The insurance industry acts as a powerful de facto regulator. As major insurers seek to exclude AI-related liabilities from policies, they could dramatically slow AI deployment because businesses will be unwilling to shoulder the unmitigated financial risk themselves.

Existing policies like cyber insurance don't explicitly mention AI, making coverage for AI-related harms unclear. This ambiguity means insurers carry unpriced risk, while companies lack certainty. This situation will likely force the creation of dedicated AI insurance products, much as cyber insurance emerged in the 2000s.

Frontier AI companies like Anthropic can go public without traditional liability insurance. Their massive valuations allow them to self-insure, while securities laws primarily require them to thoroughly disclose all risks in their S-1 filing—even the risk of destroying humanity.

Drawing from the nuclear energy insurance model, the private market cannot effectively insure against massive AI tail risks. A better model involves the government capping liability (e.g., above $15B), creating a backstop that allows a private insurance market to flourish and provide crucial governance for more common risks.

Anthropic's potential IPO presents a unique challenge: how to articulate the existential risks of its own technology in a legally required S-1 filing. With its founders on record about AI's dangers, the 'Risks' section will be a fascinating and potentially market-moving document.

Insurers like AIG are seeking to exclude liabilities from AI use, such as deepfake scams or chatbot errors, from standard corporate policies. This forces businesses to either purchase expensive, capped add-ons or assume a significant new category of uninsurable risk.

Without clear government standards for AI safety, there is no "safe harbor" from lawsuits. This makes it likely courts will apply strict liability, where a company is at fault even if not negligent. This legal uncertainty makes risk unquantifiable for insurers, forcing them to exit the market.

Sam Altman cites safety for delaying OpenAI's IPO, but this is likely an excuse. The real issues are negative momentum, pressure from investors, and the difficulty of crafting an S-1 filing that discloses unprecedented existential risks in a regulatory vacuum, creating a "no man's land" for going public.

A straightforward regulatory step would be to hold AI companies legally responsible for any crimes their models commit. This simple shift in liability would force labs to slow down and prioritize safety, as they would be unwilling to deploy models they cannot fully control.