17 predictions · 300 sources
How is AI reshaping
the labor market?
300+ 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 macro displacement — yet.
Important Reads This Week | February 27, 2026
Krugman · Feb 26
When Extraterrestrials Attacked the Stock Market
A viral AI scenario may have moved markets despite containing no new facts.
Thompson · Feb 25
Nobody Knows Anything
The knowledge vacuum around AI's effects allows speculative narratives to drive markets.
Citrini & Shah · Feb 22
The 2028 Global Intelligence Crisis
AI displacement triggers a self-reinforcing loop: job losses collapse spending, forcing deeper automation.
Citadel · Feb 24
The 2026 Global Intelligence Crisis
AI adoption follows S-curve constraints — productivity gains will boost real incomes, not cause contraction.
From exposure to job loss
AI adoption is accelerating and changing work, but the impact on jobs is less clear.
Based on 18 studies · Working papers, government data, institutional analysis · Hover for quotes and links
Read more sources →Most AI-and-jobs claims come from journalism or social media. Toggle to to see what the rigorous evidence actually says.
Filter by evidence quality
Job Displacement & Restructuring
Projected share of jobs eliminated, restructured, or significantly transformed by AI — most evidence points to task-level transition rather than wholesale replacement
Overall US Job Displacement by 2030
An estimated 2.8% of US jobs face net displacement from AI by 2030 — roles eliminated or fundamentally restructured.
Weighted average of all selected sources. Methodology
Total US Jobs Lost to AI as % of Labor Force
Roughly 4 million US workers are projected to lose their jobs to AI and automation.
Weighted average of all selected sources. Methodology
White-Collar Professional Displacement by 2030
6.9% of legal, accounting, and financial analyst roles face restructuring or elimination from LLMs and AI tools.
Weighted average of all selected sources. Methodology
Tech Sector Job Displacement by 2030
15.4% of tech sector jobs could be displaced by AI coding assistants and automated ops.
Weighted average of all selected sources. Methodology
Creative Industry Displacement by 2030
25.3% of creative roles in design, writing, and marketing could be displaced by generative AI tools.
Weighted average of all selected sources. Methodology
Education Sector Displacement by 2030
12.6% of education support roles face displacement as AI handles tutoring, grading, and content creation.
Weighted average of all selected sources. Methodology
Healthcare Administrative Displacement by 2030
20.6% of healthcare admin roles (coding, billing, prior auth) projected to be automated — one of the fastest-moving sectors.
Weighted average of all selected sources. Methodology
Customer Service Automation by 2028
41.2% of CS interactions projected to be fully handled by AI without human involvement.
Weighted average of all selected sources. Methodology
Wage Impact
How AI adoption is projected to affect compensation across worker segments
Median Wage Impact from AI by 2030
Real median wages projected to decline 1.6% as AI reshapes mid-skill work.
Weighted average of all selected sources. Methodology
AI Hub vs. Non-Hub Wage Divergence by 2030
AI hub cities (SF, Seattle, NYC) pay 40.5% more than non-hub metros for tech workers — and the gap is accelerating.
Weighted average of all selected sources. Methodology
Entry-Level Wage Impact from AI by 2030
Entry-level wages in knowledge work are projected to decline 8.6% as AI handles tasks traditionally done by juniors.
Weighted average of all selected sources. Methodology
High-Skill AI Wage Premium by 2030
Workers with AI/ML skills earn ~25.2% more than median — the gap is widening.
Weighted average of all selected sources. Methodology
Freelancer/Gig Worker Rate Impact by 2028
Freelancer rates in AI-exposed categories (writing, design, translation) have fallen 19.3% — a leading indicator of broader wage shifts.
Weighted average of all selected sources. Methodology
AI Adoption
How rapidly companies are deploying AI, how much of the workforce is exposed, and corporate signaling on earnings calls
AI Adoption Rate Across US Companies
19.3% of US companies with 50+ employees have deployed AI in production, up from under 4% in 2023.
Weighted average of all selected sources. Methodology
Generative AI Adoption
35.7% of U.S. working-age adults now use generative AI at work — overall adoption (55.9%) outpaces the PC and internet at comparable points post-launch.
Weighted average of all selected sources. Methodology
US Workforce AI Exposure
Current estimate: +42.7 % of jobs exposed.
Weighted average of all selected sources. Methodology
S&P 500 AI Workforce Mentions in Earnings Calls
42.4% of S&P 500 companies now mention AI + workforce on earnings calls, up from 8% pre-ChatGPT.
Weighted average of all selected sources. Methodology
The labor market effects above depend fundamentally on how much AI actually moves the productivity needle. Here's what leading economists currently think.
What economists expect from AI-driven productivity
Probability estimates for US productivity growth 2025–35, from Jason Furman's February 2026 exercise on X. 12 economists, 5 scenarios. Click any bar for source details.
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Based on 12 economists · X exercise by @jasonfurman · February 2026 · Click any bar for source
What the research actually shows
14 task & firm studies on productivity and 4 macro studies on economy-wide effects. The micro evidence leans heavily positive; the macro gains have not yet shown up in aggregate statistics. Click any row for details and source.
Task & Firm Productivity
RCTs, field experiments, and firm-level surveys measuring individual, team, and business productivity changes with AI tools
Macro Productivity
Economy-wide studies measuring aggregate productivity gains — TFP, labor productivity, and time savings
Key gap: Micro studies show 14–56% individual productivity gains, but macro data shows ~0–1.4% aggregate effect so far. The gap likely reflects adoption frictions, bottleneck tasks, and the J-curve dynamic of technology investment.
18 studies · Based on synthesis by Alex Imas (behavioral economist) · Studies range from peer-reviewed (Science, QJE) to working papers · Click any row for source
Live research feed
Discover Papers
Search 11 academic sources — Scopus, OpenAlex, Semantic Scholar, arXiv, NBER, Brookings, IMF, IZA, CORE, SEC EDGAR, and job market data — for recent AI + labor market research. Papers are classified by evidence tier, linked to predictions, and flagged when authored by tracked researchers.