase); 58% of full-time employees now consider freelancing, up from 36%.
Freelancer/Gig Worker Rate Impact by 2028
JPMorgan CEO Says AI Cut Up to 40% of Staff in Some Areas, Warns 'Sharp Cost Reductions Are an Illusion'
BigGo Finance (reporting JPMorgan Q2 2026 earnings)
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Jul 2026
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On JPMorgan's Q2 2026 earnings call (July 14, 2026), CEO Jamie Dimon disclosed that AI has 'already reduced headcount by 30% to 40% in certain specific areas' — most affected workers redeployed internally rather than laid off. Dimon pushed back against expectations of dramatic margin gains: 'in a competitive capitalist world, everybody is going to use AI to serve their customers better,' and such improvements 'won't happen anytime soon.' CFO Jeremy Barnum warned AI token spending will grow 'at a non-trivial pace' in H2 2026. JPMorgan maintains ~1,000 active AI use cases.
Financial Services Displacement by 2030
We Must Act Now: A Statement on AI's Economic Transformation
Stanford Digital Economy Lab (Brynjolfsson, Agrawal, Korinek, Cunningham)
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Jul 2026
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Statement organized by Erik Brynjolfsson, Ajay Agrawal, Anton Korinek, and Tom Cunningham. Signed by 16 Nobel Laureates (including Michael Spence and Daron Acemoglu) and 200+ economists and AI researchers. Core thesis: AI 'may become radically more powerful over the next 10 years,' potentially producing an economic transformation 'larger than the Industrial Revolution' on 'a vastly shorter time frame,' with 'large-scale job displacement' as a primary risk. Calls for deeper research on AI's economic impacts and for building policies and institutions to ensure AI complements human capabilities. Korinek: 'Steam, electricity, and computers each gave societies decades to adapt; AI may give us only a few years.' Brynjolfsson: 'AI capabilities are advancing far faster than our understanding of economic implications.' Agrawal: 'Whether rapidly advancing AI broadly elevates living standards or concentrates wealth depends on choices we make today.' Cunningham: 'We are driving in the fog, and it is extraordinarily difficult to anticipate what will happen next.'
AI in Higher Education Global Survey 2026
Digital Education Council
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Jul 2026
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Tier
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The Digital Education Council's AI in Higher Education Global Survey 2026 draws on 45,398 responses from 27,284 students and 18,114 faculty across 35 countries. 88% of students now use AI in their learning; 77% of faculty use it in their teaching, up 16 percentage points on 2025. 57% of students say assessments come with inadequate AI guidance; only 29% believe instructors are equipped to guide them on AI use; 31% of faculty feel meaningfully involved in institutional AI policy. Faculty intent to use AI in teaching dropped from 76% to 67% in US/Canada — the lowest globally — while other regions show 89-94% intent.
Education Sector Displacement by 2030
Business Formation Statistics — June 2026 (Released Jul 9, 2026)
US Census Bureau (BFS)
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Jul 2026
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Tier
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US Census Bureau Business Formation Statistics for June 2026 (released July 9, 2026). Total Business Applications (seasonally adjusted): 531,423 in June 2026, an increase of 1.1% compared to May 2026. Projected Business Formations (within 4 quarters), seasonally adjusted: 29,741 in June 2026, an increase of 0.7% compared to May 2026. BFS provides monthly, high-frequency information on new business applications and formations. The high-propensity applications series (HBA) tracks applications most likely to become employer businesses; definition was updated in Nov 2021 and applied retroactively.
AI-Driven New Business Formation
OECD Employment Outlook 2026 - From Resilience to Risk: Employment and Wages Under Pressure (Ch. 1)
OECD
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Jul 2026
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Tier
1
OECD's flagship employment report finds the youth unemployment gap is real and widening across Australia, Canada, the EU and the US, but attributes it to macro sensitivity rather than LLM diffusion: "the role of LLMs in explaining the unemployment gap of young labour market entrants remains limited, both for those with and without a graduate degree." The ratio of new postings in top- versus bottom-quintile Language Model Exposure occupations "exhibits no break at the end of 2023," when LinkedIn AI-hiring data date the onset of intensive firm LLM use, and the same holds for postings Lightcast flags as junior.
Early-Career Employment Decline in AI-Exposed Occupations
Projected US Job Displacement from AI by 2030
June Brings Deep Cuts at Several Universities
Inside Higher Ed
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Jul 2026
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University of Minnesota regents approved an operating budget eliminating 230 jobs through layoffs and attrition (cutting ~$44M). Johns Hopkins laid off ~110 employees concentrated in the Bloomberg School of Public Health, Carey Business School, and central administration — the university 'has lost hundreds of millions of dollars in federal funding since President Trump took office in January 2025.' The New School laid off 87 employees (19 professors, 68 staff). Southern Oregon University will shutter three academic programs and cut 66 positions (23 faculty, 43 staff).
Education Sector Displacement by 2030
How Will AI Impact the Labor Market? (Goldman Sachs Exchanges)
Goldman Sachs Exchanges (Briggs, Acemoglu, Thompson)
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Jul 2026
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Podcast episode recorded June 2026 with Goldman global economics head Joseph Briggs and MIT's Daron Acemoglu and Neil Thompson. Acemoglu expects "some net job losses, limited, but net job losses within the next five years" at a scale of "less than two to four percent," attributing the ceiling to the absence of reliable off-the-shelf applications built on foundation models, with coding an exception. He sizes the most vulnerable pool, cognitive routine work such as customer service and back office, at eight to nine million US workers, and warns of bigger losses over 10-15 years, with AI-robotics integration the largest wildcard given that physical tasks are about 50% of US work. Briggs puts the current imprint at a 10-15K/month drag on job growth concentrated in tech, consulting and graphic design, and reiterates the 9%/15M ten-year reallocation forecast under a 15% productivity uplift, with any single year's unemployment increase under 1pp. Thompson frames AI as a "rising tide" rather than a "crashing wave."
Projected US Job Displacement from AI by 2030
Robots & Physical Automation Displacement by 2030
A.I. Is Reshaping the Economy. Good Luck Measuring How.
The New York Times (Ben Casselman)
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Jul 2026
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NYT chief economics correspondent Casselman synthesizes the measurement problem: different data sources give contradictory answers on basic questions (how many companies use AI, which workers are most vulnerable, whether AI is helping or hurting employment, whether the productivity boom is real). Reports on Nathan Goldschlag's (Economic Innovation Group) new report documenting the measurement challenge; a bipartisan Senate bill (led by Sen. Mark Kelly, D-AZ, introduced June 2026) that would expand federal AI labor data collection; Yale Budget Lab's new monthly 'occupational churn' analysis as an early-warning system; Stanford DEL's ADP-based Canaries dashboard; and new Ramp/Revelio research finding companies using AI most intensely are adding jobs FASTER than laggards — the opposite direction from displacement narratives. Frames the current confusion as J-curve territory: companies still on the downward experimentation phase before productivity gains materialize. Notes federal statistical system is under stress from falling survey response rates and funding cuts; former BLS Commissioner Erika McEntarfer (fired by Trump last year) says $10M/yr would meaningfully expand the monthly labor market survey.
Projected US Job Displacement from AI by 2030
AI and Jobs: The Final Word (Until the Next One)
Economic Innovation Group (Nathan Goldschlag & Sarah Eckhardt)
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Jul 2026
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EIG applies five different measures of AI exposure (drawn from four different research papers) to test whether current labor market data shows an AI signature. The startling finding: which exposure measure you pick determines not just the SCALE but the DIRECTION of AI's estimated effect on employment. Under some measures AI appears to be hurting employment; under others it appears to be helping. Companion piece 'A New Threat to Economic Data' documents the deteriorating federal statistical system (falling response rates, funding cuts) that Casselman NYT (July 2) also foregrounds. Goldschlag is EIG's Director of Research and formerly Principal Economist at Census's Center for Economic Studies.
Projected US Job Displacement from AI by 2030
The Employment Situation — June 2026 (BLS Release, Jul 2, 2026)
US Bureau of Labor Statistics
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Jul 2026
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Tier
1
BLS Employment Situation, June 2026 (released July 2, 2026). Total nonfarm payroll employment changed little in June (+57,000), roughly in line with the average monthly change over the prior 12 months (+36,000). Unemployment rate 4.2% (dipped slightly). Health care +22,000 (below prior 12-month average of +38K); leisure and hospitality declined by 61,000 (weaker seasonal hiring). Prior months revised down: April -31K (to +148K), May -43K (to +129K); combined -74K. Average hourly earnings for private nonfarm payrolls +13 cents (0.3%), to $37.64. Wall Street had expected 115,000 jobs — actual well below.
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
BTOS 2026 AI Supplement — Full Biannual Data Release
US Census Bureau (BTOS AI Supplement)
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Jul 2026
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Tier
1
US Census Bureau BTOS 2026 AI Supplement (reference period Nov 17, 2025 - Feb 8, 2026; released 2026). Full biannual supplement replacing the biweekly two-week question with a six-month lookback plus new modules on task substitution, wage/employment effects, and planned adoption. Headline (Q1, 2-week): 17.9% of US businesses used AI in any function in the past two weeks (SE 0.13%). Use case incidence (6-month): sales/marketing 14.3%, strategy 12.4%, IT 11.4%, R&D 11.2%, PR/comms 9.3%. Task substitution: 10.1% used AI to perform a task previously done by an employee; 43.7% to supplement/enhance an employee task; 10.6% to introduce a new task. Of firms that substituted, 70.9% substituted 'a small number' of tasks, 22.0% moderate, 7.1% large. Employment effect: 95.7% report no change in total employment from AI use; 2.3% increased, 2.0% decreased. Generative AI specifically: 20.8% of firms report employees using GenAI at work in past six months; of those, 85.4% used for writing/editing, 49.9% for information search, 44.6% for translation/analysis, 34.7% for paperwork, 30.0% for new-project development. Sector leaders (Q1 two-week): Information 37.6%, Professional/Scientific/Technical 34.2%, Education 30.7%, Finance/Insurance 30.4%, Real Estate 23.5%. Six-month outlook: 21.6% expect to be using AI, with sales/marketing (62.8%) and strategy (57.4%) leading.
AI Adoption Rate Across US Companies
Customer Service Automation by 2028
Challenger Report: June Layoffs Cool to 45,849, Down 53% From May; AI Leads Reasons for Fourth Consecutive Month
Challenger, Gray & Christmas
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Jul 2026
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Tier
3
White-Collar Professional Displacement by 2030
Tech and Finance Sectors Losing 28,000 Jobs Monthly Show AI Impact on Labor
Bloomberg (Boesler & Prakash)
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Jul 2026
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Tier
3
Bloomberg (Boesler & Prakash, Jul 2 2026): 'A decline in payrolls in the financial-activities and information sectors — where AI adoption rates have been fastest — has accelerated in 2026, to 28,000 per month on average based on government data.' 'The weakness stands out against an otherwise robust labor market that created more than 113,000 jobs monthly this year through May.' Challenger data: 'almost 102,000 announced job cuts attributed to AI so far this year.' 'Overall, the tech sector accounted for a third of all layoffs announced in 2026.' Finance workforce: 'Office and administrative support occupations — including customer service representatives, bank tellers and insurance claims processors — account for about a quarter of employment in financial activities.' California Policy Lab: 'Finance and insurance had the highest concentration of unemployment claims in the state coming from workers in highly AI-exposed occupations.'
Financial Services Displacement by 2030
Projected US Job Displacement from AI by 2030
Tech Sector Displacement by 2030: Uneven by Experience Level
June 2026
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A New Look at AI's Impact on Jobs: Firm-Level AI Spending and Workforce Adjustment
Ramp Economics Lab / Revelio Labs (Ara Kharazian et al.)
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Jun 2026
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Tier
2
First study to link observed firm-level AI spending to workforce outcomes at scale. Tracked AI spending across 21,599 US firms via Ramp expense-management data, matched to Revelio Labs employment records. Companies that invest heavily in AI grew headcount 10% over the two years following adoption; entry-level headcount grew 12%. Gains are ENTIRELY driven by high-intensity adopters — low-intensity adopters see no statistically significant change. Direction is opposite to the displacement narrative: heavy AI adopters ADD jobs faster than laggards. Caveats: AI adopters are already larger, more engineering-intensive, more likely to be venture-backed, and faster-growing than non-adopters; effect may partly reflect selection into adoption rather than causal effect of adoption.
Projected US Job Displacement from AI by 2030
AI and the Supply and Demand for Labor
Bharat Chandar (What's Next Substack)
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Jun 2026
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Tier
3
Chandar — coauthor of the Brynjolfsson-Chandar-Chen 'Canaries' paper — explains why he was one of 5 of 16 economists on a WSJ panel to predict AI would cause net job loss (others: Acemoglu, Henderson, Restrepo, Wolfers; 8 said no change, 2 said net growth). All 16 agreed AI would boost productivity. The 5 net-loss economists also unanimously said AI would replace rather than complement workers and would reduce demand for white-collar jobs. Chandar's argument: his net-job-loss prediction is not a 'jobs bloodbath' story — he expects AI to make people rich enough (via capital income or transfers) that the income effect dominates the substitution effect, lowering labor force participation in the long run (~50yr horizon). He explicitly cites Kinder's 'messy middle' framing as the short-to-medium-run risk. Useful disambiguation of what economists mean by 'net job loss' — long-run LFP decline driven by post-scarcity income, not displacement-driven destitution.
Projected US Job Displacement from AI by 2030
The state of the creative industry 2026: what our survey tells us about pay, burnout and AI
Creative Boom
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Jun 2026
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Tier
3
Creative Boom's flagship 2026 survey of 882 creative professionals (UK/US-weighted; 43% with 10+ years experience): Nearly 47% of self-employed creatives earn less than £30,000 a year (vs UK median full-time salary of £39,039). 69% experienced burnout in past 12 months — mid-career 77%, early-career 74%, studio founders 59%. 50% feel less financially secure than a year ago; 38% considering a job change; 7.5% planning to leave the industry. 86% use AI tools in their work but only 10% believe AI's impact on the industry is positive; 58% describe it as mixed, 28% straightforwardly negative. 'Creatives aren't refusing to use AI; they're adopting it because they feel they have to.'
Creative Industry Displacement by 2030
The AI Jobs Transition Framework for the EU (Mapping Europe's AI Workforce Opportunity)
OpenAI Economic Research
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Jun 2026
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Tier
2
EU companion to OpenAI's April 2026 US AI Jobs Transition Framework, applied "across more than 2,600 ESCO occupations." "our EU analysis suggests that 12% of employment is in jobs that may grow with AI, 14% of employment is in jobs with higher automation potential, 27% is in jobs likely to reorganize, and 47% is in jobs with less immediate change." Explicitly benchmarked against the US: "The comparable U.S. report found 18%, 24%, 12%, and 46%, respectively. Europe therefore has a smaller higher-automation-potential share." Median price elasticity of a European occupation is about 0.7, so a 10% price decrease raises output roughly 7%. Cross-member-state variation is wide: higher automation potential ranges from 8.7% to 16.9%.
US Workforce AI Exposure
Anthropic Economic Index Report: Cadences (June 2026)
Anthropic Economic Index
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Jun 2026
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Tier
2
Anthropic's June 2026 Economic Index 'Cadences' report combines anonymized Claude usage patterns with a survey of ~9,700 Claude users. Headline findings: about half of surveyed users report AI can already handle 50% or more of their work tasks; 4% say Claude could perform their entire job today; more than one-third expect AI to do most or nearly all of their work tasks within 12 months. The report also documents a widening 'cadence' gap between experienced and newcomer Claude users — experienced users automate substantially more of their work. Biggest automation increases occur in business sales, automated trading, and routine market-research tasks, flagging those roles as near-term automation candidates.
Generative AI Adoption
The New Push to Ready Millions for AI Career Upheaval
The Wall Street Journal (Chip Cutter)
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Jun 2026
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Tier
3
A bipartisan consortium called RAISE US launches with a 'people strategy' for the AI era — led by former Commerce Secretary Gina Raimondo (CEO) and former Indiana Gov. Eric Holcomb. Founding employers include Amazon, Microsoft, Bank of America, and Eli Lilly; OpenAI and Anthropic are involved; MIT economist David Autor sits on the advisory board. The group has raised $500M+ (about half its multiyear goal) and will initially work with Arkansas, Maryland, Utah, and Connecticut. Mandate goes beyond retraining: revisiting unemployment insurance so displaced workers can keep benefits while starting AI-enabled businesses, and developing corporate incentives for employers to retain and reskill rather than lay off.
Projected US Job Displacement from AI by 2030
Are AI Certifications Worth It? What the Salary Data Shows
Revelio Labs (Loujaina Abdelwahed)
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Jun 2026
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Tier
2
Revelio Labs analysis of AI certifications recorded on workers' online professional profiles, built from a two-level taxonomy of over 500,000 unique AI-related certification names. "After controlling for occupation and seniority level, AI certification holders earn, on average, an $8,000 salary premium compared to non-certification holders." Revelio frames this as positive selection rather than a return to certification: "within any given occupation and seniority level, the workers choosing to get certifications are those who are already earning more than their peers." Certification share rose from 1-2% of all professional certifications pre-ChatGPT to nearly 30% by 2026, a 20x increase. A propensity-score-matched comparison finds certification takers see salary grow 18.1% in their next position versus 15.3% for non-takers.
High-Skill AI Wage Premium
The Age of the Solopreneur
Stripe Economics (Tedeschi, Rama & Cruickshank)
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Jun 2026
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Tier
2
Stripe Economics analysis of business formation and solo-founder scale. "In 2023, roughly four million Americans earned their primary income as solopreneurs, generating over $100,000 in annual revenue." "More than twice as many solopreneurs earned over $1 million in 2025 than in 2023" and "close to three times as many crossed $5 million and $10 million." On AI: "AI-influenced user journeys now constitute nearly 4x the share of Stripe sign-ups as last January." On formation: "Delaware incorporations have grown approximately 40% year over year since early 2025" and "New business registrations have risen roughly 40% in Australia, 70% in Finland, and 80% in France since 2017." The share of businesses reaching $1M cumulative revenue within a year was roughly 30% higher for the 2025 cohort.
AI-Driven New Business Formation
Human Capital, AI, and Labor Commoditization
UCLA Anderson School of Management (Siddiq & Zhang)
·
Jun 2026
·
Tier
1
Difference-in-differences study on 49,610 Upwork workers and 2.26M contracts (2021Q1–2026Q1) around the release of ChatGPT. Uses text embeddings of worker profiles and Shapley values to quantify the predictive importance of human capital signals (self-presentation, credentials, reputation) and price. In max AI-exposed categories vs. unexposed, contract volume fell ~7.0% post-ChatGPT (9.6% late period, 2025Q2–2026Q1); the combined importance of human capital signals fell 7.8% (10.1% late) while price importance rose 1.1% (1.8% late). Demand premium for high-human-capital workers compressed by 6.2% (10.3% late), and demand reallocated toward lower-priced workers by 3.2% (7.9% late). Authors interpret as empirical evidence of AI-driven labor commoditization — clients view differently-skilled workers as more substitutable when AI compresses output quality.
Freelancer/Gig Worker Rate Impact by 2028
US Workforce AI Exposure
Business Trends and Outlook Survey — AI Adoption (May 2026 wave, released Jun 18)
US Census Bureau (BTOS)
·
Jun 2026
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Tier
1
US Census Bureau Business Trends and Outlook Survey (BTOS) biweekly release Jun 18, 2026. As of the May 3, 2026 reference date: national AI use rate = 19.8% of responding businesses. Between Dec 2025 and May 2026 the national AI use rate hovered between 17% and 20%, with 20-23% of firms expecting to use AI in the next six months. Sector breakdown: Information 39.7%; Finance & Insurance 33.9%; Retail Trade ~14%. Sample: approximately 1.2 million businesses with biweekly data collection.
AI Adoption Rate Across US Companies
87 Percent of Creators Say Creative AI Is Growing Their Business and Audience, According to Adobe's 2026 Creators' Toolkit Report
Adobe (Creators' Toolkit Report / Harris Poll)
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Jun 2026
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Tier
2
Creative Industry Displacement by 2030
Agentic coding and persistent returns to expertise
Anthropic Economic Research (Hitzig, Massenkoff, Lyubich, Zhang, Heller, McCrory)
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Jun 2026
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Tier
1
Anthropic Economic Research (Hitzig, Massenkoff, Lyubich, Zhang, Heller, McCrory — Jun 16, 2026). Analysis of ~400,000 Claude Code sessions from ~235,000 users between Oct 2025 and Apr 2026. Verified success rates: 'Novice: 15%; Intermediate/Expert: 28-33%.' Partial success rates: 77% (novice) vs 91-92% (intermediate/expert). Abandonment when troubled: novice 19% vs intermediate+ 5-7%. 'Every one of the ten largest occupations in our dataset lands within seven points of software engineers' (29-34% verified success). 'The estimated value of the average session rose by 27% between October and April.' Division of labor: 'people make about 70% of the planning decisions but only 20% of the execution decisions.' Work mix: code writing/fixing/testing 56%, ops 17%, planning/exploration 14%, analysis/prose 13%. Novice: ~5 actions, 600 words output/prompt; Expert: ~12 actions, 3,200 words/prompt.
High-Skill AI Wage Premium
Tech Sector Displacement by 2030: Uneven by Experience Level
AI Is Probably Not (Yet) the Reason for Labor Market Weakening
Yale Budget Lab (Gimbel, Tedeschi)
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Jun 2026
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Tier
1
Yale Budget Lab's preferred econometric strategy finds no strong evidence of AI's impact on aggregate US employment or unemployment 33 months post-ChatGPT. Measures of AI usage show no detectable connection to changes in employment or unemployment. The labor market in early 2026 features low layoffs but also low hiring, with payroll growth ~20,000 net new jobs per month and unemployment 4.3% in March 2026. Authors caution that historically technological disruption unfolds over decades, not months — AI is likely to leave its mark eventually, but the macro signature is not yet visible. A companion to the lab's March 2026 CPS update.
Projected US Job Displacement from AI by 2030
PwC 2026 Global AI Jobs Barometer
PwC (Atkinson, Brown)
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Jun 2026
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Tier
2
PwC 2026 Global AI Jobs Barometer (Atkinson & Brown, Jun 15, 2026). Analyzed 1+ billion job advertisements across 27 countries and territories, including 2.4M entry-level US jobs. Key findings: entry-level roles most exposed to AI are 'seven times more likely to require traditionally senior-level skills'; job openings for 'seniorised' entry-level roles grew 35% since 2019 while other entry-level roles declined 10%. AI-skills wage premium reached 62% (up from 57% in the 2025 barometer), ranging from 16% (government) to 118% (consumer markets). AI-skill jobs growing 69% vs 9% for the total jobs market — 'almost twice as high as 2024.' Companies most exposed to AI: 52% headcount growth vs 36% (least exposed); wage growth 24% vs 17%; productivity 34% vs 24% (2018-2025), with the top-20% 'super-stars' at 163% productivity gain. 'Professionalised' roles growing twice as fast with 42% faster salary increases. Technology/media/telecom: 11% AI job share; health: <1%.
Entry-Level Wage Impact from AI by 2030
High-Skill AI Wage Premium
White-Collar Professional Displacement by 2030
Convention concerning decent work in the platform economy, 2026 (C193)
International Labour Organization
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Jun 2026
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Tier
1
The 114th International Labour Conference adopted Convention C193 on Decent Work in the Platform Economy on June 12, 2026 — the first legally binding international treaty dedicated entirely to regulating the digital platform economy. Attendance: 5,700+ delegates from 187 ILO Member States. The Convention extends fundamental rights (freedom of association, collective bargaining, protection from discrimination and forced labor), occupational safety and health, adequate remuneration, data protection, and algorithmic decision-review mechanisms to platform workers. It establishes global protections for more than 150 million workers who earn their living through digital labour platforms.
Freelancer/Gig Worker Rate Impact by 2028
Highest Number of S&P 500 Earnings Calls Citing “AI” Over the Past 10 Years
FactSet
·
Jun 2026
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Tier
1
Final full-season count for the Q1 2026 reporting period (calls conducted March 15 through June 11, 2026), by John Butters. "Overall, the term 'AI' was cited on 337 earnings calls conducted by S&P 500 companies during this period." "This number also reflects 68% (337 out of 498) of the earnings calls conducted by S&P 500 companies during this period." "This number is well above the 5-year average of 164 and the 10-year average of 103." Supersedes the May 8 in-season update (65%, taken at 89% reported), which was an interim rather than a final.
S&P 500 AI Workforce Mentions in Earnings Calls
Europe 2031 — What getting AI wrong means for us
Arq Foundation / Delta Institute (Juijn, van Baarsen, Dada, Stelling, Fox, Petropoulos, Bakker)
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Jun 2026
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Tier
3
An 18,000-word fictional five-year scenario (June 2026) by European AI researchers warning the EU risks becoming AI-dependent on the US or China by 2031. Puts Europe at 5% of global AI compute against ~80% for the US in the scenario. Three identified 2025 misjudgements drive the trajectory: underestimating AI's pace, underestimating its scope of change, and overestimating Europe's catch-up capacity. Scenario beats include a 2027 ransomware wave (open-source frontier model) hollowing out European cybersecurity, US and Chinese firms acquiring distressed European carmakers and machine-tool makers, and conversion of factory floors to robot production. Narrative form (two protagonists in Brussels and Silicon Valley), not policy paper. Positioned in the Yelizarova Economic Futures Map at 'concentrated gains, strong replacement.'
The Hidden Workers Most Threatened by A.I.
The New York Times (Ben Casselman)
·
Jun 2026
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Tier
3
many economists are more concerned about a different, larger group of white-collar workers: customer service representatives, bookkeepers, payroll clerks and human resources specialists who fly under the radar but collectively account for tens of millions of jobs.
Healthcare Administrative Displacement by 2030
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
Stanford DEL Canaries Dashboard: April 2026 Update
Stanford Digital Economy Lab / ADP Research
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Jun 2026
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Tier
1
Monthly-updated dashboard built on anonymized ADP payroll data covering 4.6 million workers across 730+ occupations. April 2026 reading: most AI-exposed occupations contracted 0.2% YoY, least-exposed grew 0.1% YoY — a small but consistent gap. For workers ages 22-25 in highly AI-exposed occupations, employment is now shrinking at 3.8% per year, with the early-career decline sharpening from -2.8% to April 2024 to over -4% per year since. Builds on Brynjolfsson, Chandar, Chen (2025) 'Canaries in the Coal Mine.' Live update of the underlying employment story behind the 'overall not yet, early-career already' pattern.
Projected US Job Displacement from AI by 2030
Tech Sector Displacement by 2030: Uneven by Experience Level
2026 EDUCAUSE Workforce Report: How Teams Are Adapting to AI, External Pressures, and Strategic Change
EDUCAUSE
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Jun 2026
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Tier
2
EDUCAUSE's 2026 Workforce Report examines how higher-education technology and data teams are adapting to AI, financial pressures, and shifting institutional priorities. The report draws on survey and focus-group data to trace how external forces reshape institutional strategies, roles, critical competencies, and skills. Central themes: AI strategy, rising workloads, and expanding team responsibilities are reshaping the workforce. The report is designed for higher-ed leaders, managers, and professionals navigating workforce change driven by AI, financial pressures, and evolving institutional needs.
Education Sector Displacement by 2030
Amazon unveils latest warehouse robot as tech giants continue AI layoffs
CNBC
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Jun 2026
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Tier
3
Amazon unveiled next-generation Proteus, an autonomous mobile robot that takes commands in conversational language, at its 'Delivering the Future' event in London. The original Proteus, deployed since 2022, is now in 25 U.S. fulfillment centers, with the new version rolling out in Europe in H1 2027. Amazon has eliminated 30,000 corporate positions since October as it prioritizes AI initiatives. Amazon UK/Ireland VP John Boumphrey told CNBC: 'our experience of robots is that it's driven up employment rather than the reverse.'
Robots & Physical Automation Displacement by 2030
US Tech Sector Cut 38,242 Jobs in May, AI Most Cited Reason for Layoffs
tomshardware.com
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Jun 2026
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Tier
4
US Tech Sector Cut 38,242 Jobs in May, AI Most Cited Reason for Layoffs
Tech Sector Displacement by 2030: Uneven by Experience Level
SAG-AFTRA Ratifies Four-Year Deal With Studios and Streamers
Hollywood Reporter
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Jun 2026
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Tier
3
SAG-AFTRA members ratified a four-year deal with the AMPTP on June 4, 2026 — 91.42% approved, 8.58% opposed, 19.25% turnout. AI protections: 'synthetic AI-generated performers may only be used when they provide significant additional value to a project'; studios must have 'an articulable business reason' to scan a performer for a digital replica; minimum payment rates and residuals apply to independently created digital replicas; digital replicas cannot be used to circumvent strike participation. Minimum wage increases 3% annually; health plan contribution rises 1% July 1. Pension plan merger targeted for Jan 1, 2028. Deal effective July 1, 2026 through June 30, 2030.
Creative Industry Displacement by 2030
LLM Exposure and Precarious Occupations: Evidence from the Canadian Labor Force
Scandinavian Journal of Work, Environment & Health
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Jun 2026
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Tier
1
occupations characterized by low exposure to precarity had a significantly higher mean LLM exposure [mean 0.386, 95% confidence interval (CI) 0.356–0.417]
US Workforce AI Exposure
The Growth and Performance of Artificial Intelligence in Asset Management
NBER (Shuang Chen, Clemens Sialm, David X. Xu)
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Jun 2026
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Tier
1
AI-driven investing has grown steadily since the early 2010s and is concentrated among hedge funds. Average AI labor intensity is 1.17% of job postings at SEC-registered investment advisers. AI hedge funds peaked at ~2.7% of all hedge funds in 2023.
AI Adoption Rate Across US Companies
The AI Economic Indicators
Stanford Digital Economy Lab
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Jun 2026
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Tier
2
Stanford Digital Economy Lab Research Note #1: AI Economic Indicators June 2026 Update (Brynjolfsson, director). Three linked dashboards: (1) Canaries — 5-year balanced ADP payroll sample of 25,000 firms, 4.6M workers, 730+ occupations. Across all ages, most-exposed occupations growing 1.1%/yr vs 2.0%/yr for least-exposed since ChatGPT. For early-career workers (22-25, 7.4% of sample), most-exposed occupations contracting 3.8%/yr vs +2.0%/yr for least-exposed. The AUTOMATION ratio (using Anthropic Economic Index) correlates with employment declines; the augmentation ratio does not. Software developers and customer service reps show substantial early-career declines; home health aides grow. (2) Takeoff Tracker — 12 aggregate US indicators of AI-driven takeoff. As of May 2026: 7 show no evidence, 3 mild, 2 strong. Capital share = strong evidence (persistent upward trend); TFP growth = neutral (no break from recent levels); IP equipment share of private nonresidential equipment = mild (recovering to early-2000s levels). 'No decisive evidence of takeoff.' (3) Adoption Monitor — individual work adoption trending up in most surveys but reversing in some recent workplace data; firm adoption widespread and US-led; robotics and autonomous vehicles show largest current-vs-expected adoption gaps.
Projected US Job Displacement from AI by 2030
US Workforce AI Exposure
The Reverse Centaur's Guide to Life After AI
Farrar, Straus and Giroux (Cory Doctorow)
·
Jun 2026
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Tier
4
Doctorow's book-length argument that AI is mostly deployed not to automate work but to put workers into 'reverse centaur' configurations — humans serving as helpers to machines at inhuman pace (delivery drivers, warehouse pickers, AI-supervised coders). Argues the $16T+ AI investment thesis only makes sense if AI replaces vast swathes of the wage-earning workforce, and that workers, not 'AI-enjoyers,' are the political constituency for resisting that path. Companion talk delivered at University of Washington Neuroscience-AI-Society lecture series. Positioned in the Yelizarova Economic Futures Map at 'concentrated gains, strong augmentation' (augmentation in the cynical sense — humans augmenting machines, not the reverse).
Goldman Sachs Revised Forecast: ~9% / 15M US Workers Displaced over 10 Years
Goldman Sachs Research (Joseph Briggs)
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Jun 2026
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Tier
2
Goldman Sachs revised its US labor displacement forecast upward from 6-7% to ~9% (about 15 million workers) over the next decade. The change reflects a new methodology measuring total flow of workers leaving jobs due to AI-driven productivity gains, rather than steady-state unemployed count. Briggs estimates each 1% increase in technology-driven productivity yields a 0.5-0.6% increase in the job-destruction rate over the following two years. Goldman maintains the long-run benefits outweigh the disruption (US churns 25-35M jobs annually, and AI will generate new employment), and that unemployment rises less than 1 percentage point at peak under standard adoption timing. As of mid-2026, Goldman estimates AI is erasing ~16,000 net jobs per month, concentrated in entry-level and administrative roles.
Projected US Job Displacement from AI by 2030
May 2026
30
source
s
Connecticut Enacts AI Responsibility and Transparency Act (SB 5)
Bloomberg Law / State of Connecticut
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May 2026
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Tier
3
Connecticut SB 5 requires employers filing WARN Act notices to disclose whether layoffs are related to AI (effective Oct 2026), and requires notice to employees/applicants when automated systems are a substantial factor in hiring, promotion, discipline, or discharge (effective Oct 2027).
US Workforce AI Exposure
A.I. Doesn't Have to Mean Layoffs
The New York Times (Patricia Cohen)
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May 2026
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Tier
3
In the last three months of 2025, call centers fielded 150,000 questions. Three-quarters of the time, A.I. was able to provide the right answer to straightforward questions. The agent then reviews and if necessary, modifies and refines the answer with the caller.
Customer Service Automation by 2028
Solo founding is at an all-time high: Top performers have these traits in common
Stripe Atlas (Jesse Carey)
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May 2026
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Tier
2
Stripe Atlas (Jesse Carey, May 28 2026). Analysis of thousands of solo-founded Atlas startups incorporated 2022-2023 with 2+ years of revenue data. Headline: solo founders account for '63% of C corps formed so far in the second quarter of 2026 — an all-time high.' Revenue split: median solo-founder revenue -23% YoY in 2025; top-decile +19%. Top decile earns 61x median (vs 34x four years prior). Top-decile founders sold into 10 countries in month 1 (vs 3 for median) and 40 non-US countries by month 24. International revenue share: 51% top-decile vs 2% median. Top-decile month-one retention 29% vs 8% middle-decile. AI angle: 'Top-decile founders approximately twice as likely building AI-native companies'; AI-native startups generated nearly 2x revenue of non-AI at month 24. Top founders 20-26pp more likely to use recurring-billing models.
AI-Driven New Business Formation
Coding agents in the social sciences
Anthropic Economic Research (Lyttelton, Massenkoff, Wilmers)
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May 2026
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Tier
1
Anthropic Economic Research (Lyttelton, Massenkoff, Wilmers — May 27, 2026). Survey of 1,260 quantitative social scientists. '81% of respondents said yes' to using generative AI to aid research. '20% of respondents use coding agents' regularly (weekly). '86% of users reporting Claude Code use.' Demographic disparities: 'those with typically male names have adopted coding agents at more than twice the rate of respondents with typically female names.' Career stage: 'Just over a quarter of doctoral students and postdocs use coding agents' vs tenured professors at less than half that rate. University prestige: 'Researchers at top universities are 40% more likely than others to use coding agents.' Task usage: '97% of coding agent users and 77% of other AI users report using it to generate code.' Productivity effects over 6 months: users show approximately 'a quarter of a paper more' in project starts and 'around a half of a working paper more' in working papers, but 'no evidence that coding agent users are submitting more new papers to journals.' '88% of respondents were above a 5' on 10-point AI productivity scale.
Generative AI Adoption
US Workforce AI Exposure
Large Firms With at Least 20 Employees Biggest AI Users
US Census Bureau
·
May 2026
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Tier
1
US Census Bureau analysis of BTOS data collected December 14, 2025 to May 3, 2026. Documents a break in the AI-use question: “Originally framed around AI use ‘in producing goods or services,’ rather than to carry out simple tasks like drafting emails, the Census Bureau revised the wording last November to ask businesses whether they were using AI ‘in any business function.’” On November 17, 2025 BTOS began its second AI supplement and revised the core AI use questions. Over the period “overall AI usage hovered between 17% and 20% — and that between 20% and 23% of businesses expected to be using it in the next six months.” The national rate was 19.8% as of May 3, 2026, against 39.7% in Information and 33.9% in Finance and Insurance. Adoption rises with firm size: 37% of firms with at least 250 employees, 32% of firms with 100 to 249 employees, and under 20% of firms with four or fewer employees.
AI Adoption Rate Across US Companies
I'm the C.E.O. of Goldman Sachs. The A.I. Job Apocalypse Is Overblown.
The New York Times (David M. Solomon, CEO Goldman Sachs)
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May 2026
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Tier
3
Goldman Sachs's economists estimate that, over the next decade, A.I. may automate 25 percent of current work hours. If our estimate proves correct, A.I. won't eliminate 25 percent of jobs. What's more likely is that people will find more productive ways to spend their time. American companies destroy and create between 25 million and 35 million jobs annually.
Early-Career Employment Decline in AI-Exposed Occupations
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
Half of current customer service jobs will be lost to AI by 2030, Forrester predicts
Forrester (via CX Dive; analysts Kate Leggett & Laura Ramos)
·
May 2026
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Tier
2
Customer Service Automation by 2028
Solopreneurs, Solow, and the SaaSpocalypse
Stripe Economics (Ernie Tedeschi)
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May 2026
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Tier
2
Stripe Economics (Ernie Tedeschi, May 19 2026). New business applications rising worldwide with US divergence between total applications and 'high-propensity' employment-generating filings. Stripe Atlas data: 'startups have accelerated since 2023, and especially in the first quarter of 2026' — 'overwhelming[ly]' driven by solo founders across both AI and non-AI ventures. SaaS market context: 'Over 30 days in early 2026, the software sector shed roughly $1 trillion in market capitalization,' but weekly transactions for the 100 largest non-AI SaaS companies on Stripe showed 'a brief dip followed by a swift recovery' — the SaaSpocalypse was expectations-driven, not economic-activity-driven. Historical framing: post-electrification (1882), inflation-adjusted output per worker grew just 0.5%/yr for three decades before productivity 'more than doubled' in the decade after 1917; PCs showed 'gains everywhere except the productivity statistics' (Solow 1987) with visible productivity acceleration mid-1990s.
AI Adoption Rate Across US Companies
AI-Driven New Business Formation
The Broken Ladder: AI, Remote Work, and Early-Career Hiring
Lambert & Schindler (SSRN)
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May 2026
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Tier
1
Lambert & Schindler (2026, SSRN 6787638) find declines in the junior hiring share in AI-exposed jobs, replicating the Canaries pattern — BUT show these patterns can be explained by exposure to remote work, not AI per se. A key counter-evidence paper cited in Stanford DEL Research Note #1 as one of the candidate confounds in the current debate over whether the entry-level employment decline is causally attributable to generative AI adoption.
Entry-Level Wage Impact from AI by 2030
Do Job Postings Show Early Labor-Market Effects of AI?
Federal Reserve Bank of New York — Liberty Street Economics (Audoly, Guerin, Topa)
·
May 2026
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Tier
1
While job postings show a relative decline in vacancies in occupations with greater exposure to AI, that divergence began before the release of ChatGPT in late 2022. These patterns make it difficult to attribute the recent slowdown in entry-level hiring to AI alone.
AI Adoption Rate Across US Companies
Projected US Job Displacement from AI by 2030
2026 New Business Formation Report: How AI Is Reshaping Who Starts a Business
Gusto
·
May 2026
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Tier
2
Gusto 2026 New Business Formation Report (May 2026, 6th annual). '60% of new business owners used AI to help launch their business in 2025' — nearly 3x the 21% in 2023. Among AI-using founders: 75% used it to develop business ideas, 53% for administrative/legal tasks, 51% for setting up operations. Industry adoption: Professional Services 56% (highest); Goods-Producing 43%; Community Services 36%. Generational: 71% of Gen Z founders vs 42% of Boomers used AI. Growth linkage: 49% of AI-using new businesses plan headcount growth in 2026 vs 41% of non-AI-using — 'AI adoption is associated with growth rather than job displacement.' Gusto also reports Gen Z entrepreneurs outnumber Boomers in new business starts for the first time.
AI-Driven New Business Formation
AI Coding Agents Redistribute Work Across Pull Request Lifecycles
arXiv (Jo, Chung, Hassan)
·
May 2026
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Tier
2
Analysis of 29,585 PR lifecycles across 5 major AI coding tools using an Initiator x Approver taxonomy. Collaborator workflows are >=96% agent-initiated, yet terminal merge authority remains almost exclusively human, with agent-classified approvers confined to a small fraction of PRs.
Tech Sector Displacement by 2030: Uneven by Experience Level
AI Will Not Destroy the Job Market
DeepLearning.AI (Andrew Ng)
·
May 2026
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Tier
3
despite all the exciting progress in AI, the U.S. unemployment rate remains a healthy 4.3%
Projected US Job Displacement from AI by 2030
S&P 500 Earnings Season Update — Q1 2026 (AI mentions)
FactSet
·
May 2026
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Tier
2
FactSet S&P 500 Q1 2026 earnings-season update (published May 8, 2026 with 89% of S&P 500 having reported actual Q1 results). AI citations: 'about 65% of S&P 500 earnings calls have cited the term AI so far,' slightly below the prior quarter's 68% (which was the highest percentage going back at least five years). AI remains substantially elevated vs historical levels. Overall Q1 2026 earnings performance: 84% of reporting companies beat EPS estimates; aggregate earnings 18.2% above estimates. Co-trending terms: 'Middle East' and 'oil' both at 5-year highs alongside AI.
S&P 500 AI Workforce Mentions in Earnings Calls
What We Do and Don't Know About How AI is Affecting the Labor Market
The Budget Lab at Yale (Gimbel, Kendall, Nunn)
·
May 2026
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Tier
1
Synthetic differences-in-differences (SDID) comparing AI-exposed (top tercile) vs. a synthetic comparison group of unexposed (bottom tercile) occupations through 2026Q1. Finds 'no clear evidence of AI effects on the labor market' for employment shares or real hourly wages. Unemployment in latest quarter ~0.5pp higher for AI-exposed (more for 16-34 subsample) but statistically insignificant. Demographic differences make naive comparisons unreliable: AI-exposed occupations are 55.1% women and 57.3% BA+ vs. unexposed 32.7% and 10.3%. Treatment date 2022Q4 (ChatGPT release). Caveats noted: LLMs improve over time, exposure metrics may misclassify, CPS underpowered for 22-27 cohort.
Early-Career Employment Decline in AI-Exposed Occupations
Entry-Level Wage Impact from AI by 2030
Median Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
Generative AI in Daily Business Practice: Synthesis of Micro-Level Firm Evidence
Maastricht University (Fregin, Eijkenboom, Özgül-Persyn, Pardesi, Rounding — DOI 10.26481/umarpb.2026002e)
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May 2026
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Tier
1
Synthesis of micro-level firm evidence finds generative AI already embedded in everyday business practice. Productivity gains in the near term come from task reallocation and upskilling rather than headcount reduction, with high-skill workers who effectively augment their output capturing a widening wage premium. The brief cautions that this benign short-run picture may mask longer-run structural displacement.
High-Skill AI Wage Premium
The "AI Job Apocalypse" Is a Complete Fantasy
a16z (David George)
·
May 2026
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Tier
3
AI-as-augmentation out-mentions AI-as-substitution on earnings calls by ~8:1. Software Development jobs (both by count, and a percent of the overall job market) have been increasing since the beginning of 2025. The aggregate effects of AI on employment are "basically null" per recent academic research, with some evidence of reallocation between jobs and tasks.
S&P 500 AI Workforce Mentions in Earnings Calls
Tech Sector Displacement by 2030: Uneven by Experience Level
US Daily: Forecasting Productivity Growth: Slow to Adjust, Quick to Overshoot
Goldman Sachs client-distributed research note; no public URL. Findings sourced from excerpted reporting.
Goldman Sachs
·
May 2026
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Tier
2
responses to a recent survey suggest that most forecasters are quite optimistic about AI's potential but are assuming only a slow pace of AI adoption through 2030
Generative AI Adoption
Median Wage Impact from AI by 2030
AI's big messaging pivot
Noahpinion (Noah Smith)
·
May 2026
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Tier
3
Major AI industry figures (Altman, Jensen Huang, Andreessen) are pivoting from displacement-focused messaging to augmentation-focused messaging amid deteriorating public opinion on AI. The new pitch: AI will create new tasks in the short term (task creation, Jevons Paradox), and in the long term humans will be paid for the 'relational sector' where the human element is the product itself. Noah Smith cautiously endorses the new pitch as better PR and potentially self-fulfilling for research direction, while noting it may be partly competitive positioning by OpenAI against Anthropic.
Discursive Construction of the Expert Gig Economy by Leading AI Labs
Wolfe & Dangol (arXiv, DOI 10.1145/3808045.3808063)
·
May 2026
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Tier
1
Analysis of public communications from five major AI labs finds a consistent narrative framing domain experts as interchangeable data suppliers rather than irreplaceable professionals. The reframing creates a cheap-expertise gig economy with downward pressure on credentialed knowledge-worker wage premiums and freelancer rates.
Freelancer/Gig Worker Rate Impact by 2028
Did US Worker Retraining Reduce Participant Automation Exposure?
arXiv (Julian Jacobs, Oxford/DeepMind; Jordan Canedy, FRI)
·
May 2026
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Tier
2
WIOA rarely supports worker resilience to automation, with 45% of all WIOA participants returning to their prior industry of work, and 27% staying in the same occupation. Successful outcomes driven mostly by wage gains, possibly due to catch-up mean reversion, rather than changes in occupation.
Median Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
What Jobs Can AI Learn? Measuring Exposure by Reinforcement Learning
arXiv (Tomei & Klein Teeselink, AI Objectives Institute / King's College London)
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May 2026
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Tier
1
Construct a new index based on reinforcement learning (RL) covering every occupation in the U.S. economy. Scoring all 17,951 O*NET tasks across 894 occupations on eight dimensions of RL-training feasibility. A difference-in-differences analysis finds that a one-SD increase in RL exposure is associated with a 2.9% decline in job openings after ChatGPT's release.
Entry-Level Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
US Workforce AI Exposure
The Real Job Destruction from AI Is Hitting Before Careers Can Start
Yale Insights / Yale Chief Executive Leadership Institute (Sonnenfeld, Henriques, Griessel, Alam-Nist, Yu)
·
May 2026
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Tier
2
White-Collar Professional Displacement by 2030
Entry-Level Hiring in the AI Era: What Employers Are Thinking (and Doing)
Strada Institute for the Future of Work
·
May 2026
·
Tier
2
Strada Institute surveyed 1,498 US executives and senior talent leaders (Mar 3-22, 2026). 46% of employers that have at least explored AI say it increased entry-level hiring in 2025 vs 13% decrease (4-to-1); 2.7x more expect AI to raise than cut entry-level hiring in 2026. 92% are engaging with AI in some way; AI literacy is ranked the least important entry-level skill.
AI Adoption Rate Across US Companies
Customer Service Automation by 2028
White-Collar Professional Displacement by 2030
Who Uses AI? Platforms, Workforce, and AI Exposure
arXiv (Yin & Ogut)
·
May 2026
·
Tier
2
Reweighting to Bureau of Labor Statistics workforce shares attenuates estimates by 42 to 93 percent.
US Workforce AI Exposure
The Messy Middle
Molly Kinder (Brookings; personal Substack)
·
May 2026
·
Tier
3
Kinder predicts a long, hard 'messy middle' between today's mostly intact labor market and any post-AGI abundance. In that period, most jobs survive but losses concentrate in some of the best-paid, most coveted jobs — cognitive computer work in offices and professional sectors, which are exactly the roles that have grown the most as a share of the US labor force over the last 50 years. Frames these concentrated losses as politically explosive. Her rule of thumb: 'if you can do your job locked in a closet with a computer, you're probably in trouble.' Positioned in the Yelizarova Economic Futures Map at 'concentrated gains, strong replacement.'
AI Is Changing Creative Work, but the Arts Aren't Disappearing
Gallup (with Journal of Cultural Economics)
·
May 2026
·
Tier
2
Creative Industry Displacement by 2030
Generative AI Adoption Tracker — May 2026 Update
Bick, Blandin, Deming (Real-Time Population Survey)
·
May 2026
·
Tier
1
Generative AI Adoption Tracker (Bick, Blandin, Deming), May 2026 update: '45.2% of the employed respondents used genAI for work.' Based on the Real-Time Population Survey (RPS), a nationally representative online labor market survey of US adults 18-64 running continuously since 2020. Tracker visualizes findings from 8 combined survey waves encompassing approximately 40,000 respondents, weighted to be nationally representative.
Generative AI Adoption
AI in revenue cycle is delivering results across healthcare
Oliver Wyman
·
May 2026
·
Tier
2
Oliver Wyman finds '63% of healthcare organizations have already integrated AI-powered automation into their revenue cycle workflows.' Studies show 'up to nearly 46% reductions in coding time for complex cases' and clinical accuracy 'hit 90% or higher in specific clinical domains.' 80% of health systems are actively exploring, piloting, or implementing generative AI tools for RCM — a 38-percentage-point increase over less than two years. The survey encompassed over 200 decision-makers and 90 end users across US provider organizations. AI addresses long-standing friction points such as documentation burden and coding variability.
Healthcare Administrative Displacement by 2030
Stripe Atlas hits 100,000 all-time incorporations; Q1 2026 +130% Y/Y
Stripe Atlas
·
May 2026
·
Tier
2
Official Atlas announcement: Q1 2026 incorporations up 130% year-over-year, 100,000 all-time incorporations; all Delaware incorporations up 38% year-over-year. Population-gated to overlay: Atlas counts confounded by platform market-share growth (~25% of Delaware C corps).
AI-Driven New Business Formation
April 2026
44
source
s
The A.I. Fear Keeping Silicon Valley Up at Night
The New York Times (Jasmine Sun, Opinion)
·
Apr 2026
·
Tier
3
When we originally released GDPVal, which was just a few months ago, none of the models were yet on par with human experts. Months later, we have over an 80 percent win rate compared to human professionals.
US Workforce AI Exposure
Fiverr Announces First Quarter 2026 Results
Fiverr International Ltd. (SEC Filing / Press Release)
·
Apr 2026
·
Tier
1
Freelancer/Gig Worker Rate Impact by 2028
How (un)Stable Are LLM Occupational Exposure Scores? Evidence from Multi-Model Replication
nber.org
·
Apr 2026
·
Tier
1
Replicating the dominant rubric with three frontier models on identical tasks, we find a 3.6-fold divergence in mean exposure with agreement as low as 57%.
Projected US Job Displacement from AI by 2030
US Workforce AI Exposure
Shaping Human Capital and Work Practices in a Changing Labor Market
Maastricht University (Anna-Lena Wittich)
·
Apr 2026
·
Tier
2
The research highlights a growing divergence between workers who can complement AI tools and those whose skills are substituted by them, amplifying within-occupation wage inequality.
High-Skill AI Wage Premium
The task is not the job: A supply-side answer to Amodei and Imas
Silicon Continent (Luis Garicano)
·
Apr 2026
·
Tier
3
A job is a bundle of tasks. The real question is not whether AI can perform one component of the bundle. It is whether that component can be separated from the rest at low cost... In 2013, a study by Carl Frey and Michael Osborne put the probability that accountants and auditors would be automated at 94 percent. A decade later, the US Bureau of Labor Statistics counts 1.6 million accountants and auditors employed, median pay of $81,680, and projects the occupation to grow another 5 percent through 2034... the argument that 'half of entry-level white-collar jobs be gone in five years' confuses task automation with the extinction of jobs.
Entry-Level Wage Impact from AI by 2030
Financial Services Displacement by 2030
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
What Makes New Work Different from More Work?
MIT Stone Center / NBER (Autor, Chin, Salomons, Seegmiller)
·
Apr 2026
·
Tier
1
Between 2011-2023, 18% of US workers were employed in jobs introduced since 1970. The wage premium is four times larger for new work associated with technological change than for other types of new work. The labor share has declined 10% in the US since the early 2000s.
High-Skill AI Wage Premium
Median Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
Measuring and Mitigating Persona Distortions from AI Writing Assistance
arxiv.org
·
Apr 2026
·
Tier
1
Hundreds of millions of people use artificial intelligence (AI) for writing assistance.
Generative AI Adoption
What 81,000 people told us about the economics of AI
Anthropic (Massenkoff, Huang)
·
Apr 2026
·
Tier
2
Survey of 80,508 Claude.ai users (personal accounts). One fifth voiced concern about economic displacement. Perceived job threat correlated with observed exposure: for every 10pp increase in exposure, perceived threat increased by 1.3pp; top-quartile exposure workers mentioned worry 3x as often as bottom-quartile. Early-career respondents much more likely to express concern than senior workers. Mean productivity rating 5.1/7 ('substantially more productive'); 3% reported negative or neutral impacts, 42% no clear indication. 48% of users mentioning productivity cited scope (new tasks), 40% speed. Management occupations (mostly entrepreneurs) and computer/math groups showed largest gains; scientific and legal professions the mildest. 10% of respondents naming a beneficiary said employers/clients capture the surplus; only 60% of early-career workers said they personally benefited vs 80% of senior professionals. U-shaped relationship between reported speedup and perceived job threat: both those slowed and those sped up most are more anxious.
Generative AI Adoption
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
US Workforce AI Exposure
AI and the UK Labour Market: The Evidence So Far
Centre for British Progress (Dr Pedro Serôdio)
·
Apr 2026
·
Tier
2
Three years after generative AI reached the market, there is no detectable employment effect for the most exposed occupations on UK data, regardless of which exposure metric is used. The estimates are noisy, the confidence intervals are wide, and neither measure produces a statistically distinguishable effect on aggregate employment.
The Microstructure of AI Diffusion: Evidence from Firms, Business Functions, and Worker Tasks
US Census Bureau — Center for Economic Studies (Bonney, Breaux, Dinlersoz, Foster, Haltiwanger, Pande)
·
Apr 2026
·
Tier
1
18% of firms used AI in a business function, rising to 32% on an employment-weighted basis. In 23% (41%, employment-weighted) of firms, workers use AI in work-related tasks. Most users (66%) rely on AI solely to augment tasks, while AI-related employment decreases are rare, occurring in only 2% of firms.
AI Adoption Rate Across US Companies
Generative AI Adoption
Projected US Job Displacement from AI by 2030
US Workforce AI Exposure
A Technology-Driven Productivity Regime Shift
The Burning Glass Institute (Gad Levanon)
·
Apr 2026
·
Tier
3
U.S. labor productivity growth has accelerated, rising from 1.3% per year in the pre-pandemic expansion (2013–2019) to 2.2% in the post-pandemic period (2019–2025). Three technology-exposed groups — white-collar services, retail trade, and advanced manufacturing — are posting 3.2% to 3.9% annualized productivity growth. The rest of the private economy is at 0.1%. The pressure is likely to emerge first in entry-level white-collar work, where the same industries posting the strongest productivity gains are also showing weaker demand for junior labor.
Entry-Level Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
Tech Sector Displacement by 2030: Uneven by Experience Level
White-Collar Professional Displacement by 2030
The Carlyle Compass: Software do we go now
Carlyle (Jason Thomas, Head of Global Research & Investment Strategy)
·
Apr 2026
·
Tier
2
Our proprietary survey of AI integration efforts finds that only 11% of management teams expect AI to replace existing software subscriptions. Far more expect the move to AI-centric architectures to reduce maintenance spending on legacy infrastructure, save on consulting fees, and increase the productivity of existing workers, reducing future headcount needs. Figure 4: Internal headcount cited as AI spending offset by 26% of respondents — the largest single category; IT services/consultants cited by 22%.
AI Adoption Rate Across US Companies
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
Declining Occupations and Career Outcomes in Norway
NBER (Barth, Hoen, Kerr, Kerr)
·
Apr 2026
·
Tier
1
Workers initially employed in occupations that later decline by at least 25% demonstrate 0.4 lower future years of work, although this employment difference is mostly explained by other individual traits. These workers, conditional on controls, experience a 4.7% reduction in future cumulative earnings relative to starting earnings, akin to losing one year's worth of earnings over 2007–2024.
Median Wage Impact from AI by 2030
White-Collar Professional Displacement by 2030
Labor Automation Forecasting Hub
Metaculus / Renaissance Philanthropy / Schultz Family Foundation
·
Apr 2026
·
Tier
2
Metaculus community forecasts for 2030 and 2035: overall US employment -1.9%/-3.4%; most vulnerable AI-exposed occupations -11.4%/-17.2%; software developers -15.1%/-22.3%; financial specialists -8.1%/-15.3%; services sales -11%/-14%; lawyers -5.4%/-9.6%; designers -4%/-8.4%; K-12 teachers -1.3%/+1.3%; overall median wage -0.6%/+1.4%; percent workers using AI daily 52.5%/70.9%; new-grad unemployment ~10%/12%.
Creative Industry Displacement by 2030
Customer Service Automation by 2028
Education Sector Displacement by 2030
Entry-Level Wage Impact from AI by 2030
+
6
more
The AI Jobs Transition Framework: Mapping AI's Near-Term Impact on Jobs
OpenAI Economic Research (Alex Martin Richmond)
·
Apr 2026
·
Tier
2
All 921 occupations (147.9M jobs) sort into four categories: 18% are at a higher short-term automation risk, 46% are less likely to experience near-term change, 12% could grow because of AI, and 24% may see declining employment as their task composition shifts but remaining jobs will still need workers. ChatGPT is used about 3x more in the kinds of jobs our framework identifies as most at risk of automation. Capability overhang by archetype: high-automation-risk jobs show 23.8% realized vs 90.0% theoretical exposure (66.2pp gap); jobs that grow with AI 22.7% vs 72.4% (49.7pp); reorganize 14.9% vs 67.1% (52.3pp); less immediate change 6.4% vs 27.4% (21.0pp). Since 2024Q1, unemployment rose most in jobs we predict to have less immediate change (+0.6pp) vs +0.3pp in higher-automation-risk, reorganize, and grow-with-AI groups — underscoring that exposure alone is a weak predictor of immediate labor market pressure.
Generative AI Adoption
Projected US Job Displacement from AI by 2030
US Workforce AI Exposure
Observed AI Use at Work
It's not 'bad marketing' from A.I. companies
Slow Boring (Matthew Yglesias)
·
Apr 2026
·
Tier
4
What A.I. company executives are saying about their products — that they might lead to human extinction and almost certainly will lead to large-scale permanent disemployment — is so obviously 'bad messaging' that I would really urge people to consider that it's not a 'message' at all.
Projected US Job Displacement from AI by 2030
You're (not) hired: Artificial intelligence and early career hiring in the Quarterly Workforce Indicators
US Census Bureau (Lee C. Tucker)
·
Apr 2026
·
Tier
1
Regression-adjusted employment of early career workers in the most AI-exposed quintile of industry-state cells declined by 12% over the 10 quarters following the introduction of ChatGPT, even as employment in less-exposed industries has remained stable. I find that hires of these early career workers declined immediately by 9% in comparison with those in less exposed industries, and that they have not recovered over time.
AI Adoption Rate Across US Companies
Early-Career Employment Decline in AI-Exposed Occupations
Entry-Level Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
+
3
more
Tracking the Impact of AI on the Labor Market
The Budget Lab at Yale (Gimbel, Kendall, Kulsakdinun)
·
Apr 2026
·
Tier
1
The addition of the March 2026 CPS and the introduction of Anthropic's February usage metrics do not suggest any substantial changes. Occupational dissimilarity, industry dissimilarity, and our exposure and usage metrics all remain flat, lie within historical ranges, or continue along the trends they were already exhibiting. Currently, measures of exposure, automation, and augmentation show no sign of being related to changes in employment or unemployment.
Projected US Job Displacement from AI by 2030
US Workforce AI Exposure
UnityPoint Health to lay off 207 IT employees
Business Record (Iowa) / UnityPoint Health / Becker's Hospital Review
·
Apr 2026
·
Tier
3
Healthcare Administrative Displacement by 2030
What will be scarce? The economics of structural change and the post-commodity future of work
Ghosts of Electricity (Alex Imas)
·
Apr 2026
·
Tier
4
Imas argues AI will trigger a post-commodity economy where spending shifts toward the relational sector (care, hospitality, craft, education) whose value is inseparable from human provenance. Evidence: Starbucks rolling back automation after it hurt satisfaction; experimental finding that human-made art gains 44% from exclusivity vs only 21% for AI-generated art.
Creative Industry Displacement by 2030
Customer Service Automation by 2028
Use of Gen AI in the Workplace and the Value of Access to Training
Federal Reserve Bank of New York (Liberty Street Economics)
·
Apr 2026
·
Tier
1
Among currently employed respondents, 39 percent report that they are either using AI tools in their current job or have used AI tools in their jobs in the last twelve months. College graduates are more than twice as likely to have used AI tools at work in the past twelve months as those without a college degree (58.7 percent versus 22.9 percent). AI adoption rises from 15.9 percent among workers earning under $50,000 to 66.3 percent among those earning over $200,000 annually. Around 38 percent of employed respondents said that having training in how to use AI tools is important to them, yet only 15.9 percent report that their employer currently offers any AI training. Around 62 percent of all respondents believe the unemployment rate will increase over the next twelve months due to AI.
Generative AI Adoption
Projected US Job Displacement from AI by 2030
Rising AI Adoption Spurs Workforce Changes
Gallup
·
Apr 2026
·
Tier
2
28% of employed U.S. adults use AI a few times a week or more; 13% use daily (up from 10% in 2024). 41% of employees report their organization has integrated AI tools. 23% in AI-adopting orgs report workforce reductions vs. 16% in non-adopting. Survey of 23,717 employed U.S. adults, margin of error +/-0.9pp.
AI Adoption Rate Across US Companies
Generative AI Adoption
Inside the AI Index: 12 Takeaways from the 2026 Report
Stanford HAI
·
Apr 2026
·
Tier
2
Employment among software developers aged 22–25 has plummeted nearly 20% since 2024, even as their older colleagues' headcount grows. The pattern repeats in other jobs with higher levels of AI exposure, like customer service. Meanwhile, firm surveys indicate executives expect this trend to accelerate, with planned headcount reductions outpacing recent cuts. Generative AI reached 53% population adoption within three years, faster than the personal computer or the internet... the U.S. ranks 24th at 28.3%. Across multiple hospital systems, physicians reported up to 83% less time spent writing notes and significant reductions in burnout.
Generative AI Adoption
Healthcare Administrative Displacement by 2030
Tech Sector Displacement by 2030: Uneven by Experience Level
Long-Term Effects of AI Job Losses
Goldman Sachs (via CNN)
·
Apr 2026
·
Tier
2
Long-lasting impacts: 10 years after a job loss, technology-displaced workers' real earnings were 10 percentage points below that of non-displaced workers. Short-run impacts: It can take one month longer for technology-displaced workers to find a new job; and their inflation-adjusted earnings take bigger hits (more than 3%) versus other workers (negligible effect). Recessions worsen outcomes: The effects of technology-related displacements are amplified (by three weeks of additional unemployment and a 5-percentage-point likelihood of subsequent joblessness). Goldman Sachs previously estimated that 6% to 7% of US workers (about 11 million people) could have their jobs displaced by AI.
Median Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
Anthropic's Economics Chief on Jobs Killed by AI
Fortune (Peter McCrory, Anthropic)
·
Apr 2026
·
Tier
3
I was somewhat surprised that the gap between sort of coding in general, which as we point out had something like 94% theoretical exposure, but then based on actual adoption, it was closer to 30% of the tasks across all the jobs in that pocket of the economy.
Tech Sector Displacement by 2030: Uneven by Experience Level
AI Assistance Reduces Persistence and Hurts Independent Performance
arXiv (Liu, Christian, Dumbalska, Bakker, Dubey — CMU/Oxford/MIT/UCLA)
·
Apr 2026
·
Tier
1
Here, through a series of randomized controlled trials on human-AI interactions (N = 1, 222), we provide causal evidence for two key consequences of AI assistance: reduced persistence and impairment of unassisted performance. Although AI assistance improves performance in the short-term, people perform significantly worse without AI and are more likely to give up.
Goldman Sachs on AI Agents and Labor Market Impact
Goldman Sachs Global Investment Research
·
Apr 2026
·
Tier
2
Our analysis implies that AI substitution has reduced monthly payroll growth by roughly 25k and raised the unemployment rate by 0.16 percentage points over the past year, while augmentation has added about 9k to monthly payroll growth and lowered the unemployment rate by 0.06pp. This implies a net drag of 16k per month on payroll growth and a 0.1pp boost to the unemployment rate. These negative effects fall largely on less experienced workers, widening the entry-level-to-experienced wage gap by 1.3% and the unemployment rate gap by 0.6pp from their pre-pandemic averages.
Entry-Level Wage Impact from AI by 2030
Median Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
JPMorgan Chase 2025 Annual Report — CEO Letter (Jamie Dimon)
JPMorgan Chase (Jamie Dimon)
·
Apr 2026
·
Tier
3
AI will definitely eliminate some jobs, while it enhances others. Huge increase in AI-driven capital spending and construction by the five hyperscalers. In 2025, this number was $450 billion, and in 2026, it will be approximately $725 billion. There is a possibility that AI deployment will move faster than workforce adaptation to new job creation.
AI Adoption Rate Across US Companies
Projected US Job Displacement from AI by 2030
AI's Tech Displacement Effect: Gen Z and the 16,000 Jobs-per-Month Drag
Goldman Sachs (via Fortune)
·
Apr 2026
·
Tier
2
New research by Goldman Sachs economists finds that AI is already a measurable drag on the U.S. job market—erasing roughly 16,000 net jobs per month over the past year, with the pain falling hardest on Gen Z and entry-level workers. Goldman's breakdown shows AI substitution wiped out roughly 25,000 jobs per month in the past year, while augmentation added back about 9,000. The wage gap has similarly deteriorated, with Goldman's regression analysis estimating that a one standard-deviation increase in AI substitution exposure widens the entry-level-to-experienced wage gap by roughly 3.3 percentage points.
Entry-Level Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
BLS Employment Situation: Total Nonfarm Payrolls — March 2026
data.bls.gov
·
Apr 2026
·
Tier
1
Total nonfarm payrolls rose by 571K in March 2026 to 157,775K.
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
BLS Employment Situation: Information Sector — March 2026
data.bls.gov
·
Apr 2026
·
Tier
1
Information sector employment at 2,772K, +3K month-over-month.
Tech Sector Displacement by 2030: Uneven by Experience Level
BLS Unemployment Rate — March 2026
data.bls.gov
·
Apr 2026
·
Tier
1
Unemployment rate 4.3% in March 2026, down 0.1 percentage points.
Projected US Job Displacement from AI by 2030
Economists Once Dismissed the A.I. Job Threat, but Not Anymore
The New York Times (Ben Casselman)
·
Apr 2026
·
Tier
3
Most still do not see much evidence that A.I. is disrupting the job market. But they are starting to take seriously the possibility that it could someday soon. If it does, they are worried that policymakers are not ready to respond.
AI Adoption Rate Across US Companies
Entry-Level Wage Impact from AI by 2030
Projected US Job Displacement from AI by 2030
White-Collar Professional Displacement by 2030
+
1
more
Autonomous Coding Agents Generate 400,000+ Pull Requests: Real-World Software Workflow Implications
arXiv (Chowdhury, Banik, Ferdous, Shamim)
·
Apr 2026
·
Tier
3
Autonomous coding agents are generating code at an unprecedented scale, with OpenAI Codex alone creating over 400,000 pull requests (PRs) in two months. CRA-only PRs achieve a 45.20% merge rate, 23.17 percentage points lower than human-only PRs (68.37%).
Tech Sector Displacement by 2030: Uneven by Experience Level
Monitoring AI Adoption in the U.S. Economy
Federal Reserve Board of Governors (Jeffrey S. Allen)
·
Apr 2026
·
Tier
1
Adoption stood at about 18 percent of firms at the end of 2025. Prior to the question revision, the adoption rate had grown by 68 percent (3.9 percentage points) over the prior year but decelerated in Q2 2025. Over 20 percent of firms expect to use AI in the first half of 2026. The right panel of figure 2 shows that work-related GenAI adoption reported in the RPS stands at about 41 percent of the workforce, and non-work-related usage at about 50 percent of the population as of the latest survey in November 2025. The SBU estimates an employment-weighted firm AI adoption rate of around 78 percent and an LLM adoption rate of about 54 percent.
AI Adoption Rate Across US Companies
Generative AI Adoption
US Workforce AI Exposure
Observed AI Use at Work
How AI may reshape career pathways to better jobs
Brookings Metro / Opportunity@Work (Heck, Muro, Methkupally, Siegmund)
·
Apr 2026
·
Tier
2
Of America's ~70M STARs (workers skilled through alternative routes, no four-year degree): 15.6M work in roles in the top quartile of AI exposure (43% of all top-quartile workers); 11M of those are in Gateway occupations — the stepping-stone roles connecting entry-level to higher-wage work — with 6 Gateway occupations alone accounting for ~8M of them. STARs are 62.3% of all Gateway-occupation workers. Across Destination occupations, 12.9M workers (~1/3) are highly exposed, including sales reps, accountants, financial managers. Only 51% of Gateway-to-Destination career pathways AVOID high AI exposure. 3.5M STARs are both highly exposed AND have low adaptive capacity (67% of all such workers). 23M STARs have low adaptive capacity overall (68% of all such workers). Highest pathway-exposure metros: Palm Bay FL (35.5%), Cape Coral FL (34.7%), Jacksonville (33%), Albany NY (32.8%), Harrisburg (32.6%), Providence (30.1%). 73% of US workers live and work in the same county, so disruption — and remediation — will be place-specific. Uses Anthropic's observed-exposure measure on Opportunity@Work pathway taxonomy.
Customer Service Automation by 2028
Entry-Level Wage Impact from AI by 2030
White-Collar Professional Displacement by 2030
US Workforce AI Exposure
AI Blamed Heavily For March Job Cuts, Report Says
Forbes (Challenger, Gray & Christmas data)
·
Apr 2026
·
Tier
3
U.S.-based employers announced 60,620 job cuts in March, according to Challenger, up 25% from 48,307 cuts announced in February. AI was the leading reason for cutting jobs, cited in 25% of announcements, followed by closings, restructuring and economic conditions.
Projected US Job Displacement from AI by 2030
Forecasting the Economic Effects of AI
NBER (Karger, Kuusela, Abaluck, Bryan, Halperin, Jones, Murphy, Trammell, et al.)
·
Apr 2026
·
Tier
1
NBER Working Paper 35046. Survey of 69 economists, 52 AI industry/policy professionals, 38 superforecasters, and 401 general public on AI's economic effects. Unconditional median economist forecasts: GDP growth 2.5% for 2025–2029, LFPR 61.0% for 2030 (vs 62.6% Jan 2025), 58.3% for 2050. Only 14.0% mean probability assigned to a 'rapid' AI progress scenario by 2030. Conditional on rapid scenario: GDP growth 3.5%, LFPR falling to 55.0% by 2050 (~10M lost jobs attributable to AI), wealth inequality reaching 80.0% held by top 10% by 2050, work hours AI-assisted rising from 3.35% (2024) to 10.1% (2030 unconditional) or 24.2% (2030 rapid). Variance decomposition finds expert disagreement driven prima

[The evaluation harness truncated this reference: showing the first 120000 of 323300 characters.]
</reference>

<statements>
1. Despite widespread evidence of microeconomic disruption and firm-level restructuring, aggregate macroeconomic indicators have exhibited historically subdued productivity surges, illustrating the modern AI Productivity Paradox.
2. Brynjolfsson, Rock, and Syverson explain this apparent disconnect by classifying artificial intelligence as a General Purpose Technology (GPT).
3. Similar to the historical lags observed during the rollouts of electrification and the internal combustion engine, the commercial fruition of a GPT requires time-intensive complementary capital investments.
4. Enterprises must overhaul existing organizational hierarchies, rethink core workflows, reskill workforces, acquire high-quality training data, and integrate specialized enterprise architectures before aggregate efficiency dividends materialize.
5. This structural adjustment process produces the phenomenon known as the Productivity J-Curve.
6. In the initial phase of widespread general-purpose technology adoption, substantial organizational capital and corporate labor hours are diverted toward developing intangible, unmeasured capital assets—including redesigned workflows, foundational datasets, and algorithmic infrastructure.
7. Because conventional national economic accounting metrics track the labor and capital costs poured into these efforts while failing to capture the corresponding output of intangible software architectures, measured aggregate total factor productivity and labor productivity appear depressed or stagnant.
8. Only after complementary intangible capital reaches sufficient operational scale does the measured productivity curve reach its inflection point, rebounding sharply upward to reflect the full economic returns of the technology.
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.