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March 202631 sources
Two jobs with identical exposure scores can have completely opposite displacement risks depending on whether their tasks are complements, whether demand for their output is elastic or inelastic, and the incentives of the firm to invest in automation. The workers at greatest risk are not necessarily those with the highest average exposure, but those whose jobs are built around a small number of core tasks that AI can automate.
The addition of the January and February 2026 CPS and the introduction of Anthropic's 'Observed Exposure' metrics do not suggest any substantial changes. Occupational dissimilarity, industry dissimilarity, and exposure and usage metrics all remain flat, lie within historical ranges, or continue along pre-existing trends.
6-7% of workers will be displaced during that transition period. In the US, AI can potentially automate tasks that account for 25% of all work hours. Goldman Sachs Research expects to see a 0.6 percentage point increase in the unemployment rate over a decade.
AI professionals earn $215,000, on average, in San Jose, CA — the highest in the country. But, with living costs 13% above average, that premium narrows. For comparison, in Dallas–Fort Worth, TX, $128,000 salaries stretch further with costs just 3% above average.
A lot of these claims are premature. Many of the people making them have an interest in selling a product. Right now I would describe the labor market as more of a wait-and-see environment. You cannot automate everything tomorrow because we simply don't have enough computing power to do it.
An event study documents an accelerating decline in employment of 22–25-year-olds in high-AI-exposure occupations, reaching 5.5 per cent by early 2025 relative to less exposed occupations within the same employers, while employment of workers over 50 rose by 1.3 per cent.
Two points of general agreement stand out: There's no measurable evidence so far that AI is putting Americans as a whole out of work, economists say. And while the victims of past workplace automation were mostly factory and trade workers, it's white collar jobs that are first in line for AI shake-ups today.
New business applications remain elevated but 'high propensity to hire' applications are in decline. SMBs are rapidly increasing tech spend (including AI) while payroll spend is flat or declining — consistent with AI-native solopreneurs substituting software for labor.
Survey of ~750 CFOs finds AI adoption widespread (58.5% in 2025, 85.4% expected 2026). Implied revenue-based labor productivity gains of 0.6% in 2025, 1.8% expected 2026, with largest gains in finance (>2%). Aggregate employment decline <0.4% in 2026 (~502K workers). Routine clerical roles declining; skilled-technical rising. Productivity paradox: reported gains 3x larger than implied revenue-based gains.
The evidence on how AI is affecting the labor market today is inconclusive, and claims about harmful impacts on particular groups of workers are premature. Initial evidence suggests that transitional disruption from AI to date is not outpacing recent technological changes.
AMIE's differential diagnosis included the final diagnosis in 90% of cases, with 75% top-3 accuracy. Blinded assessment suggested similar overall DDx and Mx plan quality between AMIE and PCPs. Human safety supervisors did not need to intervene to stop any consultations.
The U.S. Army's 18th Airborne Corps, using software from data company Palantir Technologies in a continuing string of exercises dubbed Scarlet Dragon, matched its own record from Iraq as the military's most efficient targeting operation ever. Thanks to AI, the corps achieved that with only 20 people, compared with more than 2,000 staffers employed in Iraq.
new grad hiring in large tech is down over 50% since 2019. For the first time in over decades, recent college grads have a higher unemployment rate than the national average. In addition, the 'underemployment rate' for recent graduates has risen to 42.5% (Q4 2025, New York Federal Reserve).
The survey shows institutional adoption is accelerating, with 66% of respondents reporting their institution is currently leveraging AI, an increase from 49% year over year. Eighty-eight percent of respondents say they expect institutional AI use to increase over the next two years.
While we still do not find a meaningful relationship between productivity and AI adoption at the economywide level, companies that quantified productivity impacts of AI on specific tasks reported a median productivity gain of around 30%.
February 202631 sources
AI's labor market impact still small — only 5-10K/month drag on net job growth. Only 2½% of jobs exposed to automation today. Baseline forecast: 6-7% of workers displaced (range 3-14%), lowering annual hiring by 1M jobs and raising unemployment ~½pp. US creates 30M gross new jobs/year; does not anticipate job apocalypse. Impact so far largely confined to tech sector but expects it to grow materially.
METR retracts original 19% slowdown finding, citing severe selection bias. Follow-up shows -18% speedup for original devs (CI: -38% to +9%), -4% for new recruits (CI: -15% to +9%). Authors state data gives 'unreliable signal' and are redesigning the study.
Employment in the computer systems design and related services sector has declined 5 percent. AI exposure associated with 0.28pp wage growth reduction for low-experience-premium jobs but 0.2pp increase for high-experience-premium occupations.
AI exposure metrics broadly agree with each other, but that they disagree with each other more on highly exposed occupations. The key point of disagreement between different AI exposure metrics is in the magnitude of exposure, not whether an occupation is exposed.
Full-year 2025 revenue of $430.9M, up 10.1% YoY. Active buyers down 13.6% in 2025. Spend per buyer reached $342, rising 13% YoY. Writing, translation, and simple programming categories declining ~20% due to AI substitution. High-value projects over $1,000 grew 23%. 2026 revenue guidance: $380M-$420M, a decline of 3-12% YoY.
Customer service could see as much as 75% of interactions automated by 2026. AI-driven platforms could deliver primary investment advice to nearly 80% of retail investors by 2027. Over 85% of software developers now use AI coding assistants, delivering productivity gains of up to 60%.
Survey of ~6,000 executives across US, UK, Germany, Australia. 90%+ report no employment impact from AI over the past 3 years. Firms expect AI to reduce employment by 0.7% over the next 3 years (US: -1.2%). Employees, by contrast, expect +0.5% job creation.
In a randomized experiment with 1,174 adults ages 25-45, AI access closed approximately three-quarters of the education-based productivity gap: higher-education participants outperform lower-education participants by 0.548 standard deviations without AI; with AI, this gap falls to 0.139 standard deviations.
Without AI, higher-education participants outperformed lower-education participants by 0.548 standard deviations. With AI access, this gap fell to 0.139 standard deviations—closing about 75 percent of the baseline productivity difference.
January 202654 sources
6.1 million U.S. workers face both high AI exposure and low adaptive capacity. Medical secretaries and administrative assistants (831,000 workers) stand out as one of the largest occupations in this high-risk category. About 86% of these workers are women.
Of the 37.1 million workers in the top quartile of AI exposure, 26.5 million are in occupations that also have above-median adaptive capacity. 6.1 million workers (4.2%) face high exposure + low adaptive capacity; 86% are women.
By 2040, output is only 4% higher than it would have been without the growth acceleration, and by 2060 the gain is still only 19%. A key reason for the slow acceleration is the prominence of 'weak links' (an elasticity of substitution among tasks less than one).
There is no evidence that job postings for junior roles within occupations most exposed to AI have declined more than postings for senior positions. Postings for both levels of seniority have been falling roughly in parallel since their peak in Spring 2022, with the decline in junior positions stabilizing faster.
CEO Brian Moynihan: 'We have 18,000 people on the company's payroll who code, and we've — using the AI techniques, we've taken 30% out of the coding part of the stream of introducing a new product or service or change that saved us about 2,000 people.'
BLS projects a further 6% decline in programmer roles through 2034. Computer programmer employment (routine coding roles) fell ~27.5% in roughly two years following ChatGPT's release — one of the largest two-year drops in any occupation tracked by BLS. Software developer employment remained flat.
AI adoption led to moderate productivity increases — an 8.5 percent increase in coding activity and 8.7 percent faster task completion — with no measurable quality declines. These productivity gains did not translate into increased output, changes in task composition, or effects on employment.
December 202519 sources
November 202526 sources
57% of US work hours are technically automatable. Physical tasks comprise 50%+ of hours for 40% of the US workforce. Robot unit costs ($150-500K) must fall to $20-50K for mass physical automation adoption. At least 14% of employees globally may need career changes by 2030.
Currently demonstrated technologies could automate activities accounting for about 57 percent of US work hours today. AI agents could perform tasks occupying 44 percent of US work hours, while robots could handle another 13 percent. Roles with the highest potential for automation make up about 40 percent of total jobs.
Early-career workers (ages 22-25) in AI-exposed occupations experienced 16% relative employment declines, controlling for firm-level shocks. By September 2025, employment for software developers aged 22-25 declined nearly 20% compared to its peak in late 2022.
Overall employment continues to grow robustly, but employment growth for young workers has been stagnant since late 2022. Declining employment in AI-exposed jobs drives stagnant overall employment growth for 22- to 25-year-olds.
October 202527 sources
Survey of 180 Fortune 100 executives and 12,000 knowledge workers. 96% of organizations not seeing dramatic improvements in efficiency, innovation, or work quality from AI. Costing Fortune 500 ~$98B/year in lost returns. Workers report feeling 33% more productive individually, but organizational metrics flat.
September 202523 sources
Survey of 1,150 US workers: 40% received AI-generated 'workslop' in the past month; each instance cost ~2 hours to deal with. 18% of AI users admitted sending low-quality AI output. Estimated cost: $186/worker/month or ~$9M/year for a 10,000-person org.
The framework yields several predictions: larger average firm size, greater industry concentration, and reduced local managerial autonomy. Transformative AI sharply expands what counts as codifiable local knowledge. In the absence of active countermeasures, transformative AI may lead to significantly more centralization of decision-making.
August 202511 sources
70% of providers and 80% of payers now have an AI strategy in place or in development. RCM is the top AI use case, with ambient documentation at ~20% full rollout and ~40% in pilot. Nearly half of provider executives said revenue cycle management was a top three IT investment priority. Survey of 228 US healthcare provider and payer executives.
July 202516 sources
June 202521 sources
Using O*NET and LightCast job postings data (2019-June 2024), the study found a 24% decrease in generative AI-exposed skills per firm per quarter for automation-prone occupations, while augmentation-prone occupations saw a 15% increase. Demonstrates the dual displacement/complementarity impact of generative AI.
May 202514 sources
Approximately 32% of health employment is classified under potential augmentation, approximately 4.3% of roles are identified as potentially automatable, and the high automation risk category constitutes around 0.6% of the health workforce. Analysis of 55.5 million online job postings.
April 20258 sources
In a field experiment across 66 firms and 7,137 knowledge workers, the 80% of treated workers who used the AI tool spent two fewer hours on email each week. We do not detect shifts in the quantity or composition of workers' tasks.
March 202510 sources
February 202521 sources
AI skills and expertise are highly valued by employers, offering a 23% wage premium, compared to a 13% wage premium for Master's degrees and a 33% premium for PhDs. In science, engineering, and tech jobs, the AI skills premium is 36%. Analysis of over 10 million online job vacancies in the UK between 2018 to 2024.
BLS projects employment of software developers to increase 17.9 percent between 2023 and 2033. Despite its exposure to GenAI applications, this occupation is unlikely to experience a decline in employment. Customer service representatives projected to decline 5.0 percent. Medical transcriptionists projected to decline 4.7 percent. Paralegals projected to grow 1.2 percent.
Tenured workers cumulatively lose about 3,800 Euros in wage and salary earnings over five years on average (about 9% of one year's income). Only 0.7% of all workers leave their employers each year due to automation, far below mass layoff rates.
January 202537 sources
Demand for substitutable skills (writing, translation) decreased 20-50% relative to counterfactual after ChatGPT launch. Short-term (1-3 week) jobs saw sharpest decline. ML programming demand grew 24%; AI chatbot development nearly tripled.
Among respondents actively using or experimenting with AI, 93% agree that it allows them to focus more on higher-level responsibilities. The leading response (53%) was 'AI will augment human capabilities, leading to increased productivity and new forms of innovation.'
December 20244 sources
As we approach Transformative AI, there is urgent need to advance understanding of how it reshapes economic models, institutions, and policies. Proposes nine Grand Challenges including economic growth, income distribution, and transition dynamics.
November 20243 sources
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January 202413 sources
About 21.4% of film, television, and animation jobs (approximately 118,500 jobs) are likely to be either consolidated, replaced, or eliminated by GenAI in the U.S. by 2026. 75% of survey respondents indicated Gen AI tools had supported the elimination, reduction, or consolidation of jobs in their business division.
Just under 6% of firms nationwide used AI as of 2017. Employment-weighted adoption was just over 18%. Based on the 2018 Annual Business Survey of 850,000 firms across the US. AI use clustered with cloud computing and robotics; most very large firms reported some AI use.
December 20231 source
The paper reports no statistically significant average effect on revenues or profits. But effects are highly heterogeneous: high‑performing businesses at baseline appear to improve (roughly 15 percent), while low performers do worse (roughly 8-10 percent worse)
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July 20201 source
The main impact of automation in the near future may be to cause a major reallocation of jobs, even if it does not permanently eliminate large numbers of jobs. During the 19th century, technologies had automated 98% of the labour required to weave a yard of cloth. Yet, the number of weaving jobs actually increased for decades over this period.
June 20201 source
January 20182 sources
July 20151 source
The evidence is that technological unemployment did not occur on a large scale during the Industrial Revolution. The fears of the Luddites that machinery would impoverish workers were not realized. Predictions of widespread technological unemployment were, by and large, wrong, but we should not trivialize the costs borne by the many who were actually displaced.