Extends the Chief Data Officer Council's authority to improve federal data governance. Enables agencies to securely adopt AI by appointing Chief AI Officers and mandating reports on data governance best practices, AI use cases, and synthetic data security.
Analysis summaries, actor details, and coverage mappings were LLM-classified and may contain errors.
This is a binding federal statute enacted by the United States Congress with mandatory obligations on federal agencies, enforceable through congressional oversight and administrative mechanisms.
The document has minimal coverage of AI risk domains, with limited focus on privacy and security (2.1, 2.2), governance structures (6.5), and system safety (7.3, 7.4). The document primarily addresses data governance processes and institutional structures rather than specific AI risks and harms. Coverage is concentrated in governance mechanisms and data quality, with brief mentions of privacy risks and transparency.
This document governs AI and data practices across all federal government agencies, which primarily operate in the Public Administration sector. The governance framework applies to federal agencies' internal operations and their use of AI systems across various government functions, but does not extend to private sector entities or specific economic sectors outside of government.
The document addresses multiple AI lifecycle stages with primary focus on Plan and Design, Build and Use Model, and Operate and Monitor stages. It emphasizes data governance throughout the AI lifecycle from acquisition to disposal, with particular attention to training data quality, testing procedures, and operational monitoring of AI systems.
The document explicitly mentions artificial intelligence and AI systems throughout, with detailed definitions provided. It does not specifically mention frontier AI, general purpose AI, task-specific AI, foundation models, generative AI, predictive AI, or compute thresholds. It does address synthetic data extensively and briefly mentions data sharing considerations but does not explicitly discuss open-weight or open-source models.
United States Congress (Senate and House of Representatives)
The document is a bill enacted by the United States Congress, as indicated by the standard legislative enactment clause and the legislative process described.
Director of the Office of Management and Budget, Committee on Homeland Security and Governmental Affairs of the Senate, Committee on Oversight and Accountability of the House of Representatives, Comptroller General
The Director of OMB has authority to issue guidance to agencies based on Council reports. Congressional committees receive mandatory reports for oversight purposes. The Comptroller General conducts biennial evaluations of the Council's effectiveness.
Chief Data Officer Council, Comptroller General, Congressional Committees (Committee on Homeland Security and Governmental Affairs of the Senate, Committee on Oversight and Accountability of the House of Representatives)
The Chief Data Officer Council is responsible for biennial reporting on its work and recommendations. The Comptroller General conducts evaluations every 2 years on whether the Council improved use of evidence and program evaluation. Congressional committees receive reports for oversight monitoring.
Federal agencies, Chief Data Officer Council, Chief Data Officers, Chief Artificial Intelligence Officers, Director of the Office of Management and Budget, Administrator of the Office of Electronic Government
The Act targets federal agencies and their leadership positions responsible for data governance and AI adoption, requiring them to establish governance structures, submit reports, and implement best practices for AI and data management.
6 subdomains (1 Good, 5 Minimal)