The Federal AI Regulatory Landscape in 2026
Understanding federal AI policy requires distinguishing between three distinct layers of federal action: executive orders (which direct federal agencies but do not create private-sector legal obligations), agency guidance and rulemaking (which can have binding effect when issued through formal notice-and-comment rulemaking), and federal legislation (which Congress has so far failed to enact in comprehensive form).
As of 2026, businesses operating AI systems in the United States face no directly enforceable comprehensive federal AI law. The most consequential compliance obligations come from state legislatures — Colorado, Texas, California, Illinois, Connecticut, and more than 35 other states have introduced or enacted AI-specific legislation. For legal and compliance teams, this makes state-level AI law tracking the highest-priority risk management task.
That said, federal developments set the tone for enforcement climate, influence state regulatory drafting, and shape voluntary compliance expectations. Several federal agencies — particularly the FTC, EEOC, and HHS — are actively using existing statutory authority to pursue AI-related enforcement actions without waiting for new legislation. Understanding the federal landscape is essential context for any comprehensive AI governance program.
Key compliance takeaway: Executive orders bind federal agencies — not private companies. The legal obligations that require immediate compliance attention are at the state level. Use our Am I Affected? tool to identify which state AI laws apply to your organization.
Biden's Executive Order on AI — EO 14110 (October 2023)
On October 30, 2023, President Biden signed Executive Order 14110, "Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence" — the most comprehensive federal AI policy action in U.S. history to that point. The order ran to more than 100 pages and established obligations across more than a dozen federal departments and agencies.
What EO 14110 Established
The Biden AI executive order directed action across several major areas:
- Safety testing and transparency: Developers of the most powerful AI foundation models (above a defined compute threshold) were required to share safety test results and red-team findings with the federal government, pursuant to the Defense Production Act. This was the most novel legal authority invoked.
- NIST standards development: The National Institute of Standards and Technology was directed to develop AI safety standards, testing methodologies, and red-teaming guidance, building on the January 2023 AI Risk Management Framework (AI RMF 1.0).
- Agency AI governance: All federal agencies were required to designate a Chief AI Officer, publish AI use case inventories, conduct algorithmic impact assessments for consequential AI systems, and comply with OMB-issued guidance on federal AI use.
- Civil rights and consumer protection: The order directed the FTC, EEOC, CFPB, and DOJ to use existing enforcement authority to combat algorithmic discrimination, AI-enabled fraud, and deceptive AI practices.
- AI and critical infrastructure: Sector-specific risk assessments for AI use in critical infrastructure — including energy, financial services, and healthcare — were mandated across relevant agencies.
- Immigration and talent: The order included provisions to attract AI talent to the U.S., streamline visa processing for AI specialists, and expand STEM immigration pathways.
- Watermarking and provenance: Agencies were directed to develop standards for AI-generated content authentication and provenance, to combat deepfakes and AI-generated disinformation.
EO 14110 did not create direct private-sector legal obligations. However, it significantly elevated AI governance expectations across industries and triggered OMB issuance of M-24-10 (March 2024), which required federal agencies to implement AI governance policies affecting federal contractors and vendors.
Trump Administration AI Policy (2025–2026)
President Trump's return to office produced an immediate and comprehensive reversal of Biden-era AI policy. On January 20, 2025, President Trump revoked Biden's EO 14110 on his first day in office. Three days later, on January 23, 2025, he signed Executive Order 14179, "Removing Barriers to American Leadership in Artificial Intelligence," which articulated his administration's pro-innovation AI policy direction.
EO 14179: The Trump AI Order
The Trump AI executive order articulated a fundamentally different regulatory philosophy: AI governance should prioritize American competitiveness and innovation rather than precautionary safety regulation. Key provisions include:
- Revocation of EO 14110: Biden's entire AI executive order was nullified, along with the associated OMB memoranda (M-24-10 and M-24-18) governing federal agency AI use.
- New OMB AI policy direction: The OMB was directed to issue new guidance within 60 days governing federal agency AI procurement and use, with an emphasis on reducing compliance burdens and promoting adoption.
- AI Action Plan: The Assistant to the President for Science and Technology, the Special Advisor for AI and Crypto, and the National Security Advisor were directed to develop a comprehensive federal AI Action Plan within 180 days, focusing on maintaining U.S. leadership in AI.
- Safety testing eliminated: The Defense Production Act reporting requirement for large AI model developers — one of the most substantive private-sector obligations in EO 14110 — was eliminated.
- Export controls review: The order initiated a review of AI chip and model export controls, which the Biden administration had tightened significantly in the final months of 2024.
OMB AI Guidance Revisions (2025)
Following EO 14179, the Office of Management and Budget issued revised AI guidance for federal agencies in March 2025. The new OMB memorandum replaced M-24-10's risk-based framework with a lighter-touch approach focused on innovation acceleration. Federal agencies were directed to remove unnecessary barriers to AI procurement, streamline vendor qualification processes, and reduce the algorithmic impact assessment requirements imposed under prior guidance.
For federal contractors and AI vendors serving the government, this represented a significant reduction in compliance overhead. However, the elimination of federal AI governance requirements has also increased pressure on Congress to legislate, and has reinforced the importance of state-level AI laws as the primary regulatory backstop.
DOGE and AI in Federal Operations
The Department of Government Efficiency (DOGE), operating under Elon Musk's leadership in the early months of the Trump administration, began deploying AI systems to analyze federal agency data, spending records, and workforce information. This unprecedented use of AI in federal operations raised significant legal questions under the Privacy Act, the Federal Records Act, and agencies' own AI governance policies, and generated ongoing litigation as of mid-2025.
Key Federal Agencies Shaping AI Regulation
In the absence of comprehensive federal AI legislation, multiple agencies are using existing statutory authority to address AI risks in their respective sectors. The following agencies have the most significant AI-related enforcement and regulatory activity.
NIST AI Risk Management Framework
The NIST AI Risk Management Framework (AI RMF 1.0), published January 26, 2023, is the federal government's primary voluntary guidance for managing AI risks. Developed through an extensive multi-stakeholder process, the AI RMF is organized around four core functions:
- Govern: Establish organizational policies, accountability structures, and culture for AI risk management. Includes board-level AI governance, documentation practices, and workforce training.
- Map: Identify and contextualize AI risks. Understand the AI system's context, intended uses, affected populations, and potential harms before deployment.
- Measure: Analyze and assess AI risks using quantitative and qualitative methods, including bias testing, robustness evaluation, and performance benchmarking.
- Manage: Prioritize and address identified AI risks. Implement controls, incident response plans, and ongoing monitoring processes.
Although voluntary, the NIST AI RMF has become a de facto compliance standard. It is referenced in multiple state AI laws, used as a baseline in federal procurement requirements, and increasingly cited in FTC guidance on responsible AI deployment. Organizations demonstrating NIST AI RMF alignment are better positioned to defend against regulatory enforcement and litigation.
NIST also published AI RMF Playbook supplementary guidance and has released sector-specific profiles for financial services, healthcare, and defense applications. The NIST Trustworthy and Responsible AI Resource Center (airc.nist.gov) provides implementation resources.
FTC Enforcement on AI and Algorithmic Fairness
The Federal Trade Commission has been the most active federal enforcement authority on AI-related consumer protection issues, using its existing authority under Section 5 of the FTC Act (prohibiting unfair or deceptive acts or practices) and the Fair Credit Reporting Act.
Key FTC enforcement themes in AI include:
- Deceptive AI claims: Companies making false or unsubstantiated claims about their AI systems' capabilities, accuracy, or safety have faced FTC investigation and consent orders.
- AI-enabled impersonation: The FTC has pursued enforcement against companies using AI for robocalls, voice cloning for fraud, and deepfake-based deception.
- Algorithmic accountability: The FTC has invoked its authority to require algorithmic audits and fairness assessments as part of consent order remedies in cases involving discriminatory automated decision-making.
- Data practices for AI training: The FTC has scrutinized whether companies are obtaining meaningful consent before using consumer data to train AI models, and has required data deletion as a remedy.
The FTC's enforcement posture has fluctuated with administration changes — the Trump administration's FTC leadership has moderated some prior enforcement positions — but the basic legal tools available to the FTC have not changed, and AI-related enforcement risk remains significant for companies making AI-related consumer-facing claims. See our Algorithmic Bias and AI Transparency topic pages for related state-level requirements.
Federal Policy and State-Level AI Laws
The most consequential question for compliance professionals in 2026 is the interaction between federal AI policy and the growing body of state AI legislation. The answer, for now, is that state laws are doing the heavy lifting.
Because there is no comprehensive federal AI statute, there is no federal preemption of state AI laws. States retain broad authority to regulate AI within their borders, and they are exercising it vigorously. The result is an increasingly complex patchwork of obligations that varies by state, industry, and use case.
Several states have enacted or are advancing AI laws with real compliance obligations:
- Colorado SB 205 (effective June 30, 2026): Requires developers and deployers of "high-risk" AI systems to conduct algorithmic impact assessments, provide consumer notices, and disclose AI use in consequential decisions.
- Texas HB 1709: Comprehensive AI regulatory framework covering high-risk AI system disclosure, impact assessment, and bias testing obligations.
- California: Multiple AI bills addressing deepfakes, employment AI, automated decision-making, and AI-generated content disclosure, including requirements affecting the state's large employer base.
- Illinois AIAA: The Artificial Intelligence Video Interview Act requires employers to notify job applicants when AI is used to evaluate video interviews and to comply with deletion requests.
- New York City Local Law 144: In effect since July 2023, requires annual bias audits of automated employment decision tools and public reporting of results.
Browse the complete state-by-state AI law directory to track all active legislation. Use the Deadline Calendar to see upcoming compliance dates, the Penalty Tracker to understand enforcement risk by state, and our AI legislation trends page for interactive charts showing the dramatic growth in state AI bills since 2016.
Federal preemption remains a live policy debate. Tech industry groups have lobbied for federal legislation that would preempt state AI laws and establish a single national standard — a significant issue to monitor as Congress considers AI legislation in the 2025–2026 session.
Federal AI Legislation: What Congress Is Considering
Congress has introduced dozens of AI-related bills across multiple sessions but has not enacted comprehensive AI legislation. The following legislative proposals are the most significant ones being tracked in the 2025–2026 congressional session:
- The Algorithmic Accountability Act: Would require companies to conduct impact assessments of "automated decision systems" used for consequential decisions and report findings to the FTC. Multiple versions have been introduced in the House and Senate.
- The NO FAKES Act: Addresses AI-generated replicas of individuals' voice and likeness without consent — a priority issue following high-profile deepfake incidents involving public figures and recording artists.
- The AI Transparency in Advertising Act: Would require disclosure labels on AI-generated political advertising, with FEC enforcement authority.
- The DEFIANCE Act: Would establish a federal private right of action for victims of AI-generated non-consensual intimate images (NCII). Passed the Senate unanimously in July 2024 but did not advance through the House before the end of the 118th Congress.
- The Future of AI Innovation Act: A more innovation-focused proposal backed by Republican leadership in the Senate, focused on NIST AI safety standards and agency coordination rather than prescriptive requirements.
- Sector-specific AI bills: Multiple bills addressing AI in healthcare (AI in Health Care Act), financial services (AI Consumer Protection Act), and national security applications.
The central legislative debate is between approaches that would preempt state AI laws (favored by the tech industry and many Republicans) versus a federal "floor" that preserves state authority to go further (favored by consumer advocates and many Democrats). This debate is likely to remain unresolved through at least the 2025–2026 session.
For regular updates on federal legislative developments, subscribe to our free newsletter — we track all major federal AI policy developments alongside state-level changes.
Why State Laws Are the Compliance Priority Right Now
For legal counsel and compliance officers advising businesses that deploy AI, the practical implication of the federal policy vacuum is clear: state laws are where the compliance work is happening today.
The reasons are straightforward. Federal executive orders are not enforceable against private companies. Federal agency guidance, while influential, is often voluntary or applies only to federal contractors. Congress has not enacted comprehensive AI legislation. By contrast, state AI laws — including Colorado's SB 205 (effective June 30, 2026), New York City's Local Law 144, Illinois's AIAA, and a growing number of others — impose real legal obligations with real penalties for non-compliance.
Businesses deploying AI systems in employment, healthcare, insurance, financial services, or education need to track state-level requirements now. Key questions for any AI compliance program include:
- Does my state require disclosure when AI is used in hiring, lending, or insurance decisions? (See: AI Transparency)
- Does my state require bias audits of algorithmic decision-making tools? (See: Algorithmic Bias)
- What are the penalties for non-compliance in each state where I operate? (See: Penalty Tracker)
- What compliance deadlines are approaching in my operating states? (See: Deadline Calendar)
- Does the AI system I'm deploying qualify as "high-risk" under state definitions? (See: Am I Affected?)
The complete guide to AI laws by state provides a comprehensive overview of the current regulatory landscape. The Bill Comparator lets you compare how different state laws approach the same issue side-by-side.