Gartner Says General Counsel Should Assess AI Insurance to Mitigate AI Risks

“As AI incidents surge and insurers increasingly add AI exclusions to traditional policies, companies face growing exposure to legal, financial and regulatory fallout from algorithmic failures,” said Alissa Lugo, Senior Director Analyst in the Gartner Legal & Compliance Practice. “GC should be evaluating a new wave of ‘affirmative AI insurance’ offerings that provide targeted coverage for risks, such as hallucinations, bias, IP infringement and safety failures.”

Gartner analysts advise that if organizations are to broaden AI adoption in a responsible way, legal leaders must develop a clear understanding of the financial, operational and legal implications of dedicated AI insurance, including its costs, benefits and coverage terms (see Figure 1).

Affirmative AI insurance policies offer protection on liabilities that are not covered in more traditional business owner policies, such as:

• AI hallucinations and errors: Covers financial losses if an AI model generates false information (e.g., a chatbot giving bad advice) or makes an incorrect decision.
• Algorithmic bias and discrimination: Covers legal defense and settlements if an AI model inadvertently discriminates against a group (e.g., in hiring or lending).
• IP and copyright infringement: Protects against claims that an AI model was trained on or generated copyrighted material or otherwise infringed on a third-party’s IP without permission.
• Performance guarantees: Innovative “warranty” products will refund license fees or cover costs if an AI model fails to meet specific performance metrics (e.g., accuracy, fairness, etc.).
• Physical damage: Covers large scale property or physical damage resulting from AI giving negligent medical advice, damages as a result of device hacking, AI system failures or AI agent bad actions as some examples.

GC should lead an initiative to assess current coverage for AI risks by reviewing existing insurance policies to determine current level of coverage and gaps, and determine if existing insurance providers have affirmative AI insurance to augment and fill policy gaps.

Further, GC should lead an enterprise AI risk assessment with compliance, legal, marketing, cybersecurity and IT, evaluating the impact of events related to AI failures, such as fines, penalties, lawsuits, and brand/reputation injury that may occur. This can be used in any sales cycle to obtain affirmative AI insurance.

“Ultimately, the rise of affirmative AI insurance signals a simple reality: companies that fail to prepare for AI‑driven liability may soon find themselves exposed,” said Lugo.