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A bipartisan discussion draft in the House, the Great American Artificial Intelligence Act of 2026, would create the first broad U.S. federal framework for regulating frontier AI developers such as OpenAI, Anthropic, Google DeepMind, and Meta. The proposal would require large model developers to publish safety and governance frameworks, issue transparency and incident reports, assess catastrophic risks, and undergo semiannual independent audits or verification. The bill defines catastrophic risks to include mass-casualty harms, major property damage, cyberattacks, CBRN weapon assistance, and loss-of-control scenarios, while also formalizing the Center for AI Standards and Innovation and funding it at $100 million annually from fiscal 2027 through 2029.
The draft would also block states for three years from specifically regulating AI model development, a provision that drew immediate criticism from opponents who say it could suppress stronger state protections even as it preserves generally applicable state laws and post-deployment oversight. Beyond model governance, the measure would extend the Cybersecurity Information Sharing Act through 2035, direct DHS to support small and rural critical infrastructure operators, fund open-source software maintainers using frontier models for vulnerability discovery and patching, and establish AI testbeds across federal labs and private partners to evaluate threats including autonomous offensive cyber capabilities and risks to critical infrastructure.
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A coalition of state lawmakers sent a letter to Congress opposing the Great American AI Act's proposed three-year preemption of state AI laws. The letter argued the provision would hinder states from addressing AI-related risks involving safety, privacy, livelihoods, and cybersecurity.
Sen. Bernie Sanders put forward an alternative AI legislative approach that would create an AI sovereign wealth fund and give the federal government a 50 percent stake in major AI firms, with returns directed to public benefit. The proposal contrasted sharply with the bipartisan House discussion draft and drew mixed reactions from across the political spectrum.
The discussion draft quickly faced criticism because its language would bar states for three years from specifically regulating AI model development. Critics argued the preemption provision could be overly broad and block stronger state protections, while supporters said it would avoid a patchwork of state laws.
Reps. Jay Obernolte and Lori Trahan proposed the Great American Artificial Intelligence Act of 2026, a bipartisan draft bill to create a broad federal framework for AI regulation. The measure includes frontier model governance, workforce analysis, cybersecurity provisions, and AI research and development, while preempting state AI regulation for three years.
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Illinois, New York, and California have advanced frontier AI laws that would require major model developers to implement safety frameworks, disclose risks, report incidents, and in some cases undergo independent audits, creating a patchwork of state obligations as the United States lacks a comprehensive federal regime. The measures target highly capable models increasingly used in critical infrastructure and other sensitive environments, where policymakers and security leaders warn they could enable cyber abuse such as autonomous zero-day exploitation, guardrail evasion, deception by agentic systems, and AI-assisted ransomware. At the same time, pressure is building for a broader U.S. oversight structure for frontier models. Google DeepMind CEO Demis Hassabis called for an independent, expert-led body to evaluate advanced AI systems before release, while OpenAI said the Trump administration is developing a federal cyber-testing framework for highly capable models and argued that national institutions should lead audits, incident reporting, security standards, and whistleblower protections. Together, the proposals point toward a de facto national baseline for frontier AI governance, though unresolved questions remain around fragmented state compliance, technical rigor, transparency, and how rules would apply to downstream users and modified or embedded models.
Jul 15, 2026
Governments, regulators, and major AI developers moved to formalize oversight of advanced AI systems as concerns grew that frontier and agentic models could accelerate cyberattacks, create liability exposure, and outpace existing governance. In the United States, **NIST** expanded work on AI security through its `AI Agent Standards Initiative`, the `Cyber AI Profile`, and the Commerce Department’s **Center for AI Standards and Innovation (CAISI)**, while Google, Microsoft, xAI, OpenAI, and Anthropic agreed to voluntary pre-release model testing with the government. The White House debated a broader executive order after reports that models such as Anthropic’s **Mythos** and OpenAI’s cyber-focused systems could rapidly identify vulnerabilities and support complex offensive operations; the final order reportedly shortened the review window and paired model access with an AI cybersecurity clearinghouse and vulnerability-sharing measures for critical infrastructure defenders. At the same time, Europe and U.S. states advanced a patchwork of AI governance rules that mixed delayed enforcement with tougher operational expectations. The EU agreed to simplify parts of the **AI Act**, delaying some high-risk obligations while banning nudification tools and preserving strong powers for the Commission’s AI Office over general-purpose AI, even as guidance on high-risk classification and logging requirements continued to emerge. States including Illinois, Utah, Maryland, and San Jose expanded governance-first programs through chief AI officers, sandboxes, incident-investigation frameworks, red teaming, and procurement controls, while insurers, auditors, and legal experts warned that **AI-washing**, weak board oversight, poor logging, and inadequate vendor controls are increasing D&O, regulatory, and tort risk. Across policy, industry, and academia, the direction of travel was toward stronger **auditing, verification, incident reporting, and lifecycle governance** rather than reliance on voluntary model promises alone.
Jul 12, 2026
President Trump signed an executive order, **"Promoting Advanced Artificial Intelligence Innovation and Security,"** that directs federal agencies to strengthen cyber defenses across national security, defense, and civilian systems while promoting U.S. AI innovation. The order tasks **CISA, NSA, OMB, Treasury, ONCD**, and other agencies with near-term deadlines to prioritize cyber defense, expand AI-enabled defensive capabilities, and issue operational directives where appropriate. It also creates an **AI cybersecurity clearinghouse** to coordinate voluntary vulnerability scanning, validation, remediation, and patch distribution with AI companies and critical infrastructure operators, alongside a classified benchmarking process to determine when a system qualifies as a **"covered frontier model."** The final order adopts a narrower oversight approach than earlier drafts, preserving a **voluntary** framework for developers to share advanced models with the federal government and selected trusted partners before broader release while explicitly rejecting mandatory licensing, preclearance, or permitting. Reporting indicates the administration scaled back stronger pre-deployment review proposals after internal debate over how aggressively to address frontier-model cyber risks, with concerns centered on threats to critical infrastructure and the financial system and on whether the **Office of the National Cyber Director** has sufficient authority to coordinate the response. The order also directs the attorney general to prioritize criminal enforcement against actors who use AI to illegally access, damage, or exploit computer systems and data.
Jun 29, 2026