US Executive Order on Safe, Secure, and Trustworthy AI

Overview

Executive Order 14110↗🏛️ governmentExecutive Order 14110The Biden Administration's primary AI governance action before being partially revoked by Executive Order 14179 in January 2025; established the compute-threshold reporting framework and US AISI that remain influential in ongoing AI policy debates.President Biden's landmark Executive Order on AI (October 2023) established comprehensive federal policy for AI safety, security, and trustworthiness. It mandated safety evaluat...governancepolicyai-safetycompute+5Source ↗ on Safe, Secure, and Trustworthy Artificial Intelligence, signed by President Biden on October 30, 2023, represented the most comprehensive federal response to AI governance in US history. The 111-page directive established mandatory reporting requirements for frontier AI systems, created new oversight institutions, and addressed both immediate risks like algorithmic bias and long-term catastrophic risks from advanced AI capabilities. According to analysis by Stanford HAI, the order placed 150 specific requirements on over 50 federal entities—making it the most detailed AI policy directive ever issued by any government.

The timing was strategically significant: Biden signed the EO one day before the UK's AI Safety Summit at Bletchley Park (November 1-2, 2023), where the US joined 27 other countries in signing the Bletchley DeclarationPolicyBletchley DeclarationThe Bletchley Declaration represents a significant diplomatic achievement in establishing international consensus on AI safety cooperation among 28 countries including the US and China, though its ...Quality: 60/100 on AI safety. On the same day the EO was released, G7 leaders announced the Hiroshima AI Process Guiding Principles and a voluntary Code of Conduct for organizations developing advanced AI systems, aligning with the EO on red-teaming and content authentication.

The order was revoked by President Trump on January 20, 2025, within hours of his assuming office. The White House stated that EO 14110 "hindered AI innovation and imposed onerous and unnecessary government control over the development of AI." Stanford HAI tracking↗🔗 web★★★★☆Stanford HAIStanford HAI's implementation trackerThis tracker is particularly useful for following U.S. federal AI governance developments, including actions stemming from executive orders relevant to AI safety and compute governance.Stanford HAI's policy tracker monitors the implementation status of U.S. executive actions related to artificial intelligence, including executive orders and directives. It prov...governancepolicyai-safetydeployment+3Source ↗ showed that approximately 85% of the order's 150 distinct requirements had been completed before revocation.

Quick Assessment

For AI safety, the order represented both progress and limitations. It normalized government oversight of frontier AI development and created institutional capacity through the US AI Safety InstituteOrganizationUS AI Safety InstituteThe US AI Safety Institute (AISI), established November 2023 within NIST with $10M budget (FY2025 request $82.7M), conducted pre-deployment evaluations of frontier models through MOUs with OpenAI a...Quality: 91/100. Yet it primarily focused on transparency and voluntary cooperation rather than mandatory safety requirements or deployment restrictions.

Key Provisions and Mechanisms

Compute-Based Reporting Framework

The order's most innovative feature was its use of computational thresholds to trigger regulatory requirements. Companies training models using more than 10^26 floating-point operations (FLOP) were required to notify the Department of Commerce before and during training, share safety testing results, and provide detailed information about model capabilities, cybersecurity measures, and red-team testing outcomes.

Compute Threshold Comparison

A Biden Administration official stated that "the threshold was set such that current models wouldn't be captured but the next generation state-of-the-art models likely would." The Bureau of Industry and Security assessed↗🔗 webBureau of Industry and Security assessedLegal analysis from Mayer Brown on a 2024 BIS proposed rulemaking requiring AI developers and compute cluster operators to report advanced AI activities to the US government, relevant to AI governance and compute oversight discussions.This Mayer Brown legal analysis covers the Bureau of Industry and Security (BIS) proposed rule requiring companies to report the development of advanced AI models and large comp...governancepolicycomputecapabilities+3Source ↗ that no more than 15 companies exceeded the reporting thresholds for models and computing clusters.

No model ever triggered the threshold before revocation. Epoch AIOrganizationEpoch AIEpoch AI maintains comprehensive databases tracking 3,200+ ML models showing 4.4x annual compute growth and projects data exhaustion 2026-2032. Their empirical work directly informed EU AI Act's 10...Quality: 51/100 estimated GPT-5 pretraining at approximately 3 × 10^25 FLOP—still below the 10^26 threshold. This reflects a shift in frontier AI development: rather than scaling pre-training compute by orders of magnitude, labs increasingly focus on inference-time compute (reasoning models like OpenAIOrganizationOpenAIComprehensive organizational profile of OpenAI documenting evolution from 2015 non-profit to Public Benefit Corporation, with detailed analysis of governance crisis, 2024-2025 ownership restructuri...Quality: 62/100 o1) and algorithmic efficiency improvements. xAI's Colossus data center may have approached 10^26 FLOP for some training runs, but this remains unconfirmed.

The separate 10^23 FLOP threshold for biological sequence models reflected concerns that even smaller models could assist in bioweapon development—approximately 1,000 times less compute than the general threshold, acknowledging that biological design capabilities may emerge at lower scales than general intelligence capabilities.

The compute-based approach offered several advantages over capability-based regulations. FLOP measurements are objective and difficult to manipulate, unlike subjective assessments of AI capabilities. The thresholds also provided predictability for developers. However, the static nature of these numbers created risks of obsolescence as algorithmic efficiency improves—researchers estimated↗🔗 webTraining Compute ThresholdsPublished via heim.xyz and tagged with US AISI, this document is relevant to policymakers and researchers interested in how compute-based metrics are used to define regulatory scope for frontier AI models under frameworks like the Biden Executive Order on AI.This document examines the use of training compute thresholds as a governance mechanism for regulating advanced AI systems, analyzing how computational resource requirements can...computegovernancepolicyevaluation+5Source ↗ the thresholds could become outdated within 3-5 years. According to Fenwick analysis, algorithmic improvements of approximately 2-3x per year mean a model that would have required 10^26 FLOP in 2023 might achieve equivalent capabilities with 10^25 FLOP by 2026—rendering static thresholds increasingly ineffective.

Institutional Infrastructure Creation

The order established the US AI Safety Institute (AISI) within the National Institute of Standards and Technology, tasked with developing evaluation methodologies, conducting safety assessments, and coordinating with international partners. Unlike purely advisory bodies, AISI had operational responsibilities including direct testing of frontier models and developing technical standards for the broader AI ecosystem.

AISI Timeline and Development

AISI's creation paralleled the UK's AI Safety Institute, with the two signing cooperation agreements and developing shared evaluation frameworks. The November 2024 joint evaluation of Claude 3.5 Sonnet↗🏛️ government★★★★☆UK AI Safety InstituteNovember 2024 joint evaluation of Claude 3.5 SonnetThis is a landmark example of formal government pre-deployment AI evaluation, relevant to AI governance discussions about how safety institutes can assess frontier models before public release and coordinate internationally.The UK and US AI Safety Institutes conducted a joint pre-deployment evaluation of Anthropic's upgraded Claude 3.5 Sonnet, assessing biological capabilities, cyber capabilities, ...evaluationred-teamingcapabilitiesgovernance+6Source ↗ tested biological capabilities, cyber capabilities, software/AI development, and safeguard efficacy—representing the first such government-led assessment of a frontier model.

However, AISI faced significant resource constraints. With only $1-10M in actual funding versus the $17.7M requested, and staffing well below the estimated 200+ personnel needed for full capacity, the institute struggled to match the technical sophistication of private AI laboratories.

Global AI Safety Institute Comparison

The US AISI's $10M budget contrasts sharply with the UK's £100M commitment. NIST Director Laurie Locascio warned in May 2024 that only $1M was actually available, stating it would be "very, very tough" to continue operations without additional funding.

Leadership Transition and Organizational Uncertainty

Elizabeth Kelly, the inaugural AISI director, resigned on February 6, 2025. In her departure announcement, she stated: "I am confident that AISI's future is bright and its mission remains vital to the future of AI innovation." NIST Director Laurie Locascio also departed at the start of 2025 to head the American National Standards Institute (ANSI). Reports emerged that the Trump administration planned to lay off up to 500 NIST staffers, which posed particular risk for AISI as a new organization where most employees remained on probation.

Cloud Compute Governance

The order introduced "Know Your Customer" (KYC) requirements for Infrastructure-as-a-Service (IaaS) providers, mandating that cloud computing companies verify the identity of foreign customers and monitor large training runs. The Bureau of Industry and Security proposed rule↗🔗 webDepartment of Commerce's proposed ruleLegal blog analysis of a U.S. regulatory proposal to require cloud providers to vet foreign AI compute customers, relevant to compute governance and efforts to limit unauthorized access to frontier AI training resources.The U.S. Department of Commerce proposed a rule requiring Infrastructure-as-a-Service (IaaS) providers to implement Know Your Customer (KYC) verification for foreign users acces...governancepolicycomputedeployment+2Source ↗ required US IaaS providers to implement Customer Identification Programs (CIP) including:

• Collection of customer name, address, payment source, email, telephone, and IP addresses
• Verification of whether beneficial owners are US persons
• Reporting to Commerce when foreign customers train large AI models with potential malicious applications
• Violations subject to civil and criminal penalties under the International Emergency Economic Powers Act

These requirements reflected recognition that compute infrastructure represents a chokepoint in AI development that the US can potentially control. By leveraging American companies' dominance in cloud computing, the order extended US regulatory reach to foreign AI developers who rely on American infrastructure—complementing export controls on AI chips.

flowchart TD
  subgraph EO14110["Executive Order 14110 Framework"]
      COMPUTE[Compute Thresholds<br/>10^26 FLOP general<br/>10^23 FLOP biological] --> REPORT[Mandatory Reporting<br/>to Commerce Dept]
      REPORT --> AISI[US AI Safety Institute<br/>Pre-deployment Testing]
      CLOUD[Cloud KYC Requirements<br/>IaaS Providers] --> FOREIGN[Foreign Customer<br/>Identification]
      FOREIGN --> MONITOR[Training Run<br/>Monitoring]
  end

  subgraph REVOCATION["Trump Administration (Jan 2025)"]
      REVOKE[EO 14110 Revoked] --> REVIEW[Agency Review<br/>of All Actions]
      REVIEW --> CAISI[AISI → CAISI<br/>Safety → Innovation Focus]
      REVIEW --> UNCERTAIN[Status of KYC Rules<br/>Uncertain]
  end

  EO14110 --> REVOCATION

  style COMPUTE fill:#e1f5fe
  style AISI fill:#e1f5fe
  style REVOKE fill:#ffcdd2
  style CAISI fill:#fff3e0

The practical implementation faced several challenges. Defining "large training runs" in real-time requires technical sophistication from cloud providers, who must distinguish AI training from other compute-intensive applications. Moreover, determined adversaries might circumvent these requirements by using non-US cloud providers or developing domestic computing capabilities.

Broader Policy Scope

While the compute thresholds and AISI attracted the most attention, the order addressed AI governance across eight policy areas. Several provisions addressed immediate, non-frontier risks:

The government modernization provisions had notably high completion rates. OMB issued guidance M-24-10 defining "rights-impacting" and "safety-impacting" AI categories—terminology that mirrored the EU AI Act's "high-risk" framework—and all 24 CFO Act agencies designated Chief AI Officers by the deadline. These institutional changes largely survived the revocation, as agencies retained their AI leadership structures at their own discretion.

Legal Basis and Enforcement Authority

The order relied on two key legal authorities for its mandatory provisions. The Defense Production Act↗🏛️ governmentExecutive Order 14110The Biden Administration's primary AI governance action before being partially revoked by Executive Order 14179 in January 2025; established the compute-threshold reporting framework and US AISI that remain influential in ongoing AI policy debates.President Biden's landmark Executive Order on AI (October 2023) established comprehensive federal policy for AI safety, security, and trustworthiness. It mandated safety evaluat...governancepolicyai-safetycompute+5Source ↗ (DPA) was invoked to compel reporting from companies developing dual-use foundation models above the compute thresholds—an expansive application of Cold War-era industrial mobilization law to commercial AI development. Some legal scholars questioned whether the DPA could legitimately be used for information-gathering rather than production mandates. The International Emergency Economic Powers Act (IEEPA) underpinned the KYC requirements for cloud providers, enabling civil and criminal penalties for violations.

However, the order included no new enforcement mechanisms for most provisions. The BIS proposed rule on developer reporting requirements—published September 2024 with a comment period closing October 11, 2024—was never finalized before revocation, meaning the compute-based reporting regime never achieved full regulatory force. This gap between the order's sweeping scope and its limited enforcement authority was a recurring criticism.

Safety Implications and Risk Assessment

Promising Aspects for AI Safety

The order's most significant safety contribution is establishing the principle that frontier AI development requires government oversight. By creating mandatory reporting requirements and institutional evaluation capacity, it moves beyond purely voluntary industry commitments toward structured accountability. The compute-based thresholds provide objective criteria that avoid subjective judgments about AI capabilities while capturing systems of genuine concern.

The institutional infrastructure created by the order builds long-term capacity for AI governance that could prove crucial as capabilities advance. AISI's technical expertise and evaluation methodologies may become essential tools for assessing increasingly powerful systems. The institute's international coordination role also creates foundations for global governance frameworks that could address catastrophic risks requiring multilateral cooperation.

The order's breadth across multiple risk categories—from algorithmic bias to national security threats—reflects sophisticated understanding of AI's diverse impact pathways. By addressing both immediate harms and long-term risks simultaneously, it avoids the false dichotomy between near-term and existential AI safety concerns. The integration of fairness, security, and catastrophic risk considerations within a single framework could prove influential for future governance approaches.

Concerning Limitations

Despite its comprehensive scope, the order lacks mechanisms to actually prevent the development or deployment of dangerous AI systems. The reporting requirements provide visibility but not control, and the order includes no authority to pause training runs or restrict model releases based on safety concerns. This represents a fundamental limitation for addressing catastrophic risks that might emerge from future AI systems.

The voluntary nature of many provisions weakens the order's potential effectiveness. While reporting requirements are mandatory, many safety-related provisions rely on industry cooperation rather than enforceable mandates. Companies that choose not to comply face unclear consequences, undermining the order's credibility as a regulatory framework. The absence of specified penalties or enforcement mechanisms reflects the limited authority available through executive action.

The order's durability remains highly uncertain given its status as executive action rather than legislation. Future administrations could modify or revoke its provisions entirely, creating regulatory uncertainty that might discourage long-term compliance investments. This political fragility represents a significant weakness for addressing long-term AI risks that require sustained governance approaches spanning multiple electoral cycles.

International Comparison of AI Compute Thresholds

The EU AI Act sets a 10x lower threshold (10^25 vs 10^26 FLOP) than the US EO did, meaning more models face regulatory obligations in Europe. The US threshold was intentionally set high—a Biden Administration official stated it was designed so "current models wouldn't be captured but the next generation state-of-the-art models likely would."

Revocation and Aftermath

Trump Administration Response

On January 20, 2025, President Trump revoked Executive Order 14110 within hours of assuming office. The White House fact sheet stated↗🔗 webThe Changing Landscape of AI: Federal Guidance for Employers Reverses Course Under New AdministrationRelevant to AI governance practitioners tracking U.S. federal AI policy evolution, particularly the shift from Biden-era AI executive orders to Trump administration reversals affecting employer obligations around AI use.This article examines how federal AI guidance affecting employers has shifted under a new administration, likely referring to the reversal of Biden-era AI executive orders and f...governancepolicydeploymentai-safety+1Source ↗ that the order "hindered AI innovation and imposed onerous and unnecessary government control over the development of AI."

Policy Paradigm Comparison

Three days later, on January 23, 2025, Trump signed Executive Order 14179↗🏛️ governmentExecutive Order 14179This executive order represents a major policy reversal in U.S. AI governance, directly affecting institutions and frameworks relevant to AI safety, including the AISI and compute-threshold reporting regimes established under the prior administration.Signed by President Trump in January 2025, this executive order revokes Biden-era AI safety mandates (including EO 14110) and reorients U.S. AI policy toward promoting innovatio...governancepolicyai-safetydeployment+3Source ↗, "Removing Barriers to American Leadership in Artificial Intelligence," which:

• Directed agencies to identify and revise/rescind all EO 14110 actions "inconsistent with enhancing America's leadership in AI"
• Mandated development of an "action plan" within 180 days to "sustain and enhance America's global AI dominance"
• Explicitly framed AI development as a matter of national competitiveness over safety
• Required OMB to revise memoranda M-24-10 and M-24-18 within 60 days

Vice President Vance subsequently stated that "pro-growth AI policies" should be prioritized over safety↗📖 reference★★★☆☆WikipediaUK AI Safety Institute WikipediaUseful background reference for understanding the UK's institutional AI safety efforts; relevant to discussions of AI governance, evaluation frameworks, and international policy coordination.Wikipedia article covering the UK AI Safety Institute (AISI), a government body established in 2023 to advance AI safety research and evaluation. It provides an overview of the ...ai-safetygovernancepolicyevaluation+4Source ↗, and the US refused to sign the February 2025 AI Action Summit communique in Paris.

What Survived the Revocation

The revocation did not automatically repeal everything implemented under EO 14110. Legal analysis↗🔗 webSkadden Legal Analysis: Biden AI Executive Order WithdrawalSkadden legal analysis relevant to understanding the regulatory implications of the Biden AI EO withdrawal, particularly for compute governance and the US AISI's future role.Skadden law firm provides legal analysis of the withdrawal of President Biden's broad AI executive order, examining the implications for AI governance, compute thresholds, and t...governancepolicycomputedeployment+3Source ↗ indicates:

The Commerce Department's Framework for AI Diffusion↗🔗 webCommerce Department's Framework for AI DiffusionThis legal alert from Wiley Law covers the immediate policy implications of Trump revoking Biden's central AI executive order, relevant for tracking the evolution of US federal AI governance and regulatory landscape in 2025.On January 20, 2025, President Trump revoked Biden's landmark 2023 AI Executive Order (EO 14110) as part of a broader rescission of Biden-era actions. The article analyzes the i...governancepolicydeploymentai-safety+2Source ↗ and other final rules may require separate rulemaking processes to revoke, providing some continuity even as the overall framework shifts.

AISI to CAISI Transformation

In June 2025, the US AI Safety Institute was renamed to the Center for AI Standards and Innovation (CAISI) with a fundamentally different mission. According to Commerce Secretary Howard Lutnick: "For far too long, censorship and regulations have been used under the guise of national security. Innovators will no longer be limited by these standards. CAISI will evaluate and enhance US innovation of these rapidly developing commercial AI systems while ensuring they remain secure to our national security standards."

This represents a shift from:

• Safety evaluation → Innovation promotion
• Pre-deployment risk assessment → National security focus
• International safety coordination → Competitive advantage emphasis

The December 2025 NIST announcement of $10M in AI centers↗🔗 webNIST and MITRE Announce $20M Research Effort on AI CybersecurityCovers a U.S. government-funded initiative to strengthen AI cybersecurity research, relevant to those tracking federal AI safety policy and institutional efforts to address AI-specific security risks.NIST and MITRE announced a $20 million collaborative research initiative focused on AI cybersecurity, aiming to develop standards, tools, and frameworks to address AI-related se...governancepolicyai-safetyevaluation+3Source ↗ (with MITRE) and a planned $10M AI for Resilient Manufacturing Institute suggests resources are being redirected toward manufacturing and cybersecurity applications rather than frontier model safety evaluation.

Trump AI Action Plan (July 2025)

On July 23, 2025, the White House OSTP released "Winning the Race: America's AI Action Plan," outlining 90 federal policy positions across three pillars: accelerating innovation, building American AI infrastructure, and leading in international diplomacy and security. The plan was developed in response to EO 14179's mandate for a 180-day action plan and incorporated over 10,000 public comments.

The plan takes a deregulatory stance, directing OMB to identify and repeal regulations that hinder AI development. It emphasizes national security applications and competitive positioning against China rather than the safety-testing framework of EO 14110. CAISI's role under the plan focuses on cybersecurity, biosecurity, chemical weapons, and countering foreign adversarial influence—areas that align with national defense priorities rather than the broad consumer protection and civil rights mandate of EO 14110.

State Law Preemption Order (December 2025)

On December 11, 2025, President Trump signed a new executive order titled "Ensuring a National Policy Framework for Artificial Intelligence," which directly targets state-level AI regulation. This order represents a significant expansion of federal AI policy beyond simply revoking Biden-era rules.

The order explicitly targets the Colorado AI Act, claiming it "may even force AI models to produce false results in order to avoid a 'differential treatment or impact' on protected groups." At minimum, Commerce must identify state laws requiring AI models to alter "truthful outputs" or compel disclosures "that would violate the First Amendment."

Legal analysts note the executive order cannot itself preempt state law—only Congress or the courts can do so. Until legal challenges are resolved, state AI laws remain enforceable. The order functions as a "pressure-and-positioning instrument" to narrow the practical space for state AI regulation rather than an immediate legal override.

US AI Governance Timeline (2023-2025)

timeline
  title Evolution of US Federal AI Policy
  section Biden Era
      Oct 2023 : EO 14110 signed
               : 150+ requirements
               : Compute thresholds set
      Nov 2023 : AISI founded at NIST
      Feb 2024 : Elizabeth Kelly named director
               : AISIC consortium formed
      Aug 2024 : Anthropic/OpenAI testing agreements
      Nov 2024 : Joint US-UK model evaluation
               : International Safety Network launched
  section Trump Era
      Jan 2025 : EO 14110 revoked
               : EO 14179 signed
      Feb 2025 : Kelly resigns
               : NIST layoffs announced
               : Paris communique refused
      Jun 2025 : AISI renamed CAISI
               : Mission pivots to innovation
      Jul 2025 : AI Action Plan released
               : 90 policy positions
      Dec 2025 : State preemption EO
               : DOJ AI Litigation Task Force

Implementation Progress (Pre-Revocation)

Completed Actions (Oct 2023 - Jan 2025)

Stanford HAI's tracker↗🔗 web★★★★☆Stanford HAIStanford HAI's implementation trackerThis tracker is particularly useful for following U.S. federal AI governance developments, including actions stemming from executive orders relevant to AI safety and compute governance.Stanford HAI's policy tracker monitors the implementation status of U.S. executive actions related to artificial intelligence, including executive orders and directives. It prov...governancepolicyai-safetydeployment+3Source ↗ documented approximately 85% completion of the order's 150 distinct requirements before revocation:

Key Accomplishments

Despite its short duration, the order achieved several notable outcomes:

Model Evaluation Precedent: The joint US-UK evaluation of Claude 3.5 Sonnet↗🏛️ government★★★★★NISTPre-deployment evaluation of Claude 3.5 SonnetThis is one of the first publicly disclosed government-conducted pre-deployment AI safety evaluations, setting a precedent for how regulatory bodies may assess frontier models before release; relevant to governance, capability evaluation, and red-teaming methodology discussions.The U.S. and UK AI Safety Institutes jointly conducted pre-deployment safety evaluations of Anthropic's upgraded Claude 3.5 Sonnet, testing biological capabilities, cyber capabi...evaluationred-teaminggovernancepolicy+6Source ↗ and OpenAI o1↗🏛️ government★★★★★NISTPre-Deployment Evaluation of OpenAI's o1 ModelThis is a landmark government-led safety evaluation representing one of the first formal pre-deployment assessments of a frontier AI model by national safety institutes, relevant to discussions of AI governance frameworks and capability evaluations.The US and UK AI Safety Institutes conducted a joint pre-deployment evaluation of OpenAI's o1 model, assessing its capabilities and risks across three domains including potentia...evaluationcapabilitiesai-safetygovernance+5Source ↗ established government capacity for pre-deployment testing of frontier models—the first such government-led assessments anywhere. The o1 evaluation notably found the model "solved an additional three cryptography-related challenges that no other model completed."

International Network: In November 2024, the US launched the International Network of AI Safety Institutes↗🏛️ government★★★★★NISTInternational Network of AI Safety InstitutesThis government fact sheet documents a significant multilateral AI safety governance milestone; relevant for tracking international coordination efforts and the institutionalization of AI safety evaluation across major AI-developing nations.In November 2024, the U.S. Departments of Commerce and State launched the International Network of AI Safety Institutes, uniting ten countries and the EU to advance collaborativ...ai-safetygovernancepolicycoordination+4Source ↗, establishing formal cooperation with the UK, Canada, Japan, Singapore, and other allies on AI safety research.

Industry Cooperation: Voluntary agreements with Anthropic and OpenAI demonstrated that frontier AI companies would accept government access to pre-release models—a precedent that may persist even after revocation.

Expert and Public Reactions

The order received broadly positive reactions from AI governance researchers and Democratic lawmakers. Stanford HAI experts characterized it as "a good start" but cautioned it was "not enough" without congressional legislation. Representative Don Beyer called it a "comprehensive strategy for responsible innovation." Polling from the AI Policy Institute found 69% of voters supported the EO, including 64% of Republicans.

Critics focused on two concerns. Senator Ted Cruz described it as creating "barriers to innovation disguised as safety measures." Some legal scholars questioned whether the Defense Production Act could legitimately compel disclosures from AI companies, arguing the statute was designed for industrial production requirements rather than information-gathering mandates.

The revocation generated a different debate. Legal analysts from firms including Skadden and Wiley noted that rescinding the order created significant regulatory uncertainty, since many agency actions taken under EO 14110 were already in effect and their post-revocation legal status was unclear.

Key Uncertainties and Future Outlook

The Broader 2024-2025 Regulatory Landscape

The EO 14110 revocation occurred within a rapidly evolving AI policy environment:

This landscape reveals a core tension: while federal AI governance has fragmented following the EO revocation, state-level activity has accelerated dramatically—a 110% increase in bills proposed and 162% increase in bills passed year-over-year. The December 2025 state preemption order represents an attempt to address this fragmentation by federal assertion rather than federal legislation. According to the Stanford HAI 2025 AI Index, despite receiving over 10,000 public comments on the AI Action Plan, Congress has not passed major AI legislation since the initial AI in Government Act of 2020.

What Happens Next?

With EO 14110 revoked and AISI transformed into CAISI, several key questions remain:

Lessons for AI Governance

The EO 14110 experience offers several lessons for future AI governance efforts:

Executive action fragility: The complete revocation within 15 months demonstrates that executive orders cannot provide durable AI governance. Of the approximately 150 requirements in EO 14110, roughly 85% were completed before revocation—yet all this implementation effort could be unwound by a single signature. Any sustainable framework requires congressional legislation or deeply embedded institutional practices that survive administration changes. For comparison, the EU AI Act took 3 years to negotiate but cannot be revoked by a single executive; modification requires parliamentary supermajorities.

Compute thresholds have a shelf life: The 10^26 FLOP threshold, designed to capture "next-generation" models, was never actually triggered before revocation. Researchers estimate↗🔗 webFenwick: Interesting Developments for Regulatory Thresholds of AI ComputeA law firm analysis relevant to AI governance practitioners tracking how compute-based regulatory thresholds are being developed; useful for understanding the legal landscape around frontier AI model oversight.A legal analysis from Fenwick examining evolving regulatory frameworks that use computational thresholds (e.g., FLOP counts) to define which AI systems trigger oversight require...governancepolicycomputeregulation+4Source ↗ such thresholds become outdated within 3-5 years as algorithmic efficiency improves.

Voluntary cooperation is necessary but insufficient: The Anthropic and OpenAI agreements demonstrated frontier labs will cooperate with government oversight—but this cooperation was voluntary and contingent on political conditions that no longer exist.

International coordination requires US participation: The International Network of AI Safety Institutes↗🏛️ government★★★★★NISTInternational Network of AI Safety InstitutesThis government fact sheet documents a significant multilateral AI safety governance milestone; relevant for tracking international coordination efforts and the institutionalization of AI safety evaluation across major AI-developing nations.In November 2024, the U.S. Departments of Commerce and State launched the International Network of AI Safety Institutes, uniting ten countries and the EU to advance collaborativ...ai-safetygovernancepolicycoordination+4Source ↗ launched just months before the US pivot away from safety-focused governance. Without sustained US engagement, international safety coordination faces significant headwinds.

Sources

Primary Sources

• Executive Order 14110 (Federal Register)↗🏛️ governmentExecutive Order 14110The Biden Administration's primary AI governance action before being partially revoked by Executive Order 14179 in January 2025; established the compute-threshold reporting framework and US AISI that remain influential in ongoing AI policy debates.President Biden's landmark Executive Order on AI (October 2023) established comprehensive federal policy for AI safety, security, and trustworthiness. It mandated safety evaluat...governancepolicyai-safetycompute+5Source ↗ - Full text of Biden order
• Executive Order 14179 (Federal Register)↗🏛️ governmentExecutive Order 14179This executive order represents a major policy reversal in U.S. AI governance, directly affecting institutions and frameworks relevant to AI safety, including the AISI and compute-threshold reporting regimes established under the prior administration.Signed by President Trump in January 2025, this executive order revokes Biden-era AI safety mandates (including EO 14110) and reorients U.S. AI policy toward promoting innovatio...governancepolicyai-safetydeployment+3Source ↗ - Trump replacement order
• Executive Order on State Law Preemption (White House) - December 2025 state preemption order
• Commerce Secretary Statement on CAISI - AISI transformation announcement

Implementation Tracking

• Stanford HAI Executive Action Tracker↗🔗 web★★★★☆Stanford HAIStanford HAI's implementation trackerThis tracker is particularly useful for following U.S. federal AI governance developments, including actions stemming from executive orders relevant to AI safety and compute governance.Stanford HAI's policy tracker monitors the implementation status of U.S. executive actions related to artificial intelligence, including executive orders and directives. It prov...governancepolicyai-safetydeployment+3Source ↗ - Implementation progress monitoring
• Stanford HAI AI Index 2025 - Policy landscape analysis
• NIST AI Safety Institute↗🏛️ government★★★★★NISTNIST AI Safety InstituteThis NIST page documents the now-rescinded Biden-era EO 14110, a landmark U.S. federal AI safety policy that created NIST's AI Safety Institute; its rescission in January 2025 reflects ongoing policy volatility in U.S. AI governance.This NIST page covers the Biden Administration's Executive Order 14110 on Safe, Secure, and Trustworthy Artificial Intelligence, issued October 30, 2023. The EO directed NIST an...ai-safetygovernancepolicyevaluation+3Source ↗ - AISI resources and evaluations

Analysis

• Georgetown CSET Analysis↗🔗 web★★★★☆CSET GeorgetownGeorgetown CSET AnalysisCSET (Center for Security and Emerging Technology) at Georgetown provides policy-focused analysis; this piece is relevant for understanding US federal AI governance shifts, particularly regarding deregulation and its impact on AI safety oversight structures like the US AISI.Georgetown CSET analyzes the executive order focused on advancing American AI leadership by reducing regulatory barriers, examining implications for AI governance, safety standa...governancepolicyai-safetycompute+3Source ↗ - Policy analysis of the revocation
• Congress.gov CRS Report↗🏛️ government★★★★★US CongressCongress.gov CRS ReportThis CRS report is a key reference for U.S. federal AI policy; note that EO 14110 was revoked by the Trump Administration in January 2025, making this primarily a historical document for understanding the Biden-era AI governance framework.This Congressional Research Service report summarizes Biden's Executive Order 14110 on AI, issued October 30, 2023, covering eight major policy areas including AI safety, civil ...governancepolicyai-safetydeployment+4Source ↗ - Congressional Research Service analysis
• TechPolicy.Press Analysis - AISI to CAISI renaming implications
• Epoch AI Notes on GPT-5 Compute - Compute threshold analysis
• Gibson Dunn State Preemption Analysis - Legal analysis of December 2025 order
• Skadden: AI Broad Biden Order Withdrawn - Post-revocation legal analysis
• Wiley: Trump Revokes Biden AI EO - Regulatory uncertainty analysis