AI in Healthcare: Who pays when AI fails?

The healthcare sector is undergoing a significant AI-driven transformation. From clinical decision support and diagnostics to patient triage, claims handling, and predictive analytics, AI offers significant benefits in speed, accuracy, and efficiency. Yet alongside this progress comes a harder truth: AI is introducing new types of risk - algorithmic bias, opaque accountability, system error.

This whitepaper brings together practical insights from Willis experts, real-world litigation trends, and global regulatory developments. It sets out how AI exposures are emerging across multiple lines of insurance and provides a practical roadmap for boards and risk managers to act.

While the promise of AI in healthcare is clear, the protection around it still needs work.

The development of AI

AI is already influencing clinical care, claims decisions and business operations in healthcare. The benefits are clear: enhanced diagnostic accuracy, personalised medicine, drug discovery, streamlined administration, and predictive analytics to forecast patient outcomes. New AI models are being developed and released every day.

The pace of AI development has brought into focus whether:

1. Existing governance and frameworks for managing AI risk are adequate; and
2. AI risk creates gaps in traditional insurance policies.

For any healthcare business, the answer to these questions is likely to become more pressing in the near future.

Healthcare AI fast facts:

• 80% of large US hospitals now use AI for diagnostics or triage
• Only 12% of risk managers say they’ve reviewed AI exposure across their insurance programme

Join us at the US Healthcare Industry Leaders Conference on 23 July, where WILLIS experts will unpack these issues further across Cyber, D&O, E&O, and beyond. To request a tailored AI risk mapping or insurance programme review, contact Andrew Hill, Claudia Piccirilli or Rob Barberi.