Here’s Why Anthropic Is Pushing States to Regulate AI Faster

2026-07-16 · Source: WIRED - Ai · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, AI Policy & Regulation · Depth: Novice, medium

Summary

Anthropic, an AI company valued at nearly \$1 trillion, is actively advocating for accelerated state-level AI regulation, despite its own head of US state and local policy, Cesar Fernandez, noting that 2025 transparency laws in California and New York are already outdated. The company, founded on a mission to ensure a safe transition through transformative AI, supports stringent regulations for "large AI model developers" to mitigate catastrophic risks like financial disasters or mass deaths. This includes endorsing third-party auditing requirements in Illinois and Massachusetts, with the latter empowering the state's attorney general for injunctive relief. While praised by AI safety groups, critics like David Sacks allege Anthropic's push is a "regulatory capture strategy" to hinder smaller competitors. Anthropic denies this, asserting the regulations target only companies with hundreds of millions in AI development spending and over \$500 million in annual revenue. The company also believes deployment blocks for unsafe AI models should be a federal, not state, prerogative, following a fair evaluation process.

Key takeaway

For Policy Makers drafting AI legislation, your focus must extend beyond basic transparency and self-reporting, as these measures are rapidly becoming insufficient for advanced AI systems. You should prioritize comprehensive safety frameworks, including mandatory third-party audits for powerful AI models and clear definitions for "large AI model developers" based on financial investment. Be mindful of industry arguments regarding regulatory capture, ensuring new laws genuinely mitigate catastrophic risks without unduly stifling innovation or competition.

Key insights

Rapid AI advancement necessitates evolving, stringent regulations beyond mere transparency and self-reporting.

Principles

• AI safety measures must match advancing system capabilities.
• Third-party audits enhance accountability for frontier AI safety.
• Regulatory frameworks should target powerful AI model capabilities.

In practice

• Mandate third-party safety process evaluations for AI labs.
• Grant state attorneys general power to seek injunctive relief.
• Define regulatory thresholds based on AI development spending and revenue.

Topics

• AI Regulation
• Frontier AI Safety
• Third-Party Auditing
• Regulatory Capture
• State AI Policy
• Anthropic

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Editorial summary, takeaway, and curation by AIssential. Original article published by WIRED - Ai.