A Breakdown of the Great American AI Act

Published: July 16, 2026

The House is seeking feedback on a national framework meant govern and audit AI system development.

In early June 2026, Reps. Lori Trahan (D-MA) and Jay Obernolte (R-CA) released a bipartisan draft legislation of the Great American AI Act. The bill establishes a national policy AI framework, as called for by Executive Order (EO) 14365. The purpose of the law is to set standards that would “extend core protections to every American while giving developers, researchers, and businesses the clarity they need to invest and build responsibly,” according to an op-ed by Trahan and Obernolte.

The legislation’s authors are seeking feedback from stakeholders, educators, state leaders, AI experts, and the public prior to formally introducing the bill in Congress.

The 250+ page of the Draft Great American AI Act is filled with compliance standards, repercussions and other guidelines surrounding U.S. AI development. Below is a breakdown of selected sections within the bill that are likely to have direct or indirect implications for federal contractors.

Section	Title	Description
Center for AI Standards and Innovation
102	Center for AI Standards and Innovation (CAISI)	Formally establishes CAISI under Commerce to develop AI security guidelines, conduct evaluations and administer Independent Verification Organization (IVO) licensing. Authorizes $100M per year for CAISI from 2027 to 2029.
Transparency, Independent Verification, and Whistleblower Protections
111	Transparency in Frontier Artificial Intelligence	Requires large frontier developers (>$500M) to develop and comply with AI safety frameworks and model transparency reports.
112	IVO Audits and Assessments	Directs CAISI-licensed IVOs to verify frontier developer compliance.
113	Anti-Retaliation Protection for AI Whistleblowers	Extends whistleblower protections to employees and independent contractors reporting AI violations.
Federalization and Federal Resources
121	Federalization of State Laws Regulating AI Model Development	Preempts state and local law regarding the development of AI models. Does not preempt laws of general applicability, remedies, or AI use regulation.
123	Resources for AI Model Documentation	Directs NIST to establish a pilot program to document AI standardized models and data documentation template.
Free Speech
141	Preventing Censorship and Protecting Free Speech	Directs Commerce to submit a study with legislation recommendations on unlawful federal agency interactions with AI platforms
Labor Market Data and AI Workforce Research
242	Attracting High Qualified Experts in AI	Authorizes Labor to accelerate recruitment of up to 20 AI experts with competitive outside-of-standard hiring methods.
244	Modernizing Access to AI-Related Labor Market Data	Establishes a Labor pilot program for job-to-job flow statistics and assessment of researcher access to microdata.
245	Support for Evaluation of AI Automation	Directs NIST to launch a prize competition to develop benchmarks to measure AI in automation or augmenting of tasks in occupations.
246	Voluntary AI Adoption and Use Reporting	Creates a Labor program for AI developers and deployers to voluntarily share data on AI adoption in the workforce.
Worker Protections and Adjustment Assistance
253	Forecasting Prize Competition	Directs NSF to create a recurring prize competition for forecasts on AI labor-market questions.
Cybersecurity
301	Reauthorization of the Cybersecurity Act of 2015	Extends information-sharing authorities through 2035, includes AI-related threat indicators, and permits AI tools in threat-sharing activities.
311	Support for Designated Critical Open-Source Software Maintainers	Authorizes CISA to award grants to maintainers of critical open-source software for security work and requires large frontier AI developers to give those maintainers access to their models for cybersecurity purposes.
Testbeds and Interagency Coordination
401	AI Testbed Program	Establishes a joint Energy/NIST/NSF testbed program among labs, public and private sector entities to test, evaluate, and red-team AI systems.
402	Coordination, Reimbursement, and Savings Provisions	Requires Commerce to avoid duplication of DOE and private sector testbed activities and mandates national lab resources be provided to NSF and NIST on a reimbursable basis.
AI Research and Development
421	Public Data for AI Systems	Directs OSTP to prioritize the creation and improvement of curated federal datasets for public release to support AI training and evaluation.
422	Federal Grand Challenges in Artificial Intelligence	Establishes a prize competition under OSTP for AI R&D across priority areas such as chip design, AI interpretability, border security, cybersecurity, etc.
423	National AI Research Resource (NAIRR)	Formally establishes NAIRR under NSF to procure and provided resources for AI development made available to researchers, academia, government and small private sector entities.
Research Security
432	Certifications and Audits of Temporary Fellows	Requires non-federal employees performing AI-related work must sign a certification to not perform inherently governmental functions.

Contractor Implications

The draft contains the potential for new opportunities and money flows for contractors with mentions of new prize competitions and pilot programs. The legislation also provides ways to support and expand AI system development and R&D with provisions centered on dataset curation and testbed partnerships.

Moreover, elements of the draft aim to simplify the compliance and evaluation landscape for contractors developing AI models. However, the draft legislation also increases the stakes and repercussions when the risks of misuse in AI models are higher. This document is not the first AI policy initiative to attempt to strike a balance between fostering innovation and ensuring compliance. Contractors should take advantage of the request for feedback on the legislation. Recent trends in the federal AI rulemaking process have demonstrated a willingness to listen to industry concerns, often favoring regulatory approaches that reduce compliance obligations in federal AI governance (i.e. AI security executive order and GSA’s AI acquisition clause).

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The House is seeking feedback on a national framework meant govern and audit AI system development.