AI adoption inside familiar client accounts often introduces exposures that historical claims files do not reveal. Underwriters and brokers who rely solely on loss history risk missing technical, governance and sales-driven liabilities that can trigger costly claims.
AI’s Hidden Risks: Beyond Familiar Client Profiles
New AI components can change a risk profile even when the client relationship is long standing. Underwriters must look past legacy controls and ask for technical specifications, model provenance, data sources, training labels and vendor contracts. Sales language and product claims are as relevant as code. Governance matters: who approves model changes, what testing was performed, and who holds operational responsibility. Direct conversations with engineers and senior leaders reveal material details that papers and past claims do not.
The Broker’s Pivotal Role in Closing the Protection Gap
Brokers often hesitate to assess complex, early-stage technologies. Yet risks frequently originate in marginal activities that sit outside core governance, such as pilot programmes, side projects or third-party integrations. Brokers should translate technical risk into underwriting terms through targeted questionnaires, risk maps and red-flag summaries. Specialised broker teams or panels of independent experts can convert opaque technical facts into actionable exposures for underwriters.
Policy Clarity and Regulatory Foresight for AI
Many policies remain silent on AI, creating ambiguity when a claim arises. Silent coverage leaves insurers and clients disputing whether an event is covered, widening the protection gap. Policies need affirmative AI definitions, clear exclusions and tailored sublimits for algorithmic harms. Regulatory frameworks offer helpful precedents. Data protection regimes such as GDPR show how liability can attach to data mismanagement. Emerging rules like the EU AI Act will influence negligence and compliance obligations and should inform coverage language and underwriting appetite.
Familiar clients can present unfamiliar risks when they deploy AI. The remedy is proactive, technical due diligence, sharper broker translation and explicit policy wording aligned to regulatory trends. Absent these steps, the industry will face more contested claims and a broader global protection gap.
