Sponsors (2)
The bill establishes a short-term, bipartisan commission to deliver near-term economic guidance on AI that could help policymakers, workers, and small businesses, but it does so with limited transparency, potential exclusion of industry expertise, tight deadlines, and modest taxpayer cost.
Taxpayers and state governments get bipartisan, expert recommendations to guide federal and state AI economic policy and legislation.
Students, teachers, and unemployed workers could benefit from recommendations to expand AI education and reskilling programs.
Small and medium businesses and tech workers may gain guidance on using open-source AI models and accessing research partnerships to boost competitiveness.
The commission is exempt from FOIA and FACA and may meet non‑publicly, reducing transparency and limiting public and stakeholder oversight of its advice.
Barring appointees with personal or financial interests could exclude experienced industry experts, reducing the technical and market expertise informing recommendations.
Short statutory deadlines (45–60 days) may force rushed recruitment and deliberation, risking less robust or incomplete recommendations for policymakers.
Based on analysis of 4 sections of legislative text.
Creates a bipartisan congressional commission to develop consensus legislative recommendations on the economic impacts of AI, with membership rules, timelines, and ethics limits.
Introduced March 11, 2026 by Mark R. Warner · Last progress March 11, 2026
Creates a bipartisan congressional commission to study how artificial intelligence will change the economy and to develop consensus legislative recommendations. The Commission will include ten congressional appointees (a mix of Members and outside experts), four nonvoting federal ex officio members from Education, Labor, Commerce, and Treasury, rules for meetings and quorums, conflict‑of‑interest limits, and short deadlines for appointment and first meeting. The Commission must organize panels as needed, operate under specified procedural and ethics rules, and produce recommendations addressing workforce, education, taxation, and other economic effects from AI adoption.