OpenAI has proposed mandatory federal evaluations of the most capable AI models before public release while arguing that regulators should stop short of deciding whether those systems can be deployed, staking out a middle ground in the debate over how frontier AI should be governed.The company’s proposal came a day after the White House issued an executive order on advanced AI innovation and security, amid ongoing discussions in Washington of whether oversight of frontier AI systems should rely on voluntary commitments, mandatory evaluations, licensing requirements, or some combination of the three.At the center of OpenAI’s proposal is a distinction between government evaluation and government approval. The company proposed that the most capable AI models undergo pre-release assessments by the Center for AI Standards and Innovation (CAISI), the federal government’s AI evaluation and standards body, while stopping short of giving regulators authority to approve or block deployments.“Policymakers should require the most capable frontier models to undergo a CAISI evaluation before public release,” OpenAI wrote in its proposal, “Democratic Governance of Frontier AI: A blueprint for a federal framework.” But it added that “CAISI’s role should be to conduct evaluations and recommend mitigations—not to approve or block deployments.”It also proposed a broader federal framework that would require evaluations, audits, transparency reports, incident reporting, whistleblower protections, and stronger security controls around frontier AI systems.Shaping the governance debateSanchit Vir Gogia, chief analyst at Greyhound Research, said OpenAI’s proposal appears designed to influence the direction of an emerging federal governance framework rather than respond to one that is already settled.“The contest is no longer whether frontier AI is governed, but who governs it, on whose terms, and where final authority rests,” he said.OpenAI argued governments need greater visibility into frontier AI development and that voluntary commitments alone will not be sufficient as AI systems become more capable.“Democratic governments — not private companies acting alone — must ultimately determine the rules, safeguards, and accountability mechanisms,” it wrote. “Decisions about the pace of AI innovation should not be left to any one lab, company, or special interest group.”The company also said, “If artificial general intelligence is going to benefit all of humanity, the world needs more than voluntary commitments, individual company policies, and isolated regulatory interventions.” Instead, it argued, “It needs harmonized legal frameworks and durable institutions capable of adapting as technology advances.”A procurement gate for enterprise AIThe proposal also addresses government buyers. OpenAI said federal agencies should not run frontier AI systems that have not passed a recognized evaluation and should “prohibit procurement of products and services that rely on unevaluated frontier models” in sensitive settings.It would also sort the federal market into evaluated and unevaluated models: Any vendor building on a frontier model would have to show the system had cleared evaluation to keep selling to government.Gogia said compliance-heavy rules favor the largest developers, who help define the thresholds and audit templates that others inherit. “Governance of this shape can become a moat dressed as maturity,” he said.Beyond voluntary commitmentsOpenAI’s proposal goes beyond model evaluations, suggesting a broader governance framework for frontier AI developers.Among the measures it recommends are annual third-party audits, public transparency reports, critical safety incident reporting requirements, cybersecurity protections for unreleased model weights, and whistleblower safeguards.“Large frontier developers should annually retain an independent third party to audit compliance with frontier safety requirements,” OpenAI said in the document.The company is also calling for mandatory reporting of critical incidents involving deployed models, including dangerous model behavior and unauthorized access to sensitive model weights.Shreeya Deshpande, senior analyst at Everest Group, said the proposal attempts to balance stronger oversight with continued innovation.“This creates a credible middle path between voluntary commitments and licensing, while preserving developer control,” she said. “The model’s effectiveness will depend on CAISI’s technical capacity, independent assessment quality, and the strength of enforcement mechanisms.”Building institutions, not gatekeepersA central element of OpenAI’s proposal is to expand CAISI into what it describes as the federal government’s primary institution for frontier AI evaluation, standards development, independent assessment certification, and coordination with national security agencies and international partners.OpenAI argues policymakers need a permanent institution capable of monitoring frontier capabilities and evaluating emerging risks as AI systems evolve.At the same time, the company repeatedly cautions against turning CAISI into a deployment gatekeeper. Developers, it argues, should remain responsible for release decisions, and model deployment should not be delayed because of government capacity constraints or administrative bottlenecks.Gogia said the framework should be understood primarily as a mechanism for generating evidence about frontier AI systems rather than directly determining whether they can be deployed.“It is best understood as an evidence-producing regime rather than an accountability-producing one,” he said. “It will make developers more legible. Whether it makes them more answerable is a separate question.”