Sponsors (5)
The bill centralizes federal data collection, forecasting, and targeted workforce training for AI—giving workers and policymakers better signals and tools to manage transitions—while creating privacy risks, reporting burdens, funding uncertainty, and potential administrative and accuracy trade-offs.
Workers, training providers, and state/local workforce planners will receive regular, occupation-level AI impact forecasts and standardized benchmarks so they can better target retraining, career transitions, and funding decisions.
Federal capacity to analyze AI workforce impacts will increase because agencies can hire temporary technology experts faster and gain targeted authorities and incentives to staff AI-related research and evaluation.
Clear statutory definitions and authorities make it easier for the Department of Labor and partner agencies to administer and fund AI-focused workforce training programs, clarifying eligibility for trainees and providers.
Individuals and workers face increased privacy and reidentification risks because the bill expands federal collection and secure researcher access to unit-level employment and AI-adoption data.
Employers — especially small businesses — will face new reporting and compliance burdens (expanded WARN disclosures, voluntary reporting expectations, and requirements to estimate percent of layoffs attributable to AI), raising costs and potential disputes.
Authorized funding is modest and many activities depend on future appropriations, so programs, hubs, and benchmark efforts may be under-resourced or unevenly implemented.
Based on analysis of 7 sections of legislative text.
Establishes federal data, benchmarking, prize competitions, and forecasting to measure AI’s effects on occupations and inform workforce training and adjustment policies.
Introduced December 3, 2025 by James E. Banks · Last progress December 3, 2025
Creates a coordinated federal program to measure how AI can automate or augment jobs, improve data collection and forecasting of AI-driven employment changes, and use those data to inform workforce training, grants, and potential adjustment assistance for displaced workers. It requires public input and a workshop, tasks NIST/Commerce with prize competitions to develop reproducible AI-to-task benchmarks, directs the Labor Department to publish lists of occupations for deeper analysis and to issue regular prediction-interval employment forecasts, and directs studies and reports on using these data for training program selection and a Rapid AI Adjustment Assistance design, with modest authorized funding for the activities.