Sponsors (5)
The bill funds and standardizes data, forecasts, and tools to help workers, states, and researchers respond to AI‑driven labor changes, but it expands data collection and reporting, increases costs and federal hiring flexibilities, and creates privacy, compliance, and funding‑certainty risks that could burden small employers and raise reuse and enforcement tradeoffs.
Workers (especially displaced and at‑risk workers) get clearer, recurring AI-impact forecasts and tailored retraining guidance that inform career decisions and help target transition services.
State and local workforce agencies and boards receive actionable, standardized forecasts and technical reports to realign training programs, in‑demand lists, and funding decisions to reflect AI-related labor market changes.
Researchers, developers, and policymakers gain sustained research capacity — an AI Workforce Research Hub, standardized benchmarks, and regular BLS/Census data collection — improving measurement, reproducibility, and public analysis of AI adoption and impacts.
Workers and small businesses face privacy and reidentification risks because the bill enables collection and sharing of unit‑ or record‑level workforce and employer data even with safeguards.
Small and medium employers will incur new compliance, reporting, and disclosure costs (and may fear proprietary or competitive harm) from expanded WARN disclosures, voluntary reporting, and statutory definitions of covered AI activities.
Taxpayers assume several million dollars in new federal spending across multiple accounts (authorized amounts for forecasts, Hub, prizes, and studies) with no guaranteed long‑term benefits or sustained funding after sunsets.
Based on analysis of 7 sections of legislative text.
Creates federal data, benchmarks, prize competitions, and occupation-level forecasts to measure AI’s labor impacts and study adjustment assistance and grant-use reforms.
Official title: Better forecast and plan for the impact of artificial intelligence on the workforce of the United States, to provide data to improve training programs for in-demand industry sectors and occupations, and for other purposes.
Introduced December 3, 2025 by James E. Banks · Last progress December 3, 2025
Creates a coordinated federal program to measure, forecast, and respond to how artificial intelligence will change jobs and training needs. It directs the Departments of Labor, Commerce (via NIST), OSTP, BLS, and others to collect new data, run prize competitions and voluntary reporting, produce occupation-level forecasts with prediction intervals, identify priority occupations for deeper study, and study options for a Rapid AI Adjustment Assistance program and how workforce grants and apprenticeships could use these tools. The bill funds prize competitions and small implementation activities, requires public comment and workshops to design data collection and forecasting methods, and sets timelines for publishing occupation lists, annual forecasts, and reports on using forecasts in grant selection and worker assistance. It aims to inform training grantmaking, improve forecasting capacity, and build temporary federal technical hiring authority to implement the work.