EveryAILaw.comEO 14319 — Preventing Woke AI in the Federal Government
Obligations Covered
Timeline
| Milestone | Date | Notes |
|---|---|---|
| Signed | Jul 23, 2025 | President signed EO 14319 |
| OMB M-26-04 issued | Dec 11, 2025 | OMB guidance implementing Section 4 |
| Procurement policy deadline | Mar 11, 2026 | Agencies must integrate requirements into procurement policies |
Related Regulations and Standards
Related instruments are selected from shared compliance obligations and jurisdiction coverage.
LLM Procurement Documentation Requirements #
Creates de facto compliance obligations for any AI vendor selling LLMs to the US federal government. Agencies must require vendor documentation including model cards, data cards, acceptable use policies, and risk disclosures. Agencies must reject non-compliant models. Not branded as AI regulation, but effectively mandates transparency for a significant market segment.
Requirements
| Requirement | Details |
|---|---|
| Model/data cards | Vendors must provide model, system, and/or data cards detailing capabilities, limitations, risks, and mitigations |
| Training data provenance | Vendors must disclose training data provenance information |
| Acceptable use policy | Vendors must provide acceptable use policy documentation |
| Inappropriate use cases | Vendors must disclose inappropriate use cases |
| End-user resources | Vendors must provide end-user resources and feedback mechanisms |
Penalties
| Violation | Fine |
|---|---|
| Non-compliance | Contract termination; vendors accountable for certain costs if terminated due to non-compliance |
Sources: EO 14319 Text OMB M-26-04
Training Data and Risk Governance for Federal AI #
Vendors must disclose training data provenance, limitations, and risk mitigations as a condition of federal procurement. While framed as ensuring "unbiased AI," the practical effect is a data governance disclosure requirement for the federal AI supply chain.
Requirements
| Requirement | Details |
|---|---|
| Data provenance | Training data sources and provenance must be documented and disclosed to procuring agency |
| Risk documentation | Vendors must document risks, limitations, and mitigations for LLM systems |
| Compliance verification | Agencies must have sufficient documentation to assess vendor compliance with Unbiased AI Principles |
Penalties
| Violation | Fine |
|---|---|
| Non-compliance | Contract termination; vendors accountable for certain costs |
Sources: EO 14319 Text OMB M-26-04
Unbiased AI Principles Compliance #
Establishes two Unbiased AI Principles — truth-seeking and ideological neutrality — that federal LLM procurements must comply with. Agencies must adopt procedures to enforce compliance and hold vendors accountable. Effectively creates a content-level compliance standard for the federal market.
Requirements
| Requirement | Details |
|---|---|
| Truth-seeking principle | LLMs must prioritize factual accuracy, historical accuracy, scientific inquiry, and acknowledge uncertainty |
| Ideological neutrality principle | LLMs must avoid unprompted value judgments and ideological biases |
| Compliance procedures | Agencies must adopt procedures within 90 days of OMB guidance to enforce principles |
| Contract terms | New contracts must include compliance terms; existing contracts updated where practicable |
Penalties
| Violation | Fine |
|---|---|
| Non-compliance | Contract termination with cost accountability for vendors |
Sources: EO 14319 Text OMB M-26-04
Cite this regulation
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Attribution: EveryAILaw, PAICE.work PBC. “EO 14319 — Preventing Woke AI in the Federal Government”, EveryAILaw.com, May 21, 2026. https://everyailaw.com/regulation/us-eo-14319/
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