Who Pays When AI Gets It Wrong: The Liability Gap in Licensed Professions

As AI enters licensed professional decisions, operators cannot answer who is liable when it causes harm, and courts have not yet ruled.

A small breakout of senior operators surfaced one sharp, high-stakes concern and several practical ones. A commercial insurance professional described an emerging and unresolved risk: when AI supports decisions in licensed fields such as medicine, law, accounting, engineering, and insurance, and those decisions cause bodily injury or financial damage, it is unclear who is accountable. Responsibility could fall on the professional, the AI provider, or both. The operator expects case law to settle this, but no courtroom test has yet occurred. Firms are therefore exposed to a risk whose rules will be written after the fact through litigation. This argues for clarifying contracts, documenting human judgment, and reviewing liability coverage now rather than later. The group also touched on workforce dynamics. Advisors observed that men and women face different scrutiny when questioned about using AI, particularly in male-dominated fields, suggesting adoption is uneven and norms around disclosing AI use are inconsistent. Finally, they noted a practical skills gap: workers need structured education on how to create and effectively use prompts. Access to tools is no longer the constraint; skill is. Together these points signal that AI adoption is outpacing the governance, liability, and training frameworks meant to support it. Executives in regulated fields should treat liability ambiguity as a present exposure, set clear internal norms for AI use, and invest in practical training that reaches all staff.