[Google AI Overview at the query, signed out and incognito (operator defaults of 2026-10-01 and 2026-10-14), 2026-10-29. The paste is the Overview expanded (the 'AI Mode Conversation' view, with the source cards that follow the answer); the 'You said' line carries the query twice, run together, and is given once here. Inline links are Google redirect URLs, kept as pasted.] [QUERENT] Yale Budget Lab AI labor market [SYSTEM] The [AI Labor Market Tracker](https://www.google.com/goto?url=CAESewHrOzAVIdVACqsbX8syqbHRyGuC6LUKKtyZ4pvAADg1FMzpd1j7dzdiX8dECBNSC3i514DrMancwMIBIBIyOg05WO9Qz2ldyOBaZbiuTFgJ52tcEFhsEGvr1X_a1Cu8V9g1-vLY8uxua_vpTTcvd_nAzJbExYbLVA0AJw) by The Budget Lab at Yale finds no clear evidence of large-scale or economy-wide labor market disruption from artificial intelligence. [1] Key Findings * Minimal Economy-Wide Impact: Data updated through September 2026 shows that employment, unemployment rates, and wage trends for AI-exposed workers largely mirror historical patterns and pre-AI trajectories. [[1], [2]] * No Unusual Occupational Churn: Changes in the mix of occupations across industries (occupational churn) remain flat and show no acceleration or divergence since the late 2022 launch of ChatGPT. [[1], [2]] * Exposed vs. Unexposed Workers: Synthetic differences-in-differences comparisons between AI-exposed and unexposed workers reveal no strong, consistent statistical footprint of AI-driven displacement, though slight volatility in unemployment growth for high-exposure groups continues to be monitored. [[1], [2]] * Capital vs. Labor: Companies cutting jobs or restructuring are generally doing so for broader macro or capital-investment reasons rather than direct workforce replacement by AI agents. [1] Interactive Tracker Sections You can explore the live data via the [The Budget Lab](https://www.google.com/goto?url=CAESewHrOzAVIdVACqsbX8syqbHRyGuC6LUKKtyZ4pvAADg1FMzpd1j7dzdiX8dECBNSC3i514DrMancwMIBIBIyOg05WO9Qz2ldyOBaZbiuTFgJ52tcEFhsEGvr1X_a1Cu8V9g1-vLY8uxua_vpTTcvd_nAzJbExYbLVA0AJw), which breaks down trends into three primary areas: [1] * Occupational Churn: Tracks how fast job roles and industry composition are shifting over time. [1] * AI Metrics: Evaluates various index measurements of AI task exposure across standard occupational classifications. [[1], [2]] * Comparisons: Analyzes employment, wage, and unemployment trajectories of workers in high- versus low-AI exposure categories. [1] Would you like to know more about specific high-exposure occupations (such as tech or administrative roles) or how different AI exposure metrics compare? The Budget Lab