For cybersecurity incident response firms, the primary go-to-market channel isn't direct sales to enterprises. Instead, they must get on the pre-approved vendor panels of cybersecurity insurance companies. When an insured company is hacked, the insurer dictates which response firm they can use, making these carriers key distribution gatekeepers.

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.

Enterprises face millions of potential vulnerabilities, making prioritization impossible. The key is to ignore the noise and focus only on the small fraction that are actually exploitable by hackers. This shifts remediation efforts from theoretical weaknesses to real-world business risk.

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.

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.

Insurers can price a single large loss. What they cannot price is a single AI model, deployed by thousands of customers, having a flaw that leads to thousands of simultaneous claims. This "systemic, correlated" risk could bankrupt an insurer.

Insurers like Aviva are finding it increasingly difficult to price risk for predictable climate-related catastrophes, such as houses repeatedly built on known floodplains. The near-inevitability of these events makes them uninsurable, prompting the creation of hybrid government-backed schemes where the private market can no longer operate.