The PILLAR Act reauthorizes the CISA State and local cybersecurity grant program through fiscal year 2035, expanding its scope to cover operational technology systems and systems using artificial intelligence. It requires grant recipients to adopt multi-factor authentication and other cybersecurity best practices, with higher federal funding rates (up to 75% for multi-entity groups) if these measures are implemented by October 2027. The bill also mandates outreach to rural and small local governments to ensure equitable access to cybersecurity resources and includes a requirement for GAO reviews of artificial intelligence adoption across funded programs.
HR 5764, the "AI for Main Street Act," amends the Small Business Act to require the Small Business Administration (SBA) to provide guidance and training to small business concerns on using artificial intelligence. It directly affects small businesses by adding new SBA responsibilities to help them evaluate AI for operations, including best practices, cybersecurity, data protection, regulatory compliance, and customer trust. Key provisions mandate the SBA to offer information, training, and outreach on incorporating AI into business processes, such as planning for unexpected circumstances. The bill does not authorize new funding for these activities. It defines "artificial intelligence" using the existing term from the National AI Initiative Act.
The Algorithmic Accountability Act of 2025 requires companies that deploy complex AI systems making significant decisions (such as those affecting education, employment, healthcare, or financial services) to conduct impact assessments and submit annual reports to the Federal Trade Commission. It applies to companies with over $50 million in annual revenue or those handling information about more than 1 million consumers. Companies must assess potential negative impacts on consumers, including bias, privacy risks, and fairness concerns, and document their findings. The FTC will maintain a public repository of anonymized information from these reports to inform consumers and researchers about how AI systems are being used.
HR 4142, the "No Adversarial AI Act," prohibits U.S. federal agencies from acquiring or using artificial intelligence (AI) developed by "foreign adversary entities" as defined by the bill. Within 90 days of enactment, agencies must review and remove such AI from their systems, barring exceptions for scientific research, testing, counterterrorism, or mission-critical functions. The bill requires the Federal Acquisition Security Council to create and regularly update a public list of covered AI within 180 days, with removals possible if entities provide certification. This law directly affects federal agencies managing AI systems and aims to mitigate security risks from foreign-sourced AI technology.
HR 7294, the "AI for Secure Networks Act," requires the Secretary of Commerce to conduct a study on how artificial intelligence (AI) technology impacts telecommunications network security. The study must examine AI's potential to improve security through real-time threat detection, network resiliency, and energy efficiency, as well as its use with Open RAN and virtualized security technologies, while also assessing associated risks. The Secretary must consult with the Federal Communications Commission and industry stakeholders and submit a report with findings and potential recommendations to Congress within one year of the bill's enactment. This bill does not create new regulations or directly affect businesses or consumers; it is a procedural step to gather information about AI's role in securing telecom networks.
HRES 694 is a non-binding House resolution calling on the Centers for Medicare & Medicaid Services (CMS) to halt a pilot program using artificial intelligence to decide Medicare coverage for medical services. It directly affects seniors who rely on Medicare, as the resolution argues AI-driven coverage decisions could jeopardize their access to critical healthcare. The resolution expresses the House's "sense" that CMS should not proceed with this AI evaluation method, referencing CMS's June 2025 announcement of the pilot. As a resolution, it does not create new law but urges CMS to pause the program.
The AI for ALL Act establishes a federal commission within the Office of Science and Technology Policy to improve public understanding of artificial intelligence. The commission, composed of government officials and experts from education, industry, and research, must develop a national strategy for AI literacy within one year and update it every two years. It will create and distribute free, multilingual educational materials - via a public website and national campaigns - to help Americans learn about AI's basics, evolution, and safe use. These materials aim to enhance public knowledge without imposing new regulations or favoring specific AI technologies.
HR 6402 establishes a federal grant program administered by the National Academy of Sciences to fund research on developing "safe AI models" and mitigating AI risks. The program requires the Director to create public guiding principles for AI safety through stakeholder input, then submit a detailed proposal within one year outlining grant structure, research priorities, and evaluation methods. It directly affects researchers and institutions seeking federal funding for AI safety studies, not end-users or specific AI products. Key provisions include mandatory public input on ethical guidelines, a requirement to assess existing AI models' safety features, and a timeline for implementing the grant program. The bill focuses on research funding, not regulation of AI technology or deployment.
HR 7064, the AI in Health Care Efficiency and Study Act, requires the U.S. Department of Health and Human Services (HHS) to study how artificial intelligence can streamline administrative tasks in healthcare while protecting patient privacy. The study will examine AI applications for scheduling, claims processing, electronic health records, and cybersecurity threats like ransomware, involving healthcare providers, health plans, AI developers, and privacy experts. HHS must report findings and recommendations to Congress within 6 months of completing the study, focusing on reducing provider workload, improving data security, and ensuring compliance with health privacy laws. This bill does not create new regulations but directs a federal study to inform future policy on AI in healthcare administration.
HRES 701 is a House resolution requesting the President to provide documents about the Department of Government Efficiency's (DOGE) access to Social Security Administration data. It specifically seeks records related to a cloud system hosting the Social Security Numerical Identification System (NUMIDENT), including security plans, the purpose of the cloud copy (e.g., audits, benefits decisions, AI training), and access by named individuals. The resolution requires the President to submit these materials within 14 days of adoption. This is an inquiry, not a policy change, focused solely on transparency about government data access.
