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Federal AI Compliance Landscape

high confidence · updated 2026-06-06

The web of 94 US government-wide AI requirements from laws, EOs, and OMB guidance as of July 2025, together with 10 oversight bodies — and the documented gap between requirements and implementation.

The US federal AI compliance landscape consists of 94 government-wide requirements (as of July 2025) drawn from five laws, six executive orders, and three OMB guidance documents, alongside 10 executive-branch oversight and advisory bodies. A 2025 GAO audit found that only 4 of 35 recommendations it had made to agencies roughly 18 months earlier had been implemented, a gap between stated requirements and agency compliance that the Government Accountability Office documented across multiple agencies (Source: GAO-25-107933: AI Federal Efforts Guided by Requirements and Advisory Groups).

Statutory foundation

Five enacted laws supply the statutory basis for federal AI governance:

LawYearKey AI Provisions
AI in Government Act of 20202020AI use case inventories; GSA AI Center of Excellence; OMB AI training program
National AI Initiative Act of 20202020Created NAIAI Office and NAIAC; national AI R&D coordination
Advancing American AI Act2022AI use cases pilots; AI management principles; use-case inventories
AI Training for the Acquisition Workforce Act2022Annual AI training for acquisition workforce
CHIPS Act of 20222022Semiconductor R&D funding with AI implications; CHIPS Incentives Program

Executive orders

Successive administrations have produced a layered set of executive orders, spanning the first Trump administration, the Biden administration, and the second Trump administration:

EODateKey Change
EO 13859Feb 2019 (Trump 1)American AI Initiative — first modern federal AI EO
EO 13960Dec 2020 (Trump 1)Trustworthy AI in Federal Government — common design/use principles
EO 14110Oct 2023 (Biden)Comprehensive governance — 100+ agency requirements; safety/transparency
EO 14148Jan 2025 (Trump 2)Rescinded EO 14110
EO 14179Jan 2025 (Trump 2)Removing barriers; directed M-24-10/18 revision → M-25-21/22
EO 14319Jul 2025 (Trump 2)"Unbiased AI" / ideological neutrality in federal LLM procurement
EO 14320Jul 2025 (Trump 2)Promote export of American AI technology stack

(Sources: Executive Order 13859 — Maintaining American Leadership in Artificial Intelligence, Executive Order 14110 — Safe, Secure, and Trustworthy AI, Executive Order 14179 — Removing Barriers to American Leadership in Artificial Intelligence, Executive Order 14319 — Preventing Woke AI in the Federal Government, Executive Order 14320 — Promoting the Export of the American AI Technology Stack)

OMB guidance

OMB issues binding guidance that operationalizes the executive orders:

MemoDateKey Requirement
M-21-06Nov 2020Guidance for AI regulation
M-24-10Mar 2024 (Biden)Comprehensive AI governance; risk management
M-24-18Sept 2024 (Biden)Responsible AI acquisition
M-25-21Apr 2025 (Trump)Replaced M-24-10; generative AI policies required; CAIO Council
M-25-22Apr 2025 (Trump)Replaced M-24-18; LLM procurement must comply with EO 14319 unbiased principles

(Sources: OMB Memorandum M-24-10, OMB Memorandum M-24-18, OMB M-25-21 — Accelerating Federal Use of AI through Innovation, Governance, and Public Trust, OMB M-25-22 — Driving Efficient Acquisition of Artificial Intelligence in Government)

Agency requirements

As of July 2025, all federal agencies are required to:

  1. Prepare, share, and publish annual AI use case inventories (ongoing).
  2. Appoint a Chief AI Officer (CAIO) at every agency.
  3. Publicly release an AI strategy, due September 30, 2025.
  4. Adhere to AI acquisition guidance per M-25-22 by September 30, 2025.
  5. Ensure contracts for LLMs comply with the EO 14319 unbiased-AI principles (ideological neutrality).
  6. Adopt generative AI policies, required under M-25-21.

Oversight bodies

GAO-25-107933 identifies 10 executive-branch oversight and advisory bodies:

BodyRole
OSTPPresidential S&T advisory; chairs NSTC
NSTCCoordinate federal S&T policymaking
NSTC Select Committee on AIAI R&D priority setting
NSTC Subcommittee on ML/AIOperations arm
Committee on S&T EnterpriseCross-cutting R&D coordination
NITRD AI R&D IWGCoordinate AI R&D across 32 agencies
GSA AI Center of ExcellenceAgency AI acquisition support and convening
NAIAI OfficeFederal AI activity point of contact
[[entities/naiacNAIAC]]External advisory body (academia/civil society/industry)
PCASTPresidential advisory council (re-established Jan 2025)

Implementation gap

GAO's 2023 report (GAO-24-105980) made 35 recommendations to 19 agencies to implement federal AI requirements. By July 2025 (GAO-25-107933), 4 had been implemented — at OPM (AI rotational programs), DOT (consistency plan to OMB), and two others — while 31 remained unimplemented across 16 agencies. OMB declined to respond to GAO's request for comment, which GAO noted given that OMB has 15 requirements of its own. GAO characterized the result as a gap in which requirements exist but enforcement is weak (Source: GAO-25-107933: AI Federal Efforts Guided by Requirements and Advisory Groups).

Policy reorientation across administrations

The 2025 policy changes — EO 14148 rescinding EO 14110, and M-25-21/22 replacing M-24-10/18 — shifted the stated emphasis of federal AI policy from the safety and risk-management framing of the Biden-era documents toward an innovation and acceleration framing under the second Trump administration. Many of the underlying statutory requirements survive the EO changes, while their interpretation and implementation priorities shift.

EO 14319's unbiased-AI principles for LLM procurement create a potential tension with AI safety research that involves studying model outputs with ideological content. The requirement that vendors disclose system prompts, rather than model weights, establishes a transparency obligation in government procurement that also functions as a negotiating point.

Federal and state interaction

EO 14365 (December 2025) targets state AI laws for federal preemption. State attorney general guidance documents from California, New Jersey, Massachusetts, and Oregon constitute a concurrent state-level enforcement layer, producing a fragmented compliance picture for companies operating across multiple states (Sources: State AG AI Guidances (CA, NJ, MA, OR), Techno-Federalism: How Regulatory Fragmentation Shapes the U.S.-China AI Race).

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