20 predictions · 660 sources·Updated Aug 10, 2026
How is AI reshaping
the labor market?
~660 sources, one pattern. AI adoption is accelerating, productivity is climbing, entry-level and freelance work is compressing, and jobs are changing faster than they're disappearing.
No measurable job displacement,
Important Reads This Week | August 10, 2026 | See all →
Kartik B. Athreya (NY Fed) · Aug 5
AI's Impact on Labor and Hiring
The NY Fed's research director opens a new commentary series by reading his own bank's AI work as one argument: the labor-market story so far is changing skill requirements, not disappearing jobs. Second District adoption is climbing fast — service firms from 25% using AI in 2024 to 40% in 2025, manufacturers 16% to 26%, with 44% and 33% expected within six months — while firms report very few AI-driven layoffs and overwhelmingly intend to retrain rather than fire. The caveat he does flag: firms anticipate deeper cuts to hiring plans ahead, especially for college-educated workers. Regional and self-reported, so not comparable to the national BTOS series, but it is the clearest statement yet of how a Fed research shop reads its own evidence.
Revelio Labs · Jul 28
Introducing the Revelio AI Labor Market Tracker
Simon, Zweig and Wilkie-Rogers launch a live monthly dashboard across five lenses — talent supply, labor demand, equilibrium, work content, matching — built on online professional profiles rather than payroll. The headline finding independently replicates Canaries on non-ADP data: early-career workers (22-25) in the most AI-exposed occupations are down 13% relative to the least exposed since pre-ChatGPT, versus about 4% for all ages. Demand for the most-exposed roles is down 42%. The firm-side picture cuts the other way: AI-adopting firms grow headcount 27% more than non-adopters (though they were already growing faster pre-adoption), gains concentrate in senior roles (+31% vs +6% junior), and more AI-exposed firms see fewer layoffs, not more. Deliberately descriptive rather than predictive: the authors state the evidence does not establish that AI caused the decline in hires per posting. Two series no one else publishes monthly — a within-occupation activity-mix dissimilarity index (+8.4pp yoy, most change inside occupations rather than between them) and matching efficiency at 5.05 postings per hire, +264% yoy.
OpenAI Economic Research · Jul 27
Work at the Frontier: How AI is Expanding What People Do at Work
Chin and Richmond classify 800,000+ work-related ChatGPT messages from US users to a single O*NET detailed work activity, then compare it with the sender's stated occupation. The result they call task crossover: 16.8% of all work messages — and 43.5% of occupation-specific ones — concern tasks historically associated with another job. Cross-occupation work is the majority of occupation-specific messages in five of eight groups (customer experience 77%, design 75%, HR 69%). Borrowing and lending are independent: designers draw 35.2% of their messages from other fields while design tasks are only 1.7% of everyone else's; engineering is the inverse. Descriptive, not an employment estimate — but it argues the task bundles themselves are moving, which is a problem for any exposure measure built on fixed job descriptions.
FRED (St. Louis Fed) · Jul 24
FRED Adds Data About the Adoption of Generative Artificial Intelligence
The Bick-Blandin-Deming Real-Time Population Survey — the field's cleanest quarterly measure of US worker GenAI adoption — is now official FRED data: 137 series covering usage rates (overall, work, nonwork), time savings, and adoption compared with the PC and internet, with industry and occupation breakdowns. Latest readings: 43.4% of employed adults used GenAI for work and 57.9% of working-age adults used it anywhere in Q1 2026; GenAI-assisted work hours reached 6.3% in Q2 2026, up from 4.1% in late 2024. FRED hosting makes the series every major adoption synthesis relies on citable and API-accessible alongside official government statistics.
Google / Google DeepMind · Jul 23
AI & Economy ATLAS v1.0: Mapping Gemini Usage in the Economy
Google's entry into the usage-data triad (alongside Anthropic's Economic Index and OpenAI's Jobs Transition Framework) — 15M de-identified Gemini interactions mapped to 800+ occupations, 4,000 O*NET tasks, 300 household activities, 150 countries, and 140 languages. Headline: diffusion is broad but shallow. Usage spans occupations covering 88% of US employment, yet the median occupation applies AI to only 21% of its tasks, and end-to-end automation is under 10% of non-routine cognitive use. Uniquely adds household lenses: 86% of conversational AI happens outside work, government/civic queries over-index ~20x, and household time savings may be worth $15-149B/yr — invisible to GDP. Reviewed by Coyle and Autor; Imas co-authored.
AI exposure does not equal job loss
AI adoption is accelerating and significantly changing work, but the impact on jobs is less clear.
40% of jobs are AI-exposed, but near-zero displacement measured so far. That gap is the story →
16 studies · Hover for quotes and links
Read more sources →How Will AI Affect Your Job?
Task visualizerAI doesn't replace whole jobs. It automates specific tasks. Explore which parts of 114 occupations covering ~64% of US employment are exposed and which remain human-dependent.
Look Up Your Occupation's AI Scorecard
ScorecardAn instant read on one job: what AI is already doing in it, what stays human, and three things worth doing about it. No signup, no email.
20 Predictions for How AI Will Impact Jobs
PredictionsDisplacement, wages, and adoption: each with trend data, source quality ratings, and a weighted estimate from 660+ sources.
What if AI Creates More Jobs Than It Displaces
Demand elasticityVery possible based on historic data. Every general-purpose technology eventually created more jobs than it displaced, and AI may be no different.
Important Concepts