KI & Arbeitspolitik-Zeitleiste

Anthropic Economic Index report: Cadences

Anthropic

Anthropic Economic Index June 2026 report "Cadences" analyzing how AI usage mirrors human rhythms — workweeks, daily schedules, key dates. Based on privacy-preserving telemetry (Apr 10–Jun 10, 2026) plus a linked survey of ~9,700 respondents. Key findings: personal use rises from ~35% weekday to ~50% weekend; tax queries spiked 8x on April 14; 93% of conversations produce artifacts; higher-wage occupations (marketing managers, programmers) use 2.5x more tokens and 1.34x output per turn; over 35% expect AI to handle most tasks within 12 months yet workers delegating most are the most optimistic (86% productivity gains, only 10% fear job loss); early-career workers carry the most concern (1/3 see junior job-loss probability >60%); computer/math roles 30% of respondents vs 4% of US employment; physical occupations underrepresented. Underlying data: BLS OEWS (May 2025), World Bank WDI, UN WPP.

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

European Central Bank

ECB SAFE survey round 37 (Oct-Dec 2025, 5,000+ euro area firms): 70%+ of firms use AI but only 7% intensively. Intensive users are smaller, younger, ICT/professional-services firms driven by growth not cost-cutting; 84% have completed AI investments and allocate ~20% of total investment to AI. Top barriers: skills shortage (40%) and finance.

Human Capital, AI, and Labor Commoditization

arXiv

Study of 49,610 Upwork workers and 2.26M contracts (2021Q1-2026Q1) finds generative AI reduced the importance of human capital signals (credentials, experience, reputation) by 7.8% in AI-exposed categories. Contract volume fell ~7%, demand shifted to lower-cost workers (3.2%->7.9% share), price weight rose (1.1%->1.8%), and the high vs low human-capital demand gap narrowed (10.3%->6.2%). Average AI exposure across 102 subcategories was 0.252; highest Legal Translation (0.80), lowest Photography (0.02).

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

Statistics Canada

StatCan survey: generative AI use among Canadian workers nearly doubled from 17% to 30% in under a year (Sep 2024–Jul 2025), concentrated in degree-holding analytical and knowledge-sector roles.

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

PwC

PwC analyzed 1B+ job ads across 27 countries. AI-exposed firms grew headcount 52% vs 36% and wages 24% vs 17% since 2018. AI skills wage premium hit 62% (up from 57%). Two-track market: professionalised jobs grow 2x faster with 42% faster wage growth than democratised jobs. AI-exposed entry-level roles up 35% since 2019 while others fell 10% ("seniorization"); junior AI roles 7x more likely to require senior skills. AI-skill jobs grow 8x faster (69% vs 9%). Tech/media/telecom led at 11%.

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

UK Government (DSIT & DWP)

The UK launched a £20m Early Careers Jobs Alliance (co-chaired by the Prospect union, with partners including Microsoft, Accenture, BAE Systems and JD Sports) alongside the TechFirst programme reaching 400,000 students, an £820m Youth Guarantee supporting almost 1 million young people via 350,000 placements and 360+ youth hubs, and a phased AI bootcamps rollout (North West summer 2026, nationwide 2027-2028). National target: 10 million UK workers AI-upskilled by 2030 (1.7m courses completed).

Climbing the employment ladder tough when bottom rung is broken

Federal Reserve Bank of Dallas

Dallas Fed economists find youth (under-25) employment in highly AI-exposed occupations fell ~13% since 2022. The decline comes not from layoffs but from a falling job-finding rate — young workers cannot get hired in the first place. Firms pull back on entry-level recruitment while competing aggressively for proven, experienced talent, because AI now handles much codified (textbook) knowledge while tacit (experience-based) knowledge stays scarce. Computer systems design wages rose 16.7% since fall 2022 vs 7.5% nationally, evidence of a widening experience premium.

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

PIIE analysis by Hufbauer & Zhang finds AI adoption is skill-biased: high-wage service sectors (information, finance, professional services) lead with 30%+ firm adoption while retail/hospitality/food services lag. Large firms (250+) tripled adoption from ~4% to ~12% (2023-2025); large-firm employment share rose 37.6% (2000) to 42.3% (2025). Modest positive correlation between compensation and AI adoption. Labor displacement effects deemed premature/inconclusive.

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.

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.

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 (Friedrich & Kagerl) reports that generative AI adoption among German establishments rose nearly fivefold from 5% (2023) to 24% (2025), based on the ~15,000-establishment IAB-Betriebspanel. Adoption is 48% at firms with 200+ employees vs 21% at firms under 10; leading sectors are information & communication (59%) and finance & insurance (50%), while construction, hospitality, transport and raw materials stay below 15%. 90% of adopters use off-the-shelf tools; only 16% train purchased models and 6% build their own. About half invested financially, 25%+ offer AI training, and 20% have workplace AI rules.

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 Global Workforce Survey (payroll data for 25M+ US workers + 600,000+ workers across 34 countries) finds 50% of workers use AI at least a few times weekly and 20% almost daily. Daily AI users report higher full engagement (30% vs 14% non-users; 19% baseline) and lower overload (11% vs 23%), yet are 4x more likely to feel less productive than capable — a productivity paradox the authors attribute to workers perceiving they personally did less. Young workers and men lead adoption; early-career workers aged 22-25 in AI-exposed fields (software development, customer support) face employment-growth concerns and are less optimistic about job security.

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.

The Rise – and Rise – of Knowledge Work

ADP Research

ADP Research analysis (Nela Richardson and Tim Decker, 2026-04-21) of 25-year US employment composition trends. Professional services share grew from 14.9% (Jan 2000) to peak 17.6% (Jan 2022), declining to 16.8% (Jan 2025). Administrative/support roles fell from 47.5% (Jan 2020) to 39.5% (Jan 2025). Management/scientific consulting expanded from 10.1% (Jan 2020) to 17.3% (Jan 2025). Computer programming roles showed strongest 25-year growth. Data: BLS QCEW + ADP employment data + UMich consumer sentiment + Census retail sales + DOL unemployment claims. Affected occupations: legal services, accounting, architecture, engineering, design, advertising, computer programming, scientific research, management consulting, technical services.

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).

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).

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

The Budget Lab at Yale

Yale Budget Lab March 2026 CPS analysis: US unemployment rose to 4.3% but AI exposure/automation/augmentation metrics show no relationship to employment changes. Immigration slowdown, not AI, is the primary driver of labor market weakening. Dissimilarity index flat since ChatGPT 2022; recent graduates (20-24) show no growing divergence from older workers (25-34).

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%.

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.

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 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

Stanford HAI's 2026 AI Index documents accelerating AI capability, investment and adoption, and highlights early labor-market signals including employment declines among younger workers in AI-exposed entry-level occupations.

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.

AI and the US Labour Market: Effects on Employment Growth

European Central Bank

ECB Economic Bulletin (Issue 4/2026) finds US occupations at high AI-substitution risk declined more than 4% from 2019-2025 while low-risk occupations grew 13%, a ~15pp employment wedge that widened fastest after ChatGPT's late-2022 launch. Low-risk share rose 23%->25% of employment, high-risk fell 35%->33%. No significant wage-growth effect detected. Difference-in-differences with sector fixed effects.

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.

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

Joint ILO-World Bank background study for WDR 2026 analyzing GenAI labor market exposure across 135 countries. Finds uneven impact: advanced economies face higher exposure in clerical/professional roles; developing economies risk faster disruption than productivity gains due to digital gaps. Women and youth disproportionately vulnerable.

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.

The AI Layoff Trap: Automation Arms Race

arXiv (Wharton)

Wharton-arXiv-Paper: Die KI-Entlassungsfalle — Unternehmen im Automatisierungswettlauf erzeugen ein Kollektivhandlungsproblem, das nach hinten losgehen könnte.

Economic Index March 2026: Learning Curves

Anthropic

Anthropic Economic Index März 2026: 49 % der Jobs nutzen KI für 25 %+ der Aufgaben. Lernkurven zeigen, dass Frühnutzer davonziehen.

How AI Is Transforming Work at Anthropic (Internal Data)

Anthropic

Interne Anthropic-Daten: Ingenieure nutzen KI für 59 % ihrer Arbeit. Enthüllt tatsächliche Nutzungsmuster im Vergleich zu externen Schätzungen.

Building Pro-Worker AI

Brookings (Acemoglu, Autor, Johnson)

Acemoglu, Autor, Johnson (Brookings): Drei führende Ökonomen argumentieren, der aktuelle KI-Entwicklungspfad schade den Arbeitnehmern.

AI Hiring Is Booming While Everything Else Stalls

Stanford HAI + Indeed

Stanford HAI + Indeed-Daten: KI-Einstellungen steigen rapide, während Nicht-KI-Einstellungen stagnieren — ein Zwei-Klassen-Arbeitsmarkt entsteht.

How AI Is Changing the Labor Market

Dallas Federal Reserve + HBR

HBR + Dallas Fed Synthese: KI hilft und schadet Arbeitnehmern gleichzeitig über verschiedene Kanäle — Produktivität vs. Verdrängung.

AI and the Entry-Level Job

Harvard Business Review + IBM

IBM verdreifacht die Einstellung von Berufseinsteigern, während Konkurrenten kürzen. HBR-Fallstudie zu einer konträren KI-Personalstrategie.

Gen AI Wont Make Your Employees Experts

Stanford + Harvard

Stanford-Harvard-Studie: KI kann Erfahrungslücken nicht überbrücken. Eine 8-monatige Feldstudie zeigt, dass KI bestehende Kompetenzunterschiede verstärkt.

AI and Young Workers: Employment Effects

Dallas Federal Reserve

Dallas-Fed-Daten zeigen, dass die Jugendbeschäftigung im Techsektor seit Anfang 2022 rückläufig ist — Monate vor dem ChatGPT-Start.

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

International Labour Organization

ILO Working Paper 166 examines generative AI's uneven labor-market effects across 135 countries. Advanced economies face higher automation exposure (30-32% of employment), but developing nations face a paradox: workers vulnerable to displacement already have internet connectivity, while those positioned to gain from AI-driven productivity often lack reliable digital infrastructure. The paper warns that "disruptive effects may materialize before benefits" in some developing economies, underscoring gaps between AI's technological potential and actual implementation capacity.

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.

New Data Show No AI Jobs Apocalypse — For Now

Brookings Institution

Brookings-Analyse über 33 Monate: Noch keine Massenarbeitslosigkeit durch KI, aber erste Warnsignale in bestimmten Sektoren.

AI Labor Displacement and the Limits of Worker Retraining

Brookings Institution

Brookings untersucht historische Umschulungsprogramme und stellt begrenzte Erfolgsquoten für verdrängte Arbeitnehmer fest.

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.

Generative AI and Jobs: Refined Global Index of Occupational Exposure

ILO

Verfeinerter ILO-Index über 138 Länder: Frauen tragen ein doppelt so hohes Automatisierungsrisiko aufgrund beruflicher Segregationsmuster.

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

Brookings Institution

Brookings-Metaanalyse argumentiert, dass die KI-Arbeitsmarktforschung noch in den Anfängen steckt — die meisten Behauptungen gehen über die Evidenz hinaus.

Karpathy AI Job Exposure Score for Every US Job

Andrej Karpathy / Fortune

Karpathy (ex-OpenAI) bewertet jeden US-Beruf nach KI-Exposition. Angestellte Fachkräfte zeigen die höchste Verwundbarkeit.

World Employment and Social Outlook: Trends 2026

ILO

ILO-Leitbericht: Globale Arbeitslosigkeit bei 186 Mio., KI-Paradoxon mit Produktivitätsgewinnen ohne Beschäftigungserholung. 408 Mio. ohne angemessene Arbeit.

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

Brookings Institution

Brookings identifiziert 6,1 Mio. US-Arbeitnehmer mit hoher KI-Exposition aber geringer Anpassungsfähigkeit — strukturelle Verwundbarkeitskartierung.

AI and Young-Adult Jobs: The Real Mystery

Economic Innovation Group

EIG-Studie hinterfragt die KI-Jugend-Jobs-Erzählung: Der Beschäftigungsrückgang hat nicht-KI-bezogene Ursachen, darunter Post-Pandemie-Korrekturen.

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

Anthropic Economic Research

Anthropic introduces "observed exposure" — a new metric measuring AI's actual deployment in real workflows. Computer Programmers top at 75% observed exposure; full Computer & Math category sits at 33% (vs 90% theoretical). 30% of workers have zero observed exposure. New hires aged 22-25 in high-exposure fields drop ~0.5pp.

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

This ILO study examines how generative AI intersects with occupational gender segregation, concluding that women are roughly twice as likely as men to be in highly exposed clerical roles, which could widen labor-market inequalities without targeted policy.

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

ILO

This ILO research brief presents a refined global index of occupational exposure to generative AI, finding that clerical and administrative jobs are most exposed and that women face higher exposure than men because of their concentration in such roles.

India Brief: Economic Index

Anthropic

Anthropic Indien-Brief: Weltweit zweitgrößte KI-Nutzerbasis, aber Platz 101 bei der Pro-Kopf-Adoption — die Kluft zwischen Umfang und Tiefe.

Tracking the Impact of AI on the Labor Market

Yale Budget Lab

The Yale Budget Lab tracks AI's labor-market impact using current population data and finds that occupational exposure has stayed broadly stable since the launch of ChatGPT, with no clear sign of large aggregate disruption to employment yet.

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 meldet 12.304 KI-bedingte Stellenstreichungen im Januar/Februar 2026, während die Einstellungspläne um 56 % gegenüber dem Vorjahr zurückgingen.

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-Feldstudie über 8 Monate: KI erhöht die Arbeitsintensität statt die Belastung zu reduzieren — das Produktivitätsparadoxon.

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.

Pay trends to watch in 2026

ADP Research

ADP Research January 2026 payroll panel: job-changers 6.4% YoY wage growth vs job-stayers 4.5% (1.9pp premium, smallest since 2020). New-hire median base pay jumped from $18 to $19/hour after 18-month plateau, driven by construction and financial services. Average weekly hours 1 hour below pre-pandemic, near 7-year low. ~45% of workers now part-time (<35 hrs/wk), +6pp vs 2019. Sector switcher premium: construction +6.6pp, mining +5.6pp, leisure/hospitality negative. Authored by Nela Richardson Ph.D. and Liv Wang Feb 17 2026.

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-Freelancer-Studie: Hochqualifizierte Freiberufler sind am stärksten von KI betroffen — entgegen der Annahme, Geringqualifizierte würden zuerst verdrängt.

Building Pro-Worker AI

The Hamilton Project (Brookings)

Acemoglu, Autor and Johnson argue that AI should be steered toward complementing workers rather than replacing them, identifying barriers such as misaligned incentives and a pro-automation bias, and proposing nine policy measures to make AI more pro-worker.

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.

Payrolls to Prompts: Firms Replacing Labor With AI

arXiv (Payrolls to Prompts)

arXiv-Studie: Unternehmen geben nur 3 Cent für KI pro Dollar aus, den sie bei Freelance-Budgets kürzen — die Substitution ist unvollständig.

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.

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-Analyse: CEOs entlassen Mitarbeiter aufgrund von KI-Potenzial, nicht nachgewiesener Leistung. Nur 1 von 50 KI-Investitionen ist transformativ.

Anthropic Economic Index: January 2026

Anthropic

Anthropic Economic Index: Der tatsächliche KI-Produktivitätsgewinn beträgt 1,0 %, nicht die berichteten 1,8 % — die meiste Nutzung ist Augmentation, nicht Automatisierung.

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

Economic Innovation Group

In this EIG working paper, Zanna Iscenko and Fabien Curto Millet (Google economics team) analyze whether AI is eroding entry-level employment. They find job postings declined more in AI-exposed occupations, but the inflection point began in 2022, months before ChatGPT's public release. The timing aligns better with the macroeconomic shift of rising interest rates than with the launch of large language models, challenging the dominant narrative that AI is the primary driver of weakening entry-level hiring.

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-Studie mit 10,5 Mio. LinkedIn-Profilen: KI-exponierte Berufe verschlechterten sich 8–10 Monate vor dem ChatGPT-Start.

The Future of Jobs Report 2026

World Economic Forum

The WEF Future of Jobs Report 2026 surveys employers worldwide on how AI and automation will reshape roles by 2030, projecting large-scale displacement alongside even larger job creation and a major shift in required skills.

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

Federal Reserve Bank of Dallas

Dallas Fed economists examine employment and wage trends across more than 200 occupations since ChatGPT's late-2022 release. They find AI is simultaneously reducing employment in the most exposed industries (computer systems design down roughly 5%) while pushing wages higher for experienced workers in those same fields. Entry-level workers face the steepest challenge because AI can replicate codified textbook knowledge but not the tacit knowledge built through years of experience, so the labor-market impact hinges on whether AI automates or augments tasks.

State of play of convergence 2026 — Job quality in the EU

Eurofound

This Eurofound policy brief assesses whether job quality across EU Member States is improving and whether workplace standards are converging or diverging. It analyzes key indicators on fairness, health and safety, work-life balance, skills for the digital transition, and the role of social dialogue and collective bargaining, alongside disparities in social-protection access and persistent gender gaps. The comparative cross-country evidence is intended to inform current policy debates, including development of the EU Quality Jobs Act.

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

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.

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.

AI Jobs Barometer 2025

PwC

PwC-Barometer: KI-exponierte Berufe zeigen 4-fache Produktivitätsgewinne und 56 % Lohnprämie gegenüber nicht-exponierten Berufen.

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

Das BLS bezieht erstmals KI-Auswirkungen in die offiziellen Beschäftigungsprognosen 2024–34 ein — ein methodischer Wendepunkt.

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)

McKinsey's QuantumBlack surveyed 1,993 participants across 105 nations (June-July 2025) on enterprise AI adoption. Some 88% of respondents report regular AI use in at least one business function, up from 78% a year earlier, though most enterprises remain in experimenting or piloting stages and only about a third have begun scaling. Sixty-two percent are at least experimenting with AI agents and 23% are scaling agentic systems, yet just 39% report enterprise-level EBIT impact. The highest-value performers redesign workflows and pursue growth and innovation, not efficiency alone.

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

This Budget Lab at Yale analysis evaluates whether AI is measurably reshaping the US labor market, using occupational and industry dissimilarity metrics alongside AI-exposure measures. The data show no substantial acceleration in the rate of change in labor-market composition since ChatGPT's introduction; dissimilarity and exposure metrics remain flat or follow prior trends. The authors conclude the picture reflects stability rather than major economy-wide disruption, while cautioning that better data is needed and committing to regular updates of the analysis.

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 examines how generative AI is reshaping employment across worker age groups, drawing on Stanford Digital Economy Lab findings. Employment for workers aged 22-25 fell about 6% between late 2022 and July 2025 in AI-exposed fields like software development and customer support, while older workers in the same roles saw employment gains of 6-13%. The analysis distinguishes AI tools that automate tasks from those that augment human work, concluding that early-career professionals in easily automatable roles face the greatest vulnerability.

Rapid Spread of AI and Productivity Effects: Based on 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: 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).

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

Jobs and Skills Australia

A companion dataset to Jobs and Skills Australia's Generative AI Capacity Study (14 August 2025), this analysis presents AI exposure and adoption patterns at the industry level across the Australian economy. It complements the occupation-level data by showing which sectors face the greatest AI exposure and where adoption is concentrated, supporting a whole-of-labour-market view of generative AI's potential, its impact to date, and what is needed to support Australia's digital and AI transition.

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

Jobs and Skills Australia

Part of Jobs and Skills Australia's Generative AI Capacity Study (released 14 August 2025), this dataset maps AI exposure by occupation using ANZSCO v1.3 unit-level classifications. It measures how jobs are changing in response to AI, including the extent of task adaptation, worker mobility between roles, and overall occupational dynamism. The findings show augmentation generally outweighs automation, with higher automation potential concentrated in routine roles and women-dominated occupations, while entry-level positions show no evidence of widespread displacement in Australia yet.

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

Economic Innovation Group

EIG researchers Sarah Eckhardt and Nathan Goldschlag examine whether AI is currently driving meaningful job losses across the US labor market, testing five different AI-exposure measures against unemployment, labor-force participation, occupational switching, and industry employment. They find no substantial employment losses among AI-exposed workers; highly exposed workers actually show lower unemployment than less-exposed peers. The authors conclude AI adoption is accelerating (~9% of businesses) but real economic diffusion remains modest, with most firms reporting neutral or positive employment effects.

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

The OECD Employment Outlook 2025 reviews labor-market conditions across member countries and examines how AI adoption is affecting jobs, wages and skill demand, finding uneven exposure across occupations and limited net employment effects so far.

AI Index Report 2025

Stanford HAI

Stanford HAI AI Index 2025: Umfassende länderübergreifende Analyse der KI-Adoptionsraten im Vergleich zu Arbeitslosigkeitstrends.

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.

Technological Disruption in the Labor Market

NBER

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