AI liability in practice: What risk managers need to know now

As artificial intelligence becomes more deeply embedded in business decision-making, questions of accountability, liability, and insurability are moving from theoretical concern to practical urgency. For risk managers, insurers, and corporate leaders alike, the challenge is no longer whether AI introduces new risks, but how those risks are understood, governed, and transferred in an environment where legal, regulatory, and technical frameworks are still evolving.

This conversation with Professor Anat Lior, conducted as part of Willis Towers Watson’s ongoing research into AI liability through the Willis Research Network, builds on earlier analysis in Insuring the AI Age and offers a timely deep dive into how liability for AI-related harm is beginning to take shape. Drawing on empirical legal research and close engagement with insurers, regulators, and technology developers, the discussion highlights where existing insurance models are being stretched, where new approaches are emerging, and where uncertainty remains.

The themes below are particularly relevant for organisations deploying or underwriting AI systems today, as they speak directly to coverage gaps, regulatory divergence, litigation risk, and the evolving role of insurance in enabling safe and responsible AI adoption.

This recording dates to Summer 2025. Viewers should be aware that certain reports, policies, or legislative frameworks discussed may have been updated since that time.

Taken together, these insights underline a central message for risk managers and insurers: AI liability is not a distant or abstract concern, but a present and dynamic risk that requires active engagement. While the insurance market is beginning to respond through experimentation, endorsements, and emerging product concepts, much of the landscape remains unsettled, particularly for novel and rapidly evolving AI applications.

WTW’s collaboration with Professor Lior reflects a broader commitment to helping clients navigate this uncertainty with clarity and foresight. By combining legal scholarship, market insight, and practical risk advisory expertise, this work aims to support organisations in anticipating liability exposure, engaging constructively with insurers, and shaping governance frameworks that enable innovation without undermining accountability.

As AI technologies continue to advance and intersect with other emerging risks, including quantum computing, the ability to align legal understanding, insurance solutions, and risk management practice will be critical. Ongoing dialogue across industry, academia, and policy will play a key role in ensuring that insurance remains a meaningful enabler of safe, resilient, and responsible AI deployment.