AI और श्रम नीति टाइमलाइन

Maintaining Human Verification Capacity under Automation

arXiv

A theoretical paper on a quiet risk of automation: human verification relies on expertise that has to be kept up before it is ever needed. The model links three things — reliance on automated checks, investment in human checking ability, and performance when automation is interrupted. Its central result is that better automated checking shrinks the error reduction gained from an extra unit of human skill, which can weaken the incentive to preserve independent expertise even when it lowers the best achievable expected cost. The paper is a formal model and reports no empirical estimates.

How Albertsons Companies is reimagining retail from the inside out

OpenAI

OpenAI customer case study (company-published): grocery retailer Albertsons Cos. is using ChatGPT Enterprise and the OpenAI API to help teams work faster and make grocery shopping easier for millions of customers.

The Den frees up 10-15 hours a week to grow with ChatGPT Work

OpenAI

OpenAI customer case study (company-published): social club The Den says ChatGPT Work frees up 10-15 hours a week, with grant applications prepared in 2 hours instead of 3 days and liquor-license materials in 3 hours instead of 4 days as it opens a new location.

The eternal complement

OpenAI

OpenAI essay arguing that advanced AI may matter most for the routine work behind breakthrough ideas, and that execution could shape the next economy and the pace of progress.

Job Cuts Fall in September; Hiring Plans Up 3% Over 2025 On Weak Early Seasonal Hiring

Challenger, Gray & Christmas

Challenger, Gray & Christmas's monthly count of announced U.S. layoffs: employers announced plans to cut 43,281 jobs in September 2026, 18% fewer than in August. On the hiring side, weak early seasonal hiring plans held year-to-date hiring announcements to just 3% above the same period of 2025. The figures are announced plans tallied by an outplacement firm, not realized job losses, and they move with the timing of individual corporate announcements.

Helping small businesses put AI to work

OpenAI

OpenAI announced a partnership with America's SBDC (Small Business Development Centers) to expand hands-on AI training and local support for small businesses, released alongside a company report on how small teams are using AI. This is a corporate announcement rather than independent research.

Can we predict the jobs robots will do?

Anthropic

Anthropic economists build a robot exposure index from O*NET tasks rated by how structured an environment a robot needs. Robots can already do 74% of US physical tasks (34% of all working hours), but are cheaper than human labour for only 0.3% of work; at past 3%/yr price declines, reaching 10% would take about 40 years. Driving and packing jobs are most exposed, nursing and repair least.

AI-based matching improves refugee employment in a double-blind randomized trial

arXiv (Bansak, Hainmueller, Hangartner et al.)

In a double-blind trial run by the Swiss State Secretariat for Migration from 2020 to 2023, about 2,000 refugee cases were randomly given either an algorithmically employment-optimized canton recommendation or one approximating existing procedures, with officers keeping final say. The share of months employed over three years rose 2.2 percentage points (3.9 pp for 2022-2023 cohorts), and the 36-month employment rate rose 5.2 pp, comparable to hundreds of hours of intensive language training.

When Less Is More: Managing AI Adoption with Adaptive Incentive Design

arXiv (Gong et al.)

A large medical-device firm required about 5,000 employees to send at least 200 queries a month to an internal AI assistant. Use rose, but so did gaming: queries bunched at the threshold and 31 percent were repeated or off-task. Lowering the target to 100 cut query volume by 30 percent, about 90 percent of it from repeated or off-task queries, with no significant change in genuine work queries, while sales employees' monthly sales rose 7 percent.

Economic Governance of Autonomous Agents and Robots: Factor-Origin Accounting and Social Automation Funds

arXiv (Syed et al.)

Argues that tax systems built on wages and payroll erode as autonomous agents, foundation models and robots decouple output from human work hours. The paper proposes CivicDividendOS, a fiscal framework that attributes value across labor, AI, robotics, data and capital, levies a Social Automation Contribution on automated value added with offset credits for upskilling, and recycles revenue into payroll relief and a public wealth fund. It is a conceptual design illustrated in urban logistics, not an empirical estimate.

The Macroeconomic Effect of AI: Sizing the Software Engineering Channel (NBER WP 35793)

National Bureau of Economic Research

Blumenfeld, Hazell, Lian and Schaab measure how AI affects the economy through one channel: software engineering productivity. They build a forward-looking, real-time measure from financial markets, estimating each firm's stock-return sensitivity to an AI stock market index and how it varies with the share of firm payroll in software engineering, then use a model to map that relationship into productivity gains. The period studied is November 2022 to December 2025.

The Early Impacts of AI on Employment among Recent College Graduates (NBER WP 35796)

National Bureau of Economic Research

Fairlie and Wu use CPS microdata to produce what they describe as the first estimates of AI's effect on unemployment among recent college graduates in June, July and August 2026. The abstract says unemployment rates run especially high in summer months and that 2026 might be the first year with workplace AI use widespread enough to detect effects on this group. It notes there is no consensus on magnitude or timing.

From exposure to opportunity: Why skills shape the employment effects of new technologies

ILO

Using ILO harmonized microdata for more than 1,000 subnational regions in 69 countries, the analysis estimates how potential exposure to 40 emerging digital technologies, including industrial automation, robotics and machine learning, affects employment rates. On average exposure is associated with employment gains, but unevenly: concentrated among prime-age workers, reaching low-educated workers in low-income countries and high-educated ones in high-income countries. Gains are larger where local labour demand embeds stronger advanced cognitive, basic computer, finance, writing, project and people-management skills, even after controlling for education (Delaporte and Escudero, forthcoming).

Canaries Dashboard: Employment in AI-exposed occupations slowed in August

ADP Research

ADP's monthly Canaries Dashboard reports that employment in AI-exposed occupations slowed in August 2026, with early-career workers continuing to lose ground.

Grab and OpenAI bring practical AI skills to Southeast Asia

OpenAI

OpenAI and Grab launched "GO Forward with AI", a regional programme to help 30,000 Grab partners across Southeast Asia build practical AI skills.

Parallel cut research time and cost in half with GPT‑6 Astra

OpenAI

OpenAI customer note: GPT‑6 Astra allowed Parallel's agents to research and synthesize labor-market data in half the time and at half the cost compared with prior models. Summary is based on the feed excerpt only; the full article was not accessible at registration.

AI plays a role in weak labor market for college graduates

Federal Reserve Bank of Dallas

Dallas Fed researchers Samuel Dodini and Tucker Smith link Texas administrative records, Lightcast job postings, O*NET and Anthropic task data to measure how generative AI is reshaping outcomes for new college graduates. Graduates from AI-exposed majors were 1.7 percentage points less likely to find a Texas job within a year and earned 5% lower wages than peers in less-exposed fields. They were also 1.4 points more likely to enter graduate school, and undergraduate enrollment in exposed fields fell 4.8% between fall 2024 and fall 2025. The authors conclude that generative AI has reduced demand for roles whose tasks it completes more efficiently than humans.

How V7 gives AI agents institutional memory

OpenAI

A customer story published by OpenAI. According to OpenAI, V7 uses GPT-5.6 to turn a company's scattered files into context that AI agents can use, so the agents can complete complex work whose outputs are linked back to the underlying sources. OpenAI frames this as giving agents "institutional memory". The claims are the vendor's own and are summarized here from its post.

Expanding OpenAI Academy with new learning paths

OpenAI

An announcement published by OpenAI. According to OpenAI, OpenAI Academy is adding new learning paths for five audiences (employees, developers, leaders, educators and students) so that people can build practical AI skills and demonstrate them. This is the company's description of its own training offering; this entry summarizes the announcement only and does not assess the curricula or any outcomes.

Better Technology, Worse Motivation: Generative Artificial Intelligence’s Mediocrity Trap

Asian Development Bank (ADB)

This ADB paper examines how generative artificial intelligence (AI) affects both productivity and motivation in creative work. Summary based on the publication feed abstract; the paper itself was not read.

How Cooley is accelerating IPO work with ChatGPT

OpenAI

A customer story published by OpenAI. According to OpenAI, the law firm Cooley built "GO Public" with ChatGPT Work to bring intelligence to the IPO process, helping lawyers surface issues earlier and focus their judgment where it matters most.

Hex turns complex analysis into visual reports with GPT‑6 Astra

OpenAI

A customer story published by OpenAI. According to OpenAI, GPT-6 Astra helps Hex's data agents turn answers into interactive visualizations that employees are proud to share.

Distributional Intersectional Fairness in AI-Supported Job Matching

IAB (Institute for Employment Research)

An IAB paper analyses how machine learning methods change the distribution of outcomes between intersecting social groups, in the setting of AI-supported job matching. Summary based on the institute's one-sentence announcement; the paper itself was not read.

Artificial intelligence adoption in Chinese enterprises: Productivity effects, workforce implications, and policy challenges

International Labour Organization

ILO Research Brief (Ernst with Renmin University co-authors, 2026-09-15, CC BY 4.0). 21 firm interviews + survey of 1,591 professionals. Reported gains: recruitment 30->13 days, 300-agent CS floor 6,000->15,000 issues/day, spec-reading team 10+->2-3, lighthouse factory +30%. 13 of 21 firms report no quantified gain. Survey: 56% inevitable, 47% net job creation, 39% expect income decline. Self-reported, purposive sample, no counterfactual.

Workforce policy for the age of AI: Recommendations from the economic literature

Brookings Institution

Ben-Ishai and Thompson (MIT FutureTech), Brookings Economic Studies, 2026-09-15. Four findings from the economic literature: exposure is not commercial automation (models complete 3-4 hour tasks at 65% success as of end-2025; 10x task duration cuts performance 11%; firms would automate only 23% of automatable computer-vision tasks at current costs); the question is how AI changes the value of expertise (accountant vs family physician example); adoption requires knowing when to trust AI; reliability gains (failure halving ~2.5 years) will widen autonomous use. Five policy directions: prioritize displaced workers (displacement costs 2.8 years of prior earnings; low-wage workers -13% after six years) and high-productivity opportunities, domain-specific employer-partnered training, align programs with expertise shifts, expand apprenticeships (pay-for-performance, LEAP Act), federal wage insurance (TAA precedent). Authors concede training evidence is weak. Absolute mobility 90% (1940s cohort) to 50%.

Voice AI in Firms: A Natural Field Experiment on Automated Job Interviews

arXiv (Jabarian & Henkel)

Preprint (arXiv 2607.28222v2, 2026-09-11) by Jabarian (CMU) and Henkel (Erasmus). Natural field experiment at PSG Global Solutions (Teleperformance subsidiary) in the Philippines: 70,884 entry-level customer-service applicants randomly assigned to human-recruiter or AI voice-agent interviews; humans made all hiring decisions. Offer rate 8.70% (human) vs 9.73% (AI), +12% relative; job starts +18%; retention +18-19% at 2-4 months; no productivity difference on three firm metrics. Mechanism: 'controlled variance' (guideline similarity 0.59 vs 0.43). 78% chose AI when given the choice, with negative sorting. Lead author became unpaid Chief Economist at the partner firm after data collection.

Traditional labor market data isn't keeping up with jobs in the 'frontier economy' (Lipson & Schwartz)

Brookings Metro

Five blind spots in NAICS/SOC/O*NET data for frontier jobs: supply chain nearly triples semiconductor postings; biopharma machine-maintenance workers 26K (2008) to 57K (2025) with no SOC code; nuclear technician postings +68% in 2025 vs BLS -8% projection later revised to +1%. Revelio Labs data.

Record of proceedings: Technical meeting on challenges and opportunities for promoting decent work, productivity and a just transition arising from AI in the manufacturing industry (TMDWAI/2026/9)

International Labour Organization

Record of the 13-17 April 2026 ILO tripartite technical meeting (115 participants, 54 countries) that unanimously adopted the first ILO conclusions on AI in manufacturing (TMDWAI/2026/8, to Governing Body Nov 2026). 11 of 17 paragraphs amended: 'when applicable' inserted into worker-consultation clause, guidelines recommendation dropped (employers + US), risk assessments 'encouraged', surveillance/algorithmic 0 mentions. Background report: 489-494M manufacturing jobs, 16.5% GDP; employer barriers cost 58% / skills 43% / regulation 19%.

The Challenger Report August 2026: Job Cuts Up 58%; Consumer Products, Food Lead

Challenger, Gray & Christmas

August 2026 US job cuts totaled 52,881 (+58% MoM, -38% YoY; quietest August since 2022). AI fell to the 4th-most cited reason (3,462 cuts, lowest since Dec 2025) after leading March-July; AI remains #1 YTD at 116,175 (~22% of 529,914 total cuts). Hiring plans rose 725% YoY to 12,325; YTD 119,825, strongest Jan-Aug since 2023.

Job postings show early signs of AI automation impact

Federal Reserve Bank of Dallas

Dallas Fed Economics article (Dodini & Smith, 2026-09-01) linking Lightcast job postings to Anthropic's task-based AI exposure index. Postings for more-exposed occupations fell ~5% by end-2023 and ~7-8% by 2025-26 relative to less-exposed occupations within the same industry (per 10pp exposure difference). Incumbent Texas firms cut postings 8-9% by early 2026 and shifted composition away from automatable tasks (-2pp, ~50% of mean). Aggregate Texas postings reduced ~1.8% (2024) and 2.6% (2025). Two-thirds of Texas firms use AI (TBOS May 2026, vs 40% two years earlier).

Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting (NBER WP 35720)

National Bureau of Economic Research

Pre-registered 3-month RCT (Autor + 6 Google co-authors): 133 patent lawyers at 11 US IP firms, 2:1 AI (Google InFlow) vs control, blinded expert scoring. AI raised drafting quality 0.34 SD (10d) / 0.38 SD (90d), juniors most; 10-min time saving on 112-min task. Unassisted redlining at 90 days: treated +0.32 SD, entirely among seniors (+0.45 SD); juniors ~0 on average with bifurcated distribution. 91/133 completed (32% attrition), 15/91 flagged possible AI use on no-AI task, results robust.

인공지능(AI)는 일자리 파괴자 아닌 직무 재구성의 파트너… '인간 중심 인공지능(AI) 발전전략' 세워야

Ministry of Employment and Labor

Press release from Korea's Ministry of Employment and Labor announcing the Summer 2026 issue of "Employment Issues" (고용이슈), published by the Korea Employment Information Service. A survey of 2,297 establishments puts AI adoption at 28.6%, which the release calls an early stage; among adopting firms, 75.6% use generative AI. Among workers under 30, the 2025 employment index (2022 = 100) stood at 86.6 for the high-AI-exposure group against 92.5 for the zero-exposure group, a gap of 5.9 points, though the authors note the high-exposure decline began before ChatGPT. A separate survey of 305 incumbent workers reports an average self-rated skill gain from AI of 2.97 out of 5, highest for efficiency (3.40) and lowest for collaboration (2.37). The issue frames AI as a force that reshapes tasks rather than eliminating jobs and calls for a human-centered AI development strategy.

AI Transformation Requires Redesigning Work, Not Cutting Roles

Harvard Business Review

A Harvard Business Review article arguing that many companies are making AI-driven workforce cuts faster than the evidence warrants. It says early AI-driven layoffs have often failed to deliver expected returns, exposed gaps in organizational knowledge and created new demands for human oversight, and that some employers have reversed course. The proposed alternative starts from the work rather than headcount targets: break roles into tasks, identify where AI genuinely improves performance, and redesign processes around the right mix of human and technological capabilities.

The Pulse Beneath the Job Title: Monthly Readings of Requirements and Tasks from 750 Million Chinese Job Ads

arXiv (econ.GN)

Preprint analyzing 752.6M Chinese job ads (2022-2026, 5 platforms) into catalogs of 20,721 requirements and 44,479 tasks with monthly LLM-exposure readings. Key finding: AI-exposed occupations lose posting share (slope -1.33) far faster than their task categories decline (-0.83) — adjustment runs through which jobs are posted, not job content. Within-title exposure spreads up to 17%-48% by wage band.

Employment Projections: 2025-2035 (with new AI exposure categories data product)

U.S. Bureau of Labor Statistics

BLS projects +5.9M jobs 2025-35 (170.3M to 176.2M, +3.5% vs +10.9% in 2015-25) and debuts a four-category AI exposure classification (Low/Moderate/High/Very high) for 831 occupations, combining 3 theoretical measures (Felten et al., Eloundou et al., Eisfeldt et al.) with 2 observed telemetry sources (Anthropic Claude, Microsoft Copilot). Office/admin support -4.0% (-752,100, largest group decline); healthcare 37.0% of all new jobs; nurse practitioners +41.0% fastest.

Sophistication in GenAI Use: Field Evidence from a Large Firm

arXiv

Field study of 713,564 prompts from 3,925 KPMG back-office employees over 8 months of 2025. Sophistication rises with seniority and peaks in Strategy/Digital Innovation/PM; Accounting & Finance lowest. No improvement over time; formal training effects vanish after the training month.

AI adoption and the productivity promise: what workers report

European Central Bank

ECB Blog (Dias da Silva, Lebastard, Sondermann, 2026-08-26), cited in Lagarde's 2026-09-14 speech. ECB Consumer Expectations Survey (~20,000 respondents, 11 euro area countries): workers using AI at work 26% (2024), 41% (2025), 52% (2026), ~3 days/week. Highly educated 61% vs lower education 37%; younger +20pp. Median user saves 3 hours/week (7.7% of working time); only 48.8% use and save time, so economy-wide gain ~3.8%. Coding saves ~8 hrs/week but used by ~8%. Positive sentiment fell 43% to 41%. 41% of workers uninterested (34% of managers); ~half of firms plan AI training (SAFE).

Monocultural Biases: Correlated biases in large language models lead to unequal systemic exclusion rates in hiring

arXiv

Bone, Stephany and del Rio-Chanona test ten LLMs used to screen job applicants, comparing base and post-trained versions. Post-trained models were 3.6% less likely to call back older applicants (in 8 of 10 models) and made far more correlated decisions. That consensus raised systemic exclusion rates from 5.6% to 17.3%, with intersectional rates of 12.2-21.7%, driven mainly by age-based bias.

Normative boundaries of AI in scientific work: Evidence from PhD researchers

arXiv (Angelini & Lyrvall)

Latent class analysis of 3,785 PhD students (Nature Graduate Survey 2025) finds 4 attitudinal profiles: division-of-labour 44%, status-quo 34%, all-purpose 16%, undecided 7%. AI accepted for literature tasks (60%/48%) but resisted for writing, data analysis and experiment design (33%/33%/36%). Weekly/daily AI use strongly predicts leaving the status-quo profile (-1.911, p<0.01).

What Work Does Generative AI Do? (Bick, Blandin, Deming, Schumacher)

National Bureau of Economic Research

First task-level genAI adoption indexes from a nationally representative US survey (RPS, 4 waves Aug 2025-May 2026). Adoption is widespread but shallow: >80% of occupations and >40% of tasks exceed 20% adoption, yet fewer than half of workers adopt within most tasks. Exposure scores explain 5-53% of occupation variation; chat-log measures over-classify generic tasks (correlations with survey 0.10-0.34).

Labour demand volumes by Standard Occupation Classification (SOC 2020), UK: January 2017 to July 2026

Office for National Statistics

ONS online job advert volumes by 4-digit SOC 2020 (Textkernel-collected, ONS de-duplicated). Total UK postings peaked at 13,780,433 in 2022 and fell to 8,312,308 in 2024 (-39.7%), 27.3% below 2019. Steepest declines cluster in graduate-entry digital/consulting roles; early education and childcare grew. Official statistics in development; Mar 2026 suppressed, several months partially imputed.

CentaurBench: Benchmarking LLM Capabilities on Augmenting vs. Automating Real-World Work Tasks

arXiv (UC Berkeley Haas, DIAL)

CentaurBench (arXiv:2608.18554v1, UC Berkeley Haas DIAL) separately benchmarks LLM automation vs augmentation across seven economically grounded tasks. Automation and augmentation rankings correlate only rho=0.48 (p=0.187, n=9 models); the augmentation winner differs from the automation winner in 5 of 7 tasks. The unaided GPT-3.5-Turbo worker outranked every assisted condition on operations research, tax preparation and travel planning. Only GPT-5-Mini beat the no-guidance baseline on average (mean rank 3.66 vs 3.79). Inter-judge agreement 71.0% across 6,265 comparisons (74.5% automation, 67.8% augmentation).

Canaries Dashboard: Employment in AI-exposed occupations rose slightly in July

ADP Research

July 2026 reading of the ADP Research / Stanford Digital Economy Lab Canaries Dashboard (Nela Richardson, 2026-08-19). Employment in high AI-exposure occupations rose 0.1% year over year, the first positive all-ages reading in the monthly series, while least-exposed occupations grew 1.1%. Workers aged 22-25: overall -1.3%, high-exposure -3% (34th consecutive monthly decline since October 2023), least-exposed flat. Ages 26-30: high-exposure -2.1%, least-exposed +1.8%. Payroll data covering 730+ occupations at tens of thousands of private U.S. employers.

[제2026-19호] 청년고용 위축, AI 탓인가? 변화하는 경력 사다리와 대응 과제

한국은행 (Bank of Korea)

BOK Issue Note 2026-19 (Oh Sam-il, Oh Young-sik): Korean youth (15-29) jobs fell 285,000 from June 2022 to June 2026, 268,000 (94.0%) in AI-high-exposure industries, while workers in their 50s gained 230,000 (75.2% in the same industries). Youth employment -31.4% information services, -27.4% publishing, -16.6% computer programming, -11.6% professional services. Automation-heavy industries show steeper youth declines; augmentation-heavy do not. Graduate youth unemployment 7.0% vs 5.4% since Nov 2022. Monthly youth outflow from high-exposure industries +32% (3.7k to 4.9k). Authors frame AI as an accelerant on top of experienced-hire preference, pandemic over-hiring and remote work, not the sole cause; prescribe career-ladder redesign.

Will AI take Filipino jobs? The answer depends on what we do now

International Labour Organization

Op-ed by Khalid Hassan, Director of the ILO Country Office for the Philippines. Entry point to the ILO February 2026 policy brief "Generative AI and Jobs in the Philippines" (Phu Huynh, PSA LFS Q1-2024 microdata): 27.7% / 12.7m of Philippine employment exposed to GenAI (highest in ASEAN), only 3.6% (1.7m) in Gradient 4, of which ~78% are clerical codes. IT-BPM employed 1.8m in 2024 (1.6m contact centres). ~2/3 of IBPAP member firms use AI vs 14.9% of Philippine firms overall. Fact-check: the 6.1% youth figure quoted in the op-ed is the World row of GET for Youth 2026 Table 2.2, not a Philippine figure; the Philippine youth Gradient-4 rate is 4.2% (217,200 jobs).

Stranded credentials: how a skill-signaling market absorbed generative AI

arXiv (Song Yao)

Audit of 444,698 Kaggle participations (2010-2026) across upload- and code-competition formats. Medals predict subsequent leaderboard performance almost entirely in the first year after being earned. Upload-competition medal stocks lost 82% of informativeness, but institutional stranding (format exit predating AI) explains half to three quarters of that loss. Official lifetime-count credential tiers discard 13-16% of medal information; a recency-weighted index built on pre-AI data alone outperforms them. Preprint, not peer reviewed.

Changing landscape of skills in the age of AI

ILO / IAG on TVET (ETF, Cedefop, Eurofound, EC, ILO, UNESCO)

Joint six-agency (IAG TVET) synthesis on how AI adoption shifts the variety and depth of skills demand: rising higher-order cognitive and socio-emotional skills, small AI workforce (0.3-5% of employment), AI literacy as a new foundational skill, and training supply lagging demand.

An evidence review of worker retraining (Anthropic Institute Working Paper 2026-01)

The Anthropic Institute (arXiv 2609.07011)

Roodman & Massenkoff (Anthropic Institute WP 2026-01, arXiv 2609.07011) meta-analyze 146 impact estimates from 56 US randomized job-training trials since 1973: employment +1.7pp (years 3-5), pre-tax earnings +$791/yr per person offered, cost $13,598/participant, narrow B/C 1.44, government recoups ~3/4 of outlay. JTPA/WIA/Job Corps small or null. Sector programs (Project QUEST, Per Scholas, Year Up): earnings +$3,000-4,000/yr family average, $5-10K at top programs, B/C 7.18, but accept ~20% (Per Scholas 7.1%) of applicants and have proven hard to replicate.

Developing a strong workforce requires collaboration

Federal Reserve Bank of Dallas

Dallas Fed SVP Roberto Coronado on AI impact for jobs not requiring bachelor degrees: administrative and IT roles greatly affected, truck drivers and auto mechanics less immediate change; short-term credentials add about $5,000/yr for high school or associate holders vs $2,600 for bachelor holders (Census-controlled).

World Development Report 2026: The Promise of Artificial Intelligence

World Bank

The World Bank's annual flagship report assesses AI's potential for developing economies through an adopt/adapt/advance framework. Key findings: 14.2% of high-income-country jobs at generative-AI automation risk vs 4.5% in low- and middle-income countries, while productivity-gain potential is nearly equal (18.7% vs 16.2%); middle-income countries reached 50% of ChatGPT global traffic within six months of launch; "small AI" field evidence includes +40% daily diabetic eye screenings in Bangladesh, ~1 year of additional learning at ~US$5/student via SMS math tutoring in Ghana, and up to US$560 farmer savings from AI monsoon forecasts in Telangana.

Occupational Convergence or Divergence? Mapping Labor Market Structural Shifts Driven by AI Penetration

arXiv (Hilman & Koltai)

LinkedIn/Indeed/Glassdoor भर्तियों का विश्लेषण (दिसंबर 2025-मई 2026, 10 देश): AI संबंधी भर्तियों का 75-85% STEM व्यवसायों में केंद्रित; स्वास्थ्य-शिक्षा, सेवा, उत्पादन-लॉजिस्टिक्स, सार्वजनिक सेवा प्रत्येक 5% से कम। AI कौशल मांग एंट्री-लेवल पर केंद्रित — व्यावसायिक प्रवेश की पूर्व-शर्त। STEM कोर में अभिसरण + शेष से विचलन, ग्लोबल नॉर्थ-साउथ दोनों में समान।

Use of generative artificial intelligence tools among Canadian workers, March 2026

Statistics Canada

First results from a new recurring Labour Force Survey supplement on AI use at work (reference period March 2026, workers aged 15-69 in the ten provinces). 35.9% of workers used generative AI tools for work in the previous 12 months; 41.6% used at least one AI or automation technology. Adoption sorted by an exposure-by-complementarity taxonomy: high exposure/high complementarity 53.8%, high exposure/low complementarity 45.9%, low exposure 14.2%. Industry ranged from professional, scientific and technical services 65.6% to accommodation and food services 16.3%. Within high-complementarity occupations, workers aged 15-24 used AI least (39.1%) versus 56.9% for ages 25-54. Depth of use is shallow: among users, 63.5% some but not most tasks, 24.9% almost no tasks, 8.0% most, 3.6% almost all. Among the 64.1% of non-users, 56.0% said it was not applicable to their work and only 5.8% cited a skills gap.

Unbundling jobs: Measuring the value of tasks in an AI economy

ADP Research

ADP Research with Stanford Digital Economy Lab (Richardson, Wang) linked 5M+ ADP client job postings to 9M+ workers in payroll data; analytic sample ~7,000 workers in selected IT jobs 2019-2025, 20,000+ worker-year observations across 600+ employers. Postings mapped to 25 O*NET Intermediate Work Activities; wages regressed on task indicators controlling for age, gender, year and firm effects. 8 activities associated with higher wages (incl. advising others on design/use of technologies, designing databases), 6 with lower wages (incl. diagnosing system or equipment problems, monitoring operation of computer or information technologies). 5 tasks showed reduced compensation in 2023-2025 vs 2019-2022, including "develop models of systems, processes, or products" which otherwise ranks high-value. No effect sizes, standard errors or significance tests published. Conclusion: AI's biggest and most immediate effect is on tasks, not entire occupations.

How Houston finds workers in an AI boom

Federal Reserve Bank of Dallas

Dallas Fed President Logan Houston visit: AI chatbot pilot matching job seekers to employers by skillset; GE Vernova Houston Learning Center turbine training, high schooler to field engineer in 7-8 years; Houston payrolls +2.1% annualized over 3 months ending May 2026.

AI and the global economy: implications for central banks (BIS Bulletin No 130)

Bank for International Settlements

BIS बुलेटिन 130 के अनुसार AI बूम बड़े, बढ़ते कर्ज़-वित्तपोषित निवेश उछाल (सबसे जुड़ी अर्थव्यवस्थाओं में GDP का ~1%) को चला रहा है, जबकि उत्पादकता लाभ अनिश्चित और असमान है। श्रम विस्थापन अब तक सीमित है, कॉल सेंटर और बिज़नेस सेंटर में शुरुआती संकेत दिखे हैं; व्यापक प्रतीक्षा-रुख़ कम हायरिंग, कम फ़ायरिंग गतिकी से मेल खाता है। AI चक्रीय संकेतों को धुंधला कर मौद्रिक नीति को जटिल बनाता है।

Who Takes the Hit? The Uneven Impacts of Generative AI on Labor Demand Across Countries

World Bank

WDR 2026 background paper analyzing 555 million Lightcast job postings across 84 countries (2021Q1-2025Q2). In high-income countries, postings for above-median GenAI-vulnerability occupations fell 5.8% relative to less substitutable occupations after ChatGPT; in middle- and low-income countries the impact is small and statistically insignificant. Displacement is larger with greater GenAI adoption, schooling, English proficiency, and digital services trade specialization.

Economic Futures Research Fund: Research Agenda

Anthropic

Anthropic ने $200M के Economic Futures Research Fund का रिसर्च एजेंडा प्रकाशित किया: विश्वविद्यालयों, शोध संस्थानों और गैर-लाभकारी संस्थाओं को $5-30M (न्यूनतम $1M) की ग्रांट, पाँच क्षेत्रों में बड़े पैमाने के RCT के लिए — फर्म-स्तरीय AI प्रभाव, ट्रांज़िशन समर्थन, आय-समर्थन आधुनिकीकरण, विस्थापन-पूर्व वर्कर इक्विटी और सार्वजनिक निवेश प्रमाण।

Canaries Dashboard: Employment in AI-exposed occupations contracted in June

ADP Research

June 2026 reading of the ADP/Stanford Digital Economy Lab Canaries Dashboard. Employment in high AI-exposure occupations fell 0.2% year over year while least-exposed occupations grew 0.6%. For workers aged 22-25 high-exposure employment fell 4.3%, a 33rd consecutive monthly decline since October 2023; least-exposed employment for that age band was flat. For ages 26-30 the figures were -2.6% and +0.9%. Based on payroll files of tens of thousands of private US employers, ~4 million workers, 730+ occupations.

Artificial intelligence in UK businesses: 2023 to 2026

Office for National Statistics

ONS official statistics in development. UK business AI adoption rose from ~12% (Sept 2023) to ~35% (June 2026) among 10+ employee businesses, but average AI technologies per adopter moved only 1.4 to 1.6 and just 10% describe use as extensive. Role impacts concentrate in creative/design and administrative/clerical work; ~7% of medium-sized businesses report headcount decrease. BICS Wave 159, 5-28 June 2026, 26.7% response rate.

The Last Ten Per Cent: How task-level AI exposure fits into a jobs forecast

Economic Innovation Group

Joshua Gans (Rotman/U. Toronto) reframes the "AI automates 90% of a job" claim as an economic question: whether the remaining 10% expands (focus effects, expertise recalibration, org redesign, demand elasticity) or shrinks headcount is indeterminate. Argues task-level exposure matters more than job-title automation, and that exposure/applicability scores are starting points, not employment forecasts — converting them requires investigating expertise thresholds, job bundling, market demand, and work intensity that payroll data obscures.

The Impact of Artificial Intelligence on Israel's Labor Market (Selected Issues Paper 2026/061)

International Monetary Fund

IMF का Selected Issues Paper जो एक्सपोज़र-पूरकता फ्रेमवर्क को इज़राइल पर लागू करता है: 23.1% कर्मचारी उच्च-एक्सपोज़र, कम-पूरकता नौकरियों में (विस्थापन जोखिम), 32.8% कम-एक्सपोज़र व्यवसायों में, और अधिकांश कर्मचारियों को लाभ की संभावना। सर्वाधिक जोखिम: व्यवसाय/प्रशासन पेशेवर, बिक्री कर्मी, ICT विशेषज्ञ। नीति निष्कर्ष: व्यापक आजीवन शिक्षा रणनीति।

Aggregate Gains from AI and Their Distribution: Global Evidence from Usage Data (WP 2026/147)

IMF

First multi-wave cross-country estimate of aggregate AI gains from usage data: $2.7T/year labor cost equivalent (3.4% of 86-country GDP), with an AI concentration index showing gains tilt to high-wage occupations everywhere — near-total concentration in low-income countries.

Generative AI and labour markets in ASEAN: Significant exposure, limited disruption, uneven preparedness

ILO

ILO brief (8 July 2026) estimating that 22.9% of ASEAN employment (~80 million workers) is in occupations with more than minimal generative AI exposure, while only 3.3% (11.7m) sit in the highest exposure band. Employment in exposed occupations grew from 66m (2017) to 80m (2025), showing no widespread disruption. Women 4.8% vs men 2.3% in the top band. Adoption is concentrated in large firms and technology-intensive occupations, with Singapore MOM data showing 71.5% of firms had not begun AI adoption. Concludes outcomes depend on preparedness and policy choices.

인공지능(AI) 시대 청년 일자리, 직업훈련 확대로 돌파구 찾는다

Ministry of Employment and Labor

Press release from Korea's Ministry of Employment and Labor on a July 8, 2026 roundtable in Jongno, Seoul, where Minister Kim Young-hoon met trainees and graduates of an AI vocational training program run by KG ICT under K-Digital Training (KDT). The ministry describes newly created KDT "AI Campus" specialized courses and the launch of "AI Worker" training as its response to youth employment pressure in the AI era. KG ICT's courses include a physical-AI manufacturing AX campus track that began in June 2026 and an AI battery campus track starting in October 2026; the release cites an application ratio of 3 to 1.

International comparisons show AI effect on productivity

Federal Reserve Bank of Dallas

2024 की पहली तिमाही से अमेरिकी उत्पादकता सालाना 2.4% बढ़ी (महामारी-पूर्व 1.6%)। सबसे AI-एक्सपोज़्ड तीन क्षेत्रों (सूचना, वित्त/बीमा, पेशेवर-तकनीकी सेवाएँ) की वृद्धि 3.7% बनाम बाक़ी की 1.7%; कुल घंटों का 16% होकर भी उत्पादकता वृद्धि का 40% इन्हीं से। EU में, जहाँ वही एक्सपोज़र इंडेक्स लागू है, कोई सहसंबंध नहीं। Anthropic AI उपयोग सूचकांक (अमेरिका 3.69, EU-27 1.85, एस्टोनिया 3.05, पोलैंड 1.41) यह अंतर समझाता है। सहसंबंध, कार्य-कारण नहीं।

Skills England Annual Skills Report 2026

Skills England (GOV.UK)

Skills England की पहली Annual Skills Report (6 जुलाई 2026) अनुमान लगाती है कि UK के 70% कर्मचारी AI-उजागर व्यवसायों में हैं, जिनमें सबसे अधिक जोखिम संज्ञानात्मक-लिपिकीय पेशेवर, विश्लेषणात्मक और अधिक-वेतन भूमिकाओं में है। स्नातक ऑनलाइन विज्ञापन 2025 में 45% और प्रवेश-स्तर विज्ञापन 25% गिरे; AI-उजागर कंपनियों ने जूनियर रोज़गार 5.8% घटाया। AI-कुशल कर्मचारी 56% वेतन प्रीमियम कमाते हैं। प्राथमिकता व्यवसाय (कार्यबल का 22.9%, 76 लाख) 2035 तक 18 लाख नौकरियाँ जोड़ने का अनुमान, जिसमें देखभाल कर्मी, सॉफ्टवेयर डेवलपर और IT विश्लेषक अग्रणी। मुख्य अड़चन कौशल है: व्यावसायिक प्रशिक्षण खर्च 9% गिरा (2019-2024, 49.4 से 44.8 अरब पाउंड), और सरकार TechFirst (18.7 करोड़ पाउंड) व AI Skills Boost के ज़रिए 2030 तक 1 करोड़ कर्मचारियों को अपस्किल करने का लक्ष्य रखती है।

Integrating AI in TVET: A practical guide for institutions

UNESCO-UNEVOC

UNESCO-UNEVOC guide (Yang Congkun, Wu Wenxi, Hannes Tegelbeckers; with Shenzhen Polytechnic University and Otto von Guericke University Magdeburg), published 2026-07-03, launched by webinar 2026-07-06, English only. Builds on Beijing Consensus 2019, Ethics of AI Recommendation 2021, GenAI Guidance 2023, AI Competency Frameworks 2024. Five principles (human agency, equity, pedagogical purposefulness, transparency, accountability/data protection) with a procurement rule: if a tool fails any one, do not proceed. Four ecosystem dimensions and a four-phase integration pathway (diagnosis, early adoption incl. automated marking, pedagogical deepening, ecosystem integration). Seven institutional domains; assessment tasks classified AI-excluded/permitted/integrated/enabled; AI-resilient methods; safety-critical occupations keep hands-on competency and human oversight. Launch deck opening figures: 62% of youth used AI daily in 2025 vs 30% formally taught; <10% of institutions follow formal guidance. Full PDF (unesdoc) not readable this week; post based on landing/launch pages, agenda and 33-slide launch deck.

June 2026 Layoff Report: Cuts Cool to 45,849, Down 53% from May, AI Leads Reasons for Fourth Consecutive Month

Challenger, Gray & Christmas

अमेरिकी नियोक्ताओं ने जून 2026 में 45,849 नौकरियां काटने की घोषणा की, जो मई से 53% कम है। AI को 14,029 कटौतियों (31%) में कारण बताया गया, जो लगातार चौथे महीने शीर्ष पर रहा। 2026 में साल की शुरुआत से AI-जनित कटौती 101,743 (लगभग 23%) रही, जबकि 2025 के पूरे साल का अनुमान 54,836 (5%) था। कुल कटौती 443,604 रही, जो 2025 की पहली छमाही (744,308) से 40% कम है। तकनीक क्षेत्र 139,156 (सालाना +83%) के साथ शीर्ष पर रहा, यानी सभी कटौतियों का लगभग एक-तिहाई। भर्ती योजनाएं 91,405 रहीं, जो सालाना 10% अधिक हैं।

Getting to all-of-the-above: A framework of solutions for AI's coming impacts on work and workers

Brookings Metro

ब्रुकिंग्स मेट्रो के ज़ेवियर दे सूज़ा ब्रिग्स का तर्क है कि AI-जनित नौकरी उथल-पुथल का कोई रामबाण नहीं, और वे समाधानों को चार परिवारों में बाँटते हैं — ब्रेक (ह्यूमन-इन-द-लूप नियम, स्वचालन प्रभाव आकलन), स्टीयर (श्रमिक-हितैषी AI डिज़ाइन के प्रोत्साहन), बफ़र (आधुनिक बेरोज़गारी बीमा, वेतन बीमा, पुनःप्रशिक्षण का अधिकार), और शिफ़्ट (छोटा कार्य-सप्ताह, संपदा-साझाकरण, कर पुनर्संतुलन)। मुख्य निष्कर्ष "महान बेमेल" — 1,000+ पेशों में AI एक्सपोज़र यूनियन सदस्यता से विपरीत रूप से जुड़ा है। निजी क्षेत्र यूनियन दर 6% से कम (BLS), 55% कारोबारी नेता व 68% निवेशक कम एंट्री-लेवल भर्ती की उम्मीद में, मेटा की 700 + 8,000 छँटनियाँ, तथा इलिनॉय, कैलिफ़ोर्निया, न्यू जर्सी और न्यूयॉर्क की राज्य-स्तरीय कार्रवाई का हवाला। चेतावनी: "अकेला प्रशिक्षण या पुनःप्रशिक्षण अच्छी नौकरियाँ पैदा नहीं करता।"

Annual Economic Report 2026, Chapter I: Progress and peril

Bank for International Settlements

BIS वार्षिक आर्थिक रिपोर्ट 2026 अध्याय I: कार्य-स्तरीय AI समय-बचत 20-50%, समग्र उत्पादकता वृद्धि 1% से कम, अधिक उजागर अमेरिकी क्षेत्रों में उत्पादकता वृद्धि कम रोजगार वृद्धि की कीमत पर, आय-कॉल में श्रम-इनपुट कटौती के बढ़ते संकेत, हाइपरस्केलर 1 ट्रिलियन डॉलर+ पूँजीगत व्यय की स्थिरता-जोखिम चेतावनी।

Anthropic Economic Index report: Cadences

Anthropic

Anthropic Economic Index जून 2026 "Cadences" रिपोर्ट, जो विश्लेषण करती है कि AI उपयोग मानवीय लय — कार्य-सप्ताह, दैनिक कार्यक्रम, प्रमुख तिथियाँ — को कैसे प्रतिबिंबित करता है। गोपनीयता-संरक्षी टेलीमेट्री (10 अप्रैल–10 जून 2026) और ~9,700 उत्तरदाताओं के जुड़े सर्वेक्षण पर आधारित। मुख्य निष्कर्ष: निजी उपयोग कार्य-दिवस ~35% से सप्ताहांत ~50% तक बढ़ता है; 14 अप्रैल को टैक्स सवाल 8 गुना बढ़े; 93% बातचीत उत्पाद बनाती है; उच्च-वेतन व्यवसाय (मार्केटिंग मैनेजर, प्रोग्रामर) 2.5 गुना टोकन और प्रति मोड़ 1.34 गुना उत्पाद; 35% से अधिक 12 महीनों में AI द्वारा अधिकांश कार्य की उम्मीद करते हैं फिर भी सबसे अधिक सौंपने वाले सबसे आशावादी (86% उत्पादकता लाभ, केवल 10% नौकरी का डर); शुरुआती करियर वाले सबसे चिंतित (1/3 कनिष्ठ नौकरी जाने की संभावना >60% मानते हैं); कंप्यूटर/गणित भूमिकाएँ उत्तरदाताओं का 30% बनाम अमेरिकी रोज़गार का 4%; शारीरिक व्यवसाय कम प्रतिनिधित्व। आधार डेटा: BLS OEWS (मई 2025), विश्व बैंक WDI, UN WPP।

What separates firms that use AI intensively from firms that don't?

European Central Bank

ECB SAFE सर्वेक्षण दौर 37 (अक्टूबर-दिसंबर 2025, यूरो क्षेत्र की 5,000+ कंपनियां): 70%+ कंपनियां AI इस्तेमाल करती हैं पर सिर्फ़ 7% गहनता से। गहन उपयोगकर्ता छोटी, युवा ICT/पेशेवर-सेवा कंपनियां हैं जो लागत-कटौती नहीं बल्कि विकास से प्रेरित हैं; 84% ने AI निवेश पूरा किया, कुल निवेश का ~20% AI को। मुख्य बाधाएं: कौशल की कमी (40%) और वित्त।

Human Capital, AI, and Labor Commoditization

arXiv

49,610 Upwork कर्मचारियों और 22.6 लाख अनुबंधों (2021Q1-2026Q1) का अध्ययन। जनरेटिव AI ने AI-उजागर श्रेणियों में मानव पूंजी संकेतों (योग्यता, अनुभव, प्रतिष्ठा) का महत्व 7.8% घटाया। अनुबंध मात्रा ~7% गिरी, माँग कम-लागत कर्मचारियों की ओर बढ़ी (हिस्सा 3.2%->7.9%), कीमत भार बढ़ा (1.1%->1.8%), उच्च बनाम निम्न मानव-पूंजी माँग अंतर सिकुड़ा (10.3%->6.2%)। 102 उप-श्रेणियों में औसत जोखिम 0.252; सर्वोच्च कानूनी अनुवाद 0.80, न्यूनतम फ़ोटोग्राफ़ी 0.02।

Workplace artificial intelligence use: A profile of sociodemographic and job characteristics

Statistics Canada

स्टैटिस्टिक्स कनाडा सर्वेक्षण: कनाडाई कामगारों में जेनरेटिव AI उपयोग एक साल से कम में 17% से 30% तक लगभग दोगुना (सितंबर 2024–जुलाई 2025), डिग्रीधारी विश्लेषणात्मक एवं ज्ञान-क्षेत्र की भूमिकाओं में केंद्रित।

PwC 2026 Global AI Jobs Barometer: Two futures for jobs in an AI era

PwC

PwC ने 27 देशों में 1 अरब+ नौकरी विज्ञापन विश्लेषित किए। AI-संपर्क कंपनियों में भर्ती 52% बनाम 36%, वेतन 24% बनाम 17% (2018 से)। AI कौशल वेतन प्रीमियम 62% (57% से ऊपर)। दो-पटरी बाज़ार: पेशेवर नौकरियाँ लोकतांत्रिक से 2 गुना तेज़, 42% तेज़ वेतन वृद्धि। AI-संपर्क शुरुआती भूमिकाएँ 2019 से 35% बढ़ीं, अन्य 10% घटीं ("वरिष्ठीकरण"); जूनियर AI भूमिकाएँ वरिष्ठ कौशल माँगने की 7 गुना संभावना। AI-कौशल नौकरियाँ 8 गुना तेज़ (69% बनाम 9%)। तकनीक/मीडिया/दूरसंचार 11% पर अग्रणी।

Agentic coding and persistent returns to expertise

Anthropic

Analysis of ~400,000 Claude Code sessions (Oct 2025-Apr 2026, ~235,000 users): users make ~70% of planning but only ~20% of execution decisions. Verified success 15% (novice) vs 28-33% (intermediate/expert); troubled-session recovery 4% vs 15%. Software occupations 34% vs other occupations 29%. Debugging share fell 33%->19%; average task value +27%.

Entry-level jobs support: AI bootcamps and tech training as government supports young people into the jobs of the future

UK Government (DSIT & DWP)

ब्रिटेन ने £2 करोड़ का अर्ली करियर्स जॉब्स अलायंस (प्रॉस्पेक्ट यूनियन सह-अध्यक्ष; माइक्रोसॉफ़्ट, एक्सेंचर, BAE सिस्टम्स, JD स्पोर्ट्स जैसे साझेदार), 4 लाख छात्रों तक पहुँचने वाला टेकफ़र्स्ट कार्यक्रम, 3.5 लाख नियुक्तियों और 360+ यूथ हब के ज़रिए लगभग 10 लाख युवाओं को सहारा देने वाली £82 करोड़ की यूथ गारंटी, और चरणबद्ध AI बूटकैंप (गर्मी 2026 उत्तर-पश्चिम → 2027-2028 राष्ट्रव्यापी) शुरू किया। राष्ट्रीय लक्ष्य: 2030 तक 1 करोड़ ब्रिटिश कर्मचारी AI में पुनः प्रशिक्षित (17 लाख कोर्स पूरे)।

Texas Business Outlook Surveys: Special Questions (AI), May 2026

Federal Reserve Bank of Dallas

Survey of 313 Texas executives (May 12-20, 2026). 66.2% of firms use AI (flat vs Dec 2025). Among 203 AI-using firms, 76.4% report no impact on their need for workers; only 10.4% report any decrease. But 25.7% expect a decrease over the next few years (29.3% among current users) - a ~2.5x gap between realized and expected cuts. 71.4% report higher productivity for AI-using employees, yet only 7.4% report higher wage growth for them.

Climbing the employment ladder tough when bottom rung is broken

Federal Reserve Bank of Dallas

डलास फेड के अर्थशास्त्रियों ने पाया कि उच्च AI-संपर्क वाले व्यवसायों में युवाओं (25 से कम) का रोज़गार 2022 से लगभग 13% गिरा। यह गिरावट छँटनी से नहीं बल्कि गिरती नौकरी-पाने की दर से है — युवाओं को पहली जगह में हायर ही नहीं किया जा रहा। AI अब संहिताबद्ध (पाठ्यपुस्तक) ज्ञान संभालता है जबकि मौन (अनुभव-आधारित) ज्ञान दुर्लभ रहता है, इसलिए फर्में एंट्री-लेवल भर्ती घटाकर सिद्ध, अनुभवी प्रतिभा के लिए प्रतिस्पर्धा करती हैं। कंप्यूटर सिस्टम्स डिज़ाइन में वेतन 2022 की पतझड़ से 16.7% बढ़ा (राष्ट्रीय 7.5%), अनुभव प्रीमियम के बढ़ने का प्रमाण।

Generative AI and the Reorganization of Labor Demand

arXiv

Wang, Wei & Wang (2026) measure AI exposure dynamically at the job-posting level across the U.S. economy using a two-stage LLM pipeline. Decomposing the decline in AI exposure: 52% comes from hiring reallocation, 39.5% from within-job task redesign; observable job characteristics explain ~90% of exposure changes (Oaxaca-Blinder). Senior roles adjust earlier via reallocation; junior roles via a broader mix of reallocation, redesign, and their interaction.

The adoption of AI by industrial sectors

PIIE

हफ़बावर और झांग के PIIE विश्लेषण में AI अपनाना कौशल-पक्षपाती पाया गया। उच्च-वेतन सेवा सेक्टर (सूचना, वित्त, पेशेवर सेवाएँ) 30%+ कंपनी अपनाने के साथ आगे, खुदरा/आतिथ्य/खाद्य सेवाएँ पीछे। बड़ी कंपनियाँ (250+) ~4% से ~12% तक तीन गुना (2023-2025); बड़ी-कंपनी रोज़गार हिस्सा 37.6% (2000) से 42.3% (2025)। वेतन और AI अपनाने के बीच मामूली सकारात्मक सहसंबंध। श्रम विस्थापन प्रभाव समय से पहले/अनिर्णायक माने गए।

How ChatGPT adoption broadened in early 2026

OpenAI Signals Research

OpenAI Signals Q1 2026 update documents ChatGPT consumer adoption broadening across age (35+ gaining share), gender (feminine-name users now majority), and geography (Dominican Republic +9, Haiti +9, Japan +8, Mexico +6, Tanzania +6, Brazil/Costa Rica/Myanmar/Papua New Guinea +5 in per-capita messaging rank between Q4 2025 and Q1 2026).

April 2026 Job Cuts Report: Cuts Rise 38% From March, YTD Cuts Down 50%

Challenger, Gray & Christmas

April 2026: 83,387 US job cuts (+38% MoM, -21% YoY). AI #1 reason at 21,490 cuts (26%), second straight month. YTD AI cuts 49,135 (16% of all 2026 cuts, up from 13%). YTD total 300,749 (-50% YoY). Technology led industries with 33,361 cuts in April (85,411 YTD, +33%). Hiring announcements down 69% MoM to 10,049.

Artificial Intelligence in German establishments: One in four has adopted generative AI (IAB-Kurzbericht 08/2026)

IAB (Institute for Employment Research)

IAB-Kurzbericht 08/2026 (फ़्रीड्रिख और कागेर्ल) के अनुसार जर्मन स्थापनाओं में जेनरेटिव AI अपनाव 5% (2023) से बढ़कर लगभग पाँच गुना 24% (2025) हो गया, जो ~15,000 स्थापनाओं के IAB-Betriebspanel सर्वेक्षण पर आधारित है। 200+ कर्मचारियों वाली फ़र्मों में 48% बनाम 10 से कम में 21% अपनाव। अग्रणी क्षेत्र सूचना व संचार (59%) और वित्त व बीमा (50%) हैं, जबकि निर्माण, आतिथ्य, परिवहन और कच्चा माल 15% से नीचे रहते हैं। अपनाने वालों में से 90% तैयार उपकरण इस्तेमाल करते हैं; केवल 16% ख़रीदे मॉडल प्रशिक्षित करते हैं और 6% अपने बनाते हैं। लगभग आधी ने वित्तीय निवेश किया, 25%+ AI प्रशिक्षण देती हैं, और 20% के पास कार्यस्थल AI नियम हैं।

AI growth acceleration versus distributional fairness

Brookings Institution

Brookings synthesis arguing AI-driven growth acceleration is plausible but not guaranteed. Diffusion is highly uneven across sectors, firms, countries, demographic groups. Relative employment declines for early-career workers in AI-exposed occupations identified using high-frequency payroll data. Five-pillar policy recommendation including complementary capabilities investment, strategic procurement, transition tools, measurement standards, broad-based asset ownership.

What Jobs Can AI Learn? Measuring Exposure by Reinforcement Learning

arXiv

तोमेई और क्लाइन टीसेलिंक ने RL फ़ीज़िबिलिटी इंडेक्स (RLFI) पेश किया। 894 व्यवसायों के 17,951 O*NET कार्यों को इस पर स्कोर किया कि रीइन्फोर्समेंट लर्निंग उन्हें सीख सकती है या नहीं। भौतिक-व्यवहार्यता द्वार 40.7% कार्यों को शून्य करता है। RLFI कुल मिलाकर Eloundou LLM एक्सपोज़र से 0.88 सहसंबंधित पर डिजिटल रूप से व्यवहार्य कार्यों में केवल 0.15 — पहुँच-योग्य नौकरियों में AI क्या सीख सकता है, इस पर मतभेद। उच्च RLFI/कम LLM एक्सपोज़र: पावर प्लांट ऑपरेटर, रेलरोड कंडक्टर, एयरक्राफ़्ट कार्गो हैंडलिंग सुपरवाइज़र। कम RLFI/उच्च LLM एक्सपोज़र: संगीतकार, डॉक्टर, प्राकृतिक विज्ञान प्रबंधक। RL एक्सपोज़र वेतन में कूबड़-आकार (ऊपरी-मध्य चरम, प्रति लॉग-वेतन +12.2p), वरिष्ठता में उलटा U। ChatGPT-पश्चात DiD: +1SD RL एक्सपोज़र ~ नौकरी अवसर -2.9% (p=0.085)।

Evaluating the Impact of AI on the Labor Market: March 2026 CPS Update

Yale Budget Lab

March 2026 CPS update finds no meaningful shift from December across most categories. Occupational dissimilarity, industry dissimilarity, and exposure/usage metrics all remain flat or continue along existing trends. Notable uptick in occupational mix dissimilarity between older and younger college graduates (high end of historical range). Anthropic February 2026 usage data shows observed usage more associated with automation than augmentation, consistent with prior November 2025 release. Conclusion: anxiety widespread but data suggests AI labor market impact remains largely speculative — picture reflects stability, not major disruption at economy-wide level.

Today at Work 2026, Issue 1: AI Powers Into the Workplace

ADP Research

ADP 2025 ग्लोबल वर्कफ़ोर्स सर्वेक्षण (2.5 करोड़+ अमेरिकी कर्मचारियों का पेरोल डेटा + 34 देशों के 6 लाख+ कर्मचारी): 50% कर्मचारी हफ्ते में कई बार और 20% लगभग रोज़ AI इस्तेमाल करते हैं। रोज़ के उपयोगकर्ता ज़्यादा पूर्ण जुड़ाव (30% बनाम 14%, आधार 19%) और कम बोझ (11% बनाम 23%) दिखाते हैं, फिर भी क्षमता से कम उत्पादक महसूस करने की 4 गुना संभावना रखते हैं। युवा और पुरुष अपनाने में आगे; AI-संवेदनशील क्षेत्रों (सॉफ़्टवेयर, ग्राहक सहायता) में 22-25 वर्ष के शुरुआती करियर कर्मचारी रोज़गार चिंता का सामना करते हैं।

From Clerks to Agentic AI: How Will Technology Transform the Labor Market in Finance?

arXiv

Yu & Li (April 2026) track 40 years of financial labor productivity across three regimes: computerization (1.36 AUM/employee coefficient), indexing (2.42), and agentic AI era (3.39 — 149% higher than baseline). AI exposure correlates +0.5843 with AUM/employee but -0.0535 with revenue/employee, indicating volume-over-yield strategy. Mid-layer coordination roles face greatest pressure.

Workers exposure to AI: What indicators tell us and what they don't

ILO

ILO Research Brief warning that AI exposure indicators (3.3% global highest exposure, 34% HIC vs 11% LIC, female 4.7% vs male 2.4%) measure technical task overlap with current AI capabilities — not predictions of job displacement.

The AI Jobs Transition Framework: Mapping AI's Near-Term Impact on Jobs

OpenAI

OpenAI economist Alex Martin Richmond maps 921 US occupations covering 99.7% of US employment using a 4-dimension framework: technical capability, human necessity (regulatory/relational/physical), demand elasticity, and ChatGPT consumer usage data (H2 2025). Findings: 18% face higher short-term automation risk (legal, education, office/administrative); 46% likely see less change; 24% may see employment decline as task composition shifts; 12% could grow because of AI. Insulated roles include teachers, nurses, lawyers due to regulatory, relational and physical necessity. ChatGPT usage 3x higher in high-risk jobs.

ChatGPT Usage and Adoption Patterns at Work

OpenAI

OpenAI April 2026 workplace report: 28% of US workers use ChatGPT (up from 8% in 2024), Fortune 500 adoption 93%, 7M+ Enterprise/Team seats. Four core tasks: writing, research, programming, analysis. Adoption split sharply between IT/finance (deep) and healthcare/construction/transportation (lagging).

AI Is Probably Not (Yet) the Reason for Labor Market Weakening

The Budget Lab at Yale

येल बजट लैब मार्च 2026 CPS विश्लेषण: अमेरिकी बेरोजगारी 4.3% तक बढ़ी लेकिन AI एक्सपोज़र/स्वचालन/संवर्धन मेट्रिक्स रोजगार परिवर्तन से असंबंधित। श्रम बाजार कमजोरी का मुख्य कारण AI नहीं बल्कि आव्रजन में मंदी है। ChatGPT 2022 के बाद से असमानता सूचकांक स्थिर।

WorkRB: A Community-Driven Evaluation Framework for AI in the Work Domain

arXiv

Evaluation framework for AI work-domain capabilities. Low blog value (framework paper, not labor market impact evidence).

Inside the AI Index: 12 Takeaways from the 2026 Report

Stanford HAI

Annual AI Index 2026 report highlights: software developer employment (22-25) down ~20% since 2024, 14-26% productivity gains in customer support/SW dev, 73% expert vs 23% public optimism gap, US ranks 24th in AI adoption (28.3%), AI researcher US inflow down 89% since 2017, GenAI consumer surplus $172B, 53% global usage, physician note-writing time reduced 83%.

Is your job safe?

ADP Research

ADP Research Global Workforce Survey of 39,000+ workers found only 25% globally and 28% in the U.S. feel their jobs are safe. Age breakdown: 18-26: 26%, 27-39 & 40-54: 30%, 55-64: 23%. Three contributing factors: geopolitical concerns, AI impact, ongoing inflation. Workers feeling secure are 6× more likely to be fully engaged and 3.3× more likely to report high productivity. Authored by Nela Richardson Ph.D. April 7 2026.

AI Impact on Labor: Double-Edged Sword

Morgan Stanley

Morgan Stanley analysis: AI added at most 0.1 percentage point to overall US unemployment rate. Gen AI impact is double-edged — same technology that automates tasks also augments labor and raises productivity.

AI Eliminating 16,000 U.S. Jobs Per Month

Goldman Sachs

Goldman Sachs economist Elsie Peng finds AI substituting 25K jobs/month while augmenting 9K, net loss 16K. Gen Z hardest hit with 3.3pp wage gap widening. Insurance clerks, bill collectors at highest substitution risk.

Challenger Report: March Cuts Rise 25% From February, AI Leads Reasons

Challenger, Gray & Christmas

March 2026: 60,620 total job cuts, AI led all reasons with 15,341 cuts (25%). Q1 YTD: 217,362 total, 27,645 AI (13%). Cumulative AI cuts since 2023: 107,094. Tech sector Q1 up 40%, Healthcare record Q1 high.

How AI may reshape career pathways to better jobs

Brookings Institution

Analysis of 70M STARs (non-degree workers): 15.6M in high AI-exposed roles, 3.5M at dual risk (high exposure + low adaptive capacity). Nearly half of career advancement pathways from Gateway to Destination occupations are highly AI-exposed. Florida metros most affected. Uses Anthropic observed exposure measure.

The 2026 AI Index Report

Stanford HAI

स्टैनफोर्ड HAI की 2026 AI इंडेक्स रिपोर्ट AI क्षमता, निवेश और अपनाने की तेज़ी का दस्तावेज़ीकरण करती है, और AI-प्रभावित प्रवेश-स्तर के व्यवसायों में युवा श्रमिकों के बीच रोज़गार में गिरावट जैसे प्रारंभिक श्रम-बाज़ार संकेतों को उजागर करती है।

2026 AI Index Report: Economy Chapter

Stanford HAI

Economy chapter of 2026 AI Index. Key findings: software developers aged 22-25 employment fell nearly 20% from 2024; ~1/3 of surveyed organizations anticipate workforce reductions over coming year; expected decreases concentrated in service operations, supply chain, and software engineering; productivity gains measured at 14-15% (customer support) and 26% (software development). AI labor effects concentrated in hiring pipelines and youngest workers in exposed occupations.

Forecasting the Economic Effects of AI

National Bureau of Economic Research

Karger, Kuusela, Tetlock et al. (15 co-authors) ran a structured forecasting exercise across 5 groups (academic economists, AI company employees, policy researchers, superforecasters, general public). Median GDP growth forecast through 2050: 2.5% (vs CBO baseline 2.0%/1.7%). Under rapid AI scenario: GDP ~4%/year, labor force participation drops 62.7% to 55%, ~10M jobs displaced by AI specifically. Main driver of disagreement: not AI capability timelines, but what high-capability AI does to the economy. Policy preferences: experts favor targeted retraining + portable benefits; general public prefers UBI + federal job guarantees.

AI and the US Labour Market: Effects on Employment Growth

European Central Bank

ECB आर्थिक बुलेटिन (अंक 4/2026) में पाया गया कि अमेरिका में उच्च AI-प्रतिस्थापन जोखिम वाले व्यवसाय 2019-2025 में 4% से अधिक घटे जबकि निम्न-जोखिम वाले 13% बढ़े, ~15 प्रतिशत-अंक का रोज़गार अंतर जो 2022 के अंत में ChatGPT लॉन्च के बाद सबसे तेज़ चौड़ा हुआ। निम्न-जोखिम हिस्सा 23%->25% बढ़ा, उच्च-जोखिम 35%->33% गिरा। वेतन वृद्धि पर कोई महत्वपूर्ण प्रभाव नहीं। क्षेत्र स्थिर-प्रभाव अंतर-में-अंतर।

Crashing Waves vs. Rising Tides: Preliminary Findings on AI Automation from Thousands of Worker Evaluations of Labor Market Tasks

MIT / arXiv

MIT researchers evaluated 3,000+ text-based O*NET tasks through 17,000+ worker assessments. Found "rising tides" pattern: AI task success climbing from ~50% (2024-Q2) to ~65% (2025-Q3), projected 80-95% by 2029. Little evidence of sudden "crashing waves" displacement. Adoption timelines expected to substantially lag capability gains.

Economics of Human and AI Collaboration: When is Partial Automation More Attractive Than Full Automation?

arXiv

MIT/IBM working paper develops a unified framework for optimal task automation. Convex AI accuracy cost curve makes partial automation the cost-minimizing equilibrium. 11% of computer-vision-exposed labor compensation captured at firm level; share rises sharply under economy-wide deployment. Calibrated with O*NET task data, 3,778 domain expert surveys, GPT-4o decompositions.

Agentic AI and Occupational Displacement: A Multi-Regional Task Exposure Analysis of Emerging Labor Market Disruption

arXiv

Introduces Agentic Task Exposure (ATE) score framework. Analyzes 236 info-intensive occupations across 5 US tech hubs. 93.2% cross moderate-risk threshold by 2030 in Tier 1 regions. High-risk: credit analysts, judges, sustainability specialists (ATE 0.43-0.47). 17 emerging occupational categories in AI governance. Authors: Gupta & Kumar.

New ILO-World Bank paper highlights uneven global impact of generative AI on jobs

ILO / World Bank

ILO-World Bank joint study, WDR 2026 background paper. 135 देशों में GenAI labor market exposure analysis. Advanced economies में clerical/professional roles में सबसे ज़्यादा exposure; developing economies में digital gaps की वजह से productivity gains से पहले disruption का ख़तरा. महिलाएं और युवा disproportionately vulnerable.

The AI Layoff Trap: Automation Arms Race

arXiv (Wharton)

Wharton arXiv paper: AI layoff trap — companies automate karne ki race mein collective action problem create kar rahi hain jo backfire ho sakta hai.

A people-first vision for the future of work in the age of AI

Brookings Institution

Policy vision by Friedler, Booth, Schrank, Helper proposing worker-centered AI policies: minimum staffing laws in care sectors, tripartite institutions, participatory AI design. Cites 50%+ Americans fear AI displacement (Reuters/Ipsos). Occupations mentioned: teachers, nurses, social workers, software engineers, manufacturing, utility, guest room attendants.

Economic Index March 2026: Learning Curves

Anthropic

Anthropic Economic Index March 2026: 49% jobs mein 25%+ tasks AI se ho rahe hain. Learning curves dikhati hain ki early adopters aage nikal rahe hain.

How AI Is Transforming Work at Anthropic (Internal Data)

Anthropic

Anthropic internal data: engineers apne 59% kaam mein AI use karte hain. Actual usage patterns vs external estimates ka farq dikhata hai.

AI Hiring Is Booming While Everything Else Stalls

Stanford HAI + Indeed

Stanford HAI + Indeed data: AI hiring surge kar rahi hai jabki non-AI hiring stall — two-track labor market ban raha hai.

Building Pro-Worker AI

Brookings (Acemoglu, Autor, Johnson)

Acemoglu, Autor, Johnson (Brookings): teen leading economists ka argument — current AI development path workers ko harm karti hai.

AI and the Entry-Level Job

Harvard Business Review + IBM

IBM ne entry-level hiring triple ki jabki competitors cut kar rahe the. Contrarian AI workforce strategy par HBR case study.

How AI Is Changing the Labor Market

Dallas Federal Reserve + HBR

HBR + Dallas Fed synthesis: AI workers ko alag-alag channels se simultaneously help aur hurt karti hai — productivity vs displacement.

Gen AI Wont Make Your Employees Experts

Stanford + Harvard

Stanford-Harvard study: AI expertise gaps bridge nahi kar sakti. 8-month field study mein AI existing skill differences ko amplify karti hai.

AI and Young Workers: Employment Effects

Dallas Federal Reserve

Dallas Fed data: tech mein youth employment 2022 early se decline ho rahi hai — ChatGPT launch se months pehle se.

Equipping workers with insights about compensation

OpenAI + University of Michigan

ChatGPT wage usage study: In Jan-Feb 2026, US consumer ChatGPT users sent ~3M messages/day about wages, compensation, or earnings. Workers use ChatGPT to navigate wage info gaps, especially in labor markets with high uncertainty. Joint study with University of Michigan on how Americans engage with AI for wage information. Released 2026-03-17.

Disruption without dividend? How the digital divide and task differences split GenAI's global impact

International Labour Organization

ILO वर्किंग पेपर 166 जनरेटिव AI के 135 देशों में असमान श्रम-बाज़ार प्रभावों की जांच करता है। उन्नत अर्थव्यवस्थाएं अधिक स्वचालन जोखिम (रोज़गार का 30-32%) का सामना करती हैं, पर विकासशील देश एक विरोधाभास में हैं: विस्थापन के प्रति संवेदनशील श्रमिकों के पास पहले से इंटरनेट है, जबकि AI उत्पादकता से लाभ की स्थिति वाले श्रमिकों के पास विश्वसनीय डिजिटल बुनियादी ढांचा नहीं है। पेपर चेतावनी देता है कि कुछ विकासशील अर्थव्यवस्थाओं में "लाभ से पहले विघटनकारी प्रभाव" सामने आ सकते हैं।

New Data Show No AI Jobs Apocalypse — For Now

Brookings Institution

Brookings 33-month analysis: AI se mass unemployment nahi aayi, lekin specific sectors mein warning signs dikh rahe hain.

Evaluating the Impact of AI on the Labor Market: January/February CPS Update

Yale Budget Lab

33 months after ChatGPT release, AI exposure metrics, occupational dissimilarity, and industry dissimilarity all flat or within historical ranges. Recent vs older college graduate dissimilarity in 30-33% band since Jan 2021. Anthropic Feb 2026 usage data tilts toward automation rather than augmentation. Direct quote: exposure/automation/augmentation measures show no sign of being related to changes in employment or unemployment.

World Employment and Social Outlook: Trends 2026

ILO

ILO flagship report: global unemployment 186M, AI productivity gains ke bawajood job recovery nahi ho rahi. 408M logon ke paas adequate work nahi.

Research on AI and the Labor Market Is Still in the First Inning

Brookings Institution

Brookings meta-analysis: AI labor research abhi shuruat mein hai — zyada tar claims evidence se aage hain.

Karpathy AI Job Exposure Score for Every US Job

Andrej Karpathy / Fortune

Karpathy (ex-OpenAI) ne har US job ko AI exposure ke liye score kiya. White-collar professionals sabse zyada vulnerable.

Generative AI and Jobs: Refined Global Index of Occupational Exposure

ILO

ILO refined index 138 countries: occupational segregation patterns ke karan women ko 2x automation risk.

AI Labor Displacement and the Limits of Worker Retraining

Brookings Institution

Brookings ne historical retraining programs ka analysis kiya — displaced workers ke liye success rates limited hain.

Measuring US Workers Capacity to Adapt to AI-Driven Job Displacement

Brookings Institution

Brookings: 6.1M US workers high AI exposure lekin adapt karne ki capacity low — structural vulnerability mapping.

AI and Young-Adult Jobs: The Real Mystery

Economic Innovation Group

EIG study: AI-youth-jobs narrative ko challenge karti hai — employment decline ke non-AI causes hain jaise post-pandemic corrections.

Labor market impacts of AI: A new measure and early evidence

Anthropic Economic Research

Anthropic ने "देखी गई एक्सपोज़र" प्रस्तुत की — असली कार्यप्रवाहों में AI की वास्तविक तैनाती को मापने वाला नया मीट्रिक। Computer Programmers 75% पर शीर्ष, पूरी Computer & Math श्रेणी 33% (सैद्धांतिक 90% की तुलना में)। 30% श्रमिकों की देखी गई एक्सपोज़र शून्य है। उच्च-एक्सपोज़र क्षेत्रों में 22-25 आयु की नई भर्ती ~0.5pp गिरी।

Reverse gear: how AI is bringing vocational occupations back

Cedefop

Cedefop analysis of EU online job advertisements shows VET (vocational education and training) occupations' share fell from 36% (2019-mid 2022) to 33% (mid 2022 trough), then recovered above 36% by early 2025 — coinciding with the emergence of generative AI in late 2022. Declining categories: software developers, sales & marketing, customer info workers, database specialists. Growing categories: engineering technicians, machinery mechanics, construction trades, transport workers.

Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI

NBER

Danish admin data + adoption surveys show rapid AI chatbot adoption and reported productivity gains, but precise null effects on earnings and recorded hours at worker/workplace level (within 2%) two years after ChatGPT launch. Employers reorganized tasks rather than reducing workforce.

Generative AI, Occupational Segregation and Gender Equality in the World of Work

ILO

यह ILO अध्ययन जांचता है कि जनरेटिव AI व्यावसायिक लैंगिक विभाजन के साथ कैसे जुड़ता है, और निष्कर्ष निकालता है कि महिलाओं के अत्यधिक प्रभावित लिपिकीय भूमिकाओं में होने की संभावना पुरुषों की तुलना में लगभग दोगुनी है, जो लक्षित नीति के बिना श्रम-बाज़ार असमानताओं को बढ़ा सकता है।

Generative AI and Jobs: A Refined Global Index of Occupational Exposure (Research Brief)

ILO

यह ILO शोध संक्षेप जनरेटिव AI के प्रति व्यावसायिक प्रभाव का एक परिष्कृत वैश्विक सूचकांक प्रस्तुत करता है और पाता है कि लिपिकीय व प्रशासनिक नौकरियां सबसे अधिक प्रभावित हैं तथा महिलाएं ऐसी भूमिकाओं में अधिक केंद्रित होने के कारण पुरुषों की तुलना में अधिक प्रभावित होती हैं।

Tracking the Impact of AI on the Labor Market

Yale Budget Lab

येल बजट लैब वर्तमान जनसंख्या डेटा का उपयोग करके AI के श्रम-बाज़ार प्रभाव पर नज़र रखती है और पाती है कि ChatGPT के लॉन्च के बाद से व्यावसायिक प्रभाव काफी हद तक स्थिर रहा है, तथा रोज़गार में बड़े पैमाने पर व्यवधान का स्पष्ट संकेत अभी तक नहीं है।

India Brief: Economic Index

Anthropic

Anthropic India Brief: duniya ka 2nd largest AI user base lekin per-capita adoption mein 101st — scale vs depth gap.

AI, Productivity, and the Workforce: Evidence from Corporate Executives

NBER

Survey of 750 corporate executives. Over half invested in AI. Little evidence of near-term aggregate employment declines. Larger companies anticipate reductions, smaller firms expect gains. Productivity paradox: executives perceive larger gains than data shows.

February 2026 Job Cuts Report

Challenger, Gray & Christmas

Challenger report: Jan-Feb 2026 mein 12,304 AI-related job cuts, hiring plans 56% year-over-year gire.

Fed's Barr Names 3 AI Scenarios — Including 'Essentially Unemployable'

Bank for International Settlements (BIS Review)

AI Doesnt Reduce Work — It Intensifies It

Harvard Business Review

HBR 8-month field study: AI workload reduce karne ki jagah work intensity badha rahi hai — productivity paradox.

An AI Productivity Boom? Don't Count Your (Productivity Data) Chickens

Yale Budget Lab

Skeptical analysis of AI productivity boom claims. Productivity data is too noisy and lagged to confirm GenAI productivity gains.

Yale Budget Lab: AI Exposure Hasn't Moved Workforce Distribution Since ChatGPT

The Budget Lab at Yale

Is Generative AI a Job Killer? Evidence From the Freelance Market

Brookings Institution

Brookings freelance market study: high-skilled freelancers ko AI se sabse zyada hit — low-skill displacement narrative ko contradict karta hai.

Firm Data on AI

NBER

Survey of 6,000 executives across US/UK/Germany/Australia finds 69% use AI but 90% report zero employment/productivity impact. Executives predict -0.7% employment next 3 years; employees expect +0.5% growth.

Building Pro-Worker AI

The Hamilton Project (Brookings)

Acemoglu, Autor और Johnson का तर्क है कि AI को श्रमिकों को प्रतिस्थापित करने के बजाय उनका पूरक बनाने की दिशा में ले जाना चाहिए; वे गलत प्रोत्साहन और स्वचालन-पक्षपात जैसी बाधाओं की पहचान करते हैं और AI को अधिक श्रमिक-हितैषी बनाने के लिए नौ नीतिगत उपाय प्रस्तावित करते हैं।

Payrolls to Prompts: Firms Replacing Labor With AI

arXiv (Payrolls to Prompts)

arXiv study: companies freelance budgets se har dollar cut ke liye AI par sirf 3 cents kharch kar rahi hain — substitution incomplete hai.

Graph-Based Analysis of AI-Driven Labor Market Transitions

arXiv

Analyzes 9,978 Egyptian job postings using knowledge graphs. Finds 20.9% of jobs face high automation risk, but only 24.4% of at-risk workers have viable transition pathways. 75.6% face structural barriers requiring comprehensive reskilling, not incremental upskilling. Process-oriented skills appear in 15.6% of feasible transitions.

[제2026-3호] '쉬었음' 청년층의 특징 및 평가: 미취업 유형별 비교 분석 (Characteristics and Assessment of 'Resting' Youth)

Bank of Korea

Analysis of Korean youth in "resting" status: 6.3%p higher probability for non-college youth, reservation wage 31M KRW (not high), AI cited as labor market deterioration factor, debunks "high standards" narrative

How AI is changing early careers: A view from entry-level workers

PwC + World Economic Forum

PwC+WEF joint survey of 9,394 entry-level workers across 48 economies. 47% curious about AI, 38% excited, 29% worried. 76% say job security is most important factor, but only 53% feel confident. Presented at Davos 2026.

Companies Are Laying Off Workers Because of AIs Potential, Not Performance

Harvard Business Review

HBR analysis: CEOs AI potential ke basis par layoff kar rahe hain, demonstrated performance par nahi. 50 mein se sirf 1 AI investment transformative.

Anthropic Economic Index: January 2026

Anthropic

Anthropic Economic Index: actual AI productivity gain 1.0% hai, headline 1.8% nahi — zyada tar usage augmentation hai, automation nahi.

Looking for the Ladder: Is AI Impacting Entry-Level Jobs?

Economic Innovation Group

इस EIG वर्किंग पेपर में Zanna Iscenko और Fabien Curto Millet (Google अर्थशास्त्र टीम) विश्लेषण करते हैं कि क्या AI प्रवेश-स्तर रोज़गार को कमज़ोर कर रहा है। उन्हें AI-प्रभावित व्यवसायों में नौकरी पोस्टिंग में अधिक गिरावट मिली, पर यह मोड़ 2022 में शुरू हुआ — ChatGPT के सार्वजनिक रिलीज़ से महीनों पहले। यह समय बड़े भाषा मॉडल की शुरुआत के बजाय बढ़ती ब्याज दरों के व्यापक आर्थिक बदलाव से बेहतर मेल खाता है।

Payrolls to Prompts: Firm-Level Evidence on the Substitution of Labor for AI

arXiv

Ryan Stevens (Ramp applied science) analyzes firm-level spending on Ramp expense management platform (2021 Q3 - 2025 Q3). Top-exposed firms substitute $1 in labor for only $0.03 in AI spend (33x cost savings); mid-exposed firms at $0.30. Online labor market spending fell from 0.66% (2021 Q4) to 0.14% (2025 Q3); AI spending rose from 0% to 2.85% over same period. 50%+ of firms reduced online labor spending to 0%. Limitation: covers online freelance markets only, no occupation-level decomposition.

AI-Exposed Jobs Deteriorated Before ChatGPT

University of Pittsburgh + RAND

Pittsburgh/RAND study 10.5M LinkedIn profiles: AI-exposed jobs ChatGPT launch se 8-10 months pehle se deteriorate hone lage the.

AI is reshaping entry-level hiring while lifting pay for experienced workers

Federal Reserve Bank of Dallas

डलास फेड के अर्थशास्त्री ChatGPT के 2022 के अंत में रिलीज़ होने के बाद 200 से अधिक व्यवसायों में रोज़गार और वेतन रुझानों की जांच करते हैं। उन्हें मिला कि AI सबसे अधिक प्रभावित उद्योगों में रोज़गार घटा रहा है (कंप्यूटर सिस्टम डिज़ाइन में लगभग 5% गिरावट) जबकि उन्हीं क्षेत्रों में अनुभवी श्रमिकों का वेतन बढ़ा रहा है। प्रवेश-स्तर श्रमिक सबसे बड़ी चुनौती का सामना करते हैं क्योंकि AI संहिताबद्ध ज्ञान की नकल कर सकता है पर वर्षों के अनुभव से बना मौन ज्ञान नहीं।

Enhancing Worker Productivity Without Automating Tasks: A Different Approach to AI and the Task-Based Model

NBER

Agrawal/McHale/Oettl: AI as productivity tool vs task replacer, wage inequality depends on skill distribution

The end of work feels near. How do people perceive the impact of digital technologies and automation?

IAB / Labour Economics

अमेरिका और जर्मनी के 5,147 कामगारों पर सर्वे प्रयोग (2019, YouGov)। आधे से ज़्यादा मानते हैं कि ऑटोमेशन कुल बेरोज़गारी बढ़ाएगा और ~90% असमान असर की उम्मीद करते हैं, पर 30% से कम अपनी नौकरी को लेकर चिंतित हैं (दोनों के बीच सहसंबंध 0.1 से कम)। वैज्ञानिक जानकारी (Graetz & Michaels 2018 — रोबोट ने कुल रोज़गार उल्लेखनीय रूप से नहीं घटाया) देने पर कुल बेरोज़गारी का डर ~0.15 SD घटा और 4 हफ़्ते बाद (n=2,225) भी बना रहा। असर पूर्व-मान्यताओं के अनुसार अलग-अलग रहा। यह जनरेटिव AI से पहले का डेटा है।

AI 인재 5.7만 명 시대, 왜 기업은 사람이 없다고 할까?

한국은행

Korea has 57K AI specialists but 6% wage premium (vs US 25%), 16% brain drain, 30% firms lack AI job definitions.

Preparing for 2040: four AI-powered scenarios for the future of continuing skills development

Cedefop

Cedefop foresight report naming AI the most influential yet unpredictable force shaping continuing skills development (CSD) by 2040, presenting four scenarios (A opportunities / B polarisation / C slow adoption / D dystopia) and cross-cutting red flags. Paired with the 2024 European AI skills survey (42% need AI skills vs 15% trained = 27pp gap).

AI Jobs Barometer 2025

PwC

PwC barometer: AI-exposed jobs mein 4x productivity gains aur non-exposed roles ke comparison mein 56% wage premium.

Stanford AI Experts Predict What Will Happen in 2026

Stanford HAI

2026 predictions: emergence of high-frequency AI economic dashboards tracking task/occupation-level productivity, displacement, new roles. Shift from speculation to careful measurement. Round-up prediction article, not primary research.

Beyond Automation: Redesigning Jobs with LLMs to Enhance Productivity

arXiv

UK Civil Service study analyzing 193,497 job vacancies and 1,542,411 tasks for AI exposure. Finds productivity gains, not just displacement. Authors propose redesign framework: automate, optimize, reallocate.

AI 전문인력 현황과 수급 불균형: 규모, 임금, 이동성 분석

한국은행

BOK Issue Note 2025-36: 57K AI workforce with 58% holding graduate degrees, 69% large firms plan to expand AI hiring.

Incorporating AI Impacts in BLS Employment Projections 2024-34

Bureau of Labor Statistics

BLS ne pehli baar 2024-34 official employment projections mein AI impacts ko incorporate kiya — methodology shift.

Agents, Robots, and Us: Skill Partnerships in the Age of AI

McKinsey Global Institute

MGI report: $2.9T US value by 2030, 57% work hours automatable, 40% jobs highly automatable, 70%+ skills transferable

AI 확산 초기, 청년고용은 왜 감소하는가?

한국은행

Youth employment declined 2.11M over 3 years with 98.6% in AI-exposed sectors. Junior workers with codified knowledge most vulnerable.

The State of AI: Global Survey 2025

McKinsey & Company (QuantumBlack)

मैकिन्ज़ी के QuantumBlack ने जून-जुलाई 2025 में 105 देशों के 1,993 प्रतिभागियों का सर्वेक्षण किया। लगभग 88% उत्तरदाता कम से कम एक व्यावसायिक कार्य में नियमित AI उपयोग की रिपोर्ट करते हैं, जो एक साल पहले 78% था, हालांकि अधिकांश उद्यम अभी प्रयोग या पायलट चरण में हैं और केवल एक-तिहाई ने स्केलिंग शुरू की है। 62% AI एजेंट्स के साथ प्रयोग कर रहे हैं और 23% एजेंटिक सिस्टम स्केल कर रहे हैं, फिर भी केवल 39% उद्यम-स्तरीय EBIT प्रभाव बताते हैं।

AI 확산과 청년고용 위축: 연공편향(seniority-biased) 기술변화를 중심으로 [BOK 이슈노트 제2025-30호]

한국은행 (Bank of Korea)

BOK Issue Note No. 2025-30. In Korea over the past 3 years, youth (ages 15-29) employment in high-AI-exposure sectors fell by 211,000 jobs, of which 208,000 (98.6%) occurred specifically in AI-high-exposure sectors. Senior (50+) employment grew by 209,000 in same period, with 146,000 in AI-exposed sectors. AI diffusion exhibits 'seniority-biased technological change' — entry-level (codifiable, routinized) jobs replaced by AI, while jobs requiring tacit knowledge and social skills show complementarity. Korea GenAI adoption rate 63.5% (work-use 51.8%) — roughly 2x US, 8x faster diffusion than internet adoption.

AI and Demographic Changes

Yale Budget Lab

Martha Gimbel analysis: AI exposure intersects with workforce aging and immigration. Some aging-heavy occupations (legal secretaries, admin assistants) show higher AI exposure; passenger attendants show minimal applicability. AI exposure concentrates in occupations with lower shares of foreign-born workers. Commentary piece, no numerical breakdowns in article body.

GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks

OpenAI

GDPval benchmark: 1,320 tasks across 44 knowledge-work occupations in 9 top-GDP sectors (Real estate, Government, Manufacturing, Professional services, Health care, Finance, Retail, Wholesale, Information). Top models (GPT-5, Claude Opus 4.1) rated as good as or better than humans in ~50% of tasks. 100x faster and cheaper than experts. Occupations include: software developers, lawyers, registered nurses, mechanical engineers, accountants, financial analysts, customer service reps, pharmacists, project management specialists, police supervisors, producers/directors, and others. Based on O*NET + BLS May 2024 wage data.

Remote Labor Index: Measuring AI Automation of Remote Work

arXiv

Introduces a Remote Labor Index to measure AI automation capability across remote-work tasks. Key finding: AI capabilities on remote-work benchmarks are rising rapidly but remain below human baseline for complex multi-step tasks. Relevant for occupations dominated by remote knowledge work.

Evaluating the Impact of AI on the Labor Market: Current State of Affairs

The Budget Lab at Yale

येल के बजट लैब का यह विश्लेषण मूल्यांकन करता है कि क्या AI मापने योग्य रूप से अमेरिकी श्रम बाज़ार को पुनर्आकार दे रहा है, व्यावसायिक और उद्योग असमानता मेट्रिक्स के साथ AI-एक्सपोज़र मापों का उपयोग करते हुए। डेटा ChatGPT की शुरुआत के बाद श्रम-बाज़ार संरचना में परिवर्तन दर में कोई पर्याप्त त्वरण नहीं दिखाता; असमानता और एक्सपोज़र मेट्रिक्स स्थिर हैं या पूर्व रुझानों का पालन करते हैं। लेखक निष्कर्ष देते हैं कि यह तस्वीर बड़े पैमाने पर व्यवधान के बजाय स्थिरता दर्शाती है।

AI and jobs: A review of theory, estimates, and evidence

arXiv

Meta-review of AI exposure and employment literature. Synthesizes theoretical frameworks, empirical estimates, and emerging evidence across 2023-2025. Tests consistency of exposure scores (Felten, Webb, Pizzinelli) with observed hiring patterns.

How People Use ChatGPT (NBER Working Paper 34255)

OpenAI / NBER

Aaron Chatterji, Thomas Cunningham, David J. Deming, Zoe Hitzig, Christopher Ong, Carl Yan Shan, Kevin Wadman. NBER WP 34255 (Sep 2025). ChatGPT adopted by ~10% of world adult population by Jul 2025; gender gap narrowing; higher growth in lower-income countries. Non-work messages grew 53% -> 70%+. 75% of conversations focus on practical guidance, information seeking, and writing. 49% of messages are Asking mode (advisor) showing decision-support value especially in knowledge-intensive jobs. Privacy-preserving automated classifier on de-identified messages. Companion to OpenAI compensation paper (#64) and GDPval (#65).

Yes, AI is affecting employment. Here's the data.

ADP Research

ADP Research जांचता है कि जनरेटिव AI विभिन्न आयु समूहों में रोज़गार को कैसे बदल रहा है, स्टैनफोर्ड डिजिटल इकोनॉमी लैब के निष्कर्षों के आधार पर। सॉफ़्टवेयर डेवलपमेंट और ग्राहक सहायता जैसे AI-प्रभावित क्षेत्रों में 22-25 वर्ष के श्रमिकों का रोज़गार 2022 के अंत से जुलाई 2025 के बीच लगभग 6% गिरा, जबकि उन्हीं भूमिकाओं में बड़े श्रमिकों को 6-13% रोज़गार वृद्धि मिली। आसानी से स्वचालित होने वाली भूमिकाओं में शुरुआती-करियर पेशेवर सबसे अधिक संवेदनशील हैं।

[제2025-22호] AI의 빠른 확산과 생산성 효과: 가계조사를 바탕으로 (Rapid Spread of AI and Its Productivity Effects: Evidence from a Household Survey)

Bank of Korea

63.5% of Korean workers use GenAI (51.8% for work), 3.8% work time reduction, 1.0% productivity gain, autonomous robot collaboration 11%->27%, equalizing effect for junior workers

Our Gen AI Transition: Industry Exposures & Adoption (Industry Data)

Jobs and Skills Australia

Jobs and Skills Australia के जनरेटिव AI क्षमता अध्ययन (14 अगस्त 2025) का सहयोगी डेटासेट, यह विश्लेषण ऑस्ट्रेलियाई अर्थव्यवस्था में उद्योग स्तर पर AI एक्सपोज़र और अपनाने के पैटर्न प्रस्तुत करता है। यह दिखाकर व्यवसाय-स्तरीय डेटा को पूरा करता है कि कौन से क्षेत्र सबसे अधिक AI एक्सपोज़र का सामना करते हैं और अपनाना कहां केंद्रित है, जो जनरेटिव AI की क्षमता का संपूर्ण श्रम-बाज़ार दृष्टिकोण समर्थन करता है।

Our Gen AI Transition: Exposures, Adaptation, Dynamism (Occupation Data)

Jobs and Skills Australia

Jobs and Skills Australia के जनरेटिव AI क्षमता अध्ययन (14 अगस्त 2025 को जारी) का हिस्सा, यह डेटासेट ANZSCO v1.3 इकाई-स्तरीय वर्गीकरण का उपयोग करके व्यवसाय के अनुसार AI एक्सपोज़र मैप करता है। यह मापता है कि नौकरियां AI के जवाब में कैसे बदल रही हैं, जिसमें कार्य अनुकूलन की सीमा, भूमिकाओं के बीच श्रमिक गतिशीलता शामिल है। निष्कर्ष दिखाते हैं कि संवर्धन आम तौर पर स्वचालन से अधिक है, और प्रवेश-स्तर पदों में अभी व्यापक विस्थापन का कोई प्रमाण नहीं है।

Our Gen AI Transition: Implications for Work and Skills

Jobs and Skills Australia

JSA Gen AI Capacity Study Overarching Report. First national whole-of-labour-market study by Australian government. 358 occupations analyzed using ANZSCO + two-axis (augmentability + automatability) framework. Key findings: 79% low risk, 21% meaningful exposure (routine clerical concentrated).

AI and Jobs: The Final Word (Until the Next One)

Economic Innovation Group

EIG के शोधकर्ता Sarah Eckhardt और Nathan Goldschlag जांचते हैं कि क्या AI वर्तमान में अमेरिकी श्रम बाज़ार में सार्थक नौकरी हानि का कारण बन रहा है, और इसके लिए पाँच अलग-अलग AI-एक्सपोज़र मापों का उपयोग करते हैं। उन्हें AI-प्रभावित श्रमिकों में कोई पर्याप्त रोज़गार हानि नहीं मिली; अत्यधिक प्रभावित श्रमिकों की बेरोज़गारी वास्तव में कम है। लेखक निष्कर्ष देते हैं कि AI अपनाना तेज़ हो रहा है (~9% व्यवसाय) पर वास्तविक आर्थिक प्रसार अभी भी मध्यम है और अधिकांश कंपनियाँ तटस्थ या सकारात्मक रोज़गार प्रभाव बताती हैं।

Advancing AI Capabilities and Evolving Labor Outcomes

arXiv

Empirical analysis linking AI capability advancement to labor market outcomes. Higher AI exposure associated with reduced employment, higher unemployment rates, and shorter work hours. Evidence consistent with 2025 AI-related hiring slowdowns and layoffs.

OECD Employment Outlook 2025

OECD

OECD रोज़गार आउटलुक 2025 सदस्य देशों की श्रम-बाज़ार स्थितियों की समीक्षा करता है और जांचता है कि AI को अपनाना नौकरियों, वेतन और कौशल की मांग को कैसे प्रभावित कर रहा है, तथा पाता है कि व्यवसायों में प्रभाव असमान है और अब तक शुद्ध रोज़गार प्रभाव सीमित है।

AI Index Report 2025

Stanford HAI

Stanford HAI AI Index 2025: countries ke beech AI adoption rates vs unemployment trends ka comprehensive cross-country analysis.

Augmenting or Automating Labor? The Dual Impact of AI on Jobs and Wages

arXiv

Studies 2015-2022 US data using instrumental variables. Finds automation AI negatively impacts new work, employment, and wages in low-skilled occupations, while augmentation AI fosters new work and raises wages for high-skilled occupations. Concludes AI may accelerate existing wage inequality.

The Future of Jobs Report 2025

World Economic Forum

WEF फ्यूचर ऑफ जॉब्स रिपोर्ट 2025 दुनिया भर के 1,000 से अधिक नियोक्ताओं का सर्वेक्षण करती है कि AI और स्वचालन 2030 तक भूमिकाओं को कैसे बदलेंगे, जिसमें 9.2 करोड़ नौकरियों के विस्थापन के साथ-साथ 17 करोड़ नई नौकरियों के सृजन और श्रमिकों के 39% मूल कौशल में बदलाव का अनुमान है।

Technological Disruption in the Labor Market

NBER

Deming/Ong/Summers: Historical labor disruption analysis, STEM jobs 50%+ surge since 2010, AI as potential GPT