Silent AI Is Out, Affirmative Coverage Is In

Summary: AI is one of today’s fastest-growing business risks, yet many traditional insurance policies remain silent. History has shown that ambiguous coverage leads to disputes, unexpected costs, and costly claim denials—just as it did with cyber insurance. Fortunately, there is another option. To avoid repeating these pitfalls, industry leaders are advocating for a clear, proactive solution: affirmative AI insurance.

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Global Law Firm Warns Against Silent Coverage

Kennedys Law LLP, a global leader in insurance law, recently flagged AI as a rising risk in its annual report on global risks. The report highlights concerns about coverage gaps and urges businesses to consider affirmative AI policies:

“They [businesses] should also consider the need for affirmative AI policies that would specifically cover losses where AI technologies do not perform as intended.”

“For [those] wishing to avoid a dispute from a gap in cover or unintended cover, insurance products need to contain clear, unambiguous wordings.”

Like Kennedys, more industry leaders are voicing concerns about silent AI risks and coverage gaps, underscoring the need for clear, affirmative policies—reflecting helpful lessons from the rise of cyber insurance.

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Confidence in Silent AI is Fading

Just as silent cyber coverage eventually gave way to disputes and exclusions, industry leaders are increasingly recognizing that traditional policies fail to adequately address AI risks.

• AI endorsements from several carriers may have appeared to clarify AI coverage, but many see them as precursors to exclusions, limiting insurer exposure rather than expanding protection.
• Similarly, skeptics see a major carrier’s recent comments on existing policies as echoing comments around early silent cyber—when coverage assurances ultimately led to denied claims and litigation.
• Recently, a leading brokerage noted that AI exclusions are beginning to emerge, with existing policies only "partially responding" to AI-related claims
• And like Kennedy’s, global reinsurer Swiss Re has repeatedly warned that relying on silent AI is a major gamble.  

“Coverage gaps caused by silent AI risks could expose businesses to significant financial and reputational losses. … With silent AI, it is time to prevent repetition of the same mistakes … Clarity and precision in underwriting AI risks are essential.” — Swiss Re, 2024

 The smarter approach? Proactive, affirmative AI insurance.

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Proactive, Affirmative AI Insurance

AI risk shouldn’t be an afterthought—it demands a proactive, affirmative approach across the entire risk management life cycle. Silent coverage leaves gaps, leading to disputes, exclusions, and uncovered losses. Brokers and risk managers play a critical role in ensuring AI risks are assessed, quantified, and explicitly insured before issues arise. A complete strategy integrates:

• AI Risk Assessments – Identifying vulnerabilities in performance, bias, and compliance.
• Risk Quantification & Mitigation – Measuring exposures and implementing safeguards.
• Affirmative Coverage – Ensuring AI risks are clearly covered, not left to interpretation.

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Are You Proactively Managing AI Risk?

Waiting for coverage disputes and exclusions to arise is not a strategy. The insurance industry learned this lesson most recently with cyber risk, and AI is next. Enterprises are looking for trusted advisors to help them confidently deploy AI, with greater certainty that risks are continuously managed and covered. 

AI innovation and risk are evolving rapidly. Here are some questions that can help you take a proactive approach: 

AI Risk Awareness

• Do you have full visibility into where AI is deployed in the organization, including in AI vendor solutions?
• Have you identified AI-driven financial, legal, and reputational risks that could lead to claims or disputes?

AI Risk Quantification

• Are you assessing AI system risks—such as performance failures, bias, security vulnerabilities, and regulatory exposure?
• Have AI models been stress-tested through quantitative evaluation, scenario analysis, or red-teaming?
• Have exposures been quantified and matched to coverages?

Coverage Clarity

• Have insurers introduced AI-related exclusions that could leave businesses exposed?
• Do existing policies explicitly define AI-related risks, or is coverage ambiguous?
• Are high-risk AI systems covered under silent or affirmative insurance language?
  

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‍Contact us to learn how Armilla AI helps enterprises assess, quantify, and insure AI risk in partnership with top brokerages.

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