Artificial Intelligence is rapidly becoming a part of the insurance value chain. Insurers are using it for underwriting, claims processing, fraud detection, customer service, product recommendation, risk scoring and operational efficiency. Used responsibly, AI can reduce turnaround time, identify fraudulent claims, improve pricing accuracy and expand insurance access. However, the real challenge before insurers is not only whether AI can improve efficiency, but whether it can strengthen policyholder trust.
Insurance is fundamentally a promise. The customer pays premium today in the belief that the insurer will stand by him or her at the time of loss. If AI is perceived as a tool to reject claims faster, increase exclusions, profile customers unfairly or make decisions without explanation, it will widen the existing trust deficit. This is particularly sensitive in health, life and motor insurance, where customers already worry about claim disputes, hidden conditions and complicated policy language.
Recent developments show that this concern is not theoretical. IRDAI has flagged AI-related cyber risks, pushing insurers to reassess their cyber risk frameworks and preparedness against AI-driven threats. Insurers are now expected to modernise risk evaluation because traditional models may not be adequate in the face of generative AI, synthetic identities and new fraud patterns. Globally too, reports have warned that AI is being embedded in underwriting, claims and cyber defence faster than governance frameworks are maturing.
The trust deficit can be reduced only if insurers adopt AI with transparency and accountability. Customers should know when AI is being used in important decisions and should have access to a clear human review mechanism. No claim rejection, premium loading or adverse underwriting decision should depend entirely on a black-box system. Explainability must become a core principle of AI governance.
Data protection is equally important. Insurance companies handle sensitive financial, health and personal information. Any misuse, leakage or unauthorised sharing of such data can permanently damage customer confidence. A Swiss Re survey found that while many consumers trust insurers to handle data responsibly with AI, insurers still rank behind banks and health companies in consumer trust. This gap must be addressed through stronger consent practices, limited data collection, secure storage and regular cyber audits.
Insurers must also guard against algorithmic bias. Historical data may carry social, regional, gender or health-related biases. If such data is used without correction, AI may unfairly deny cover, increase premiums or delay claims for certain customer groups. Regular model audits, independent testing and ethical review committees can reduce this risk.
AI governance should be owned by the board and senior management, not left only to technology teams. Every insurer should have clear policies on model validation, vendor accountability, customer grievance redressal, cyber incident response and human oversight. Frontline staff and intermediaries must also be trained to explain AI-supported decisions in simple language.
AI can make insurance faster, smarter and more inclusive. But trust will not come from technology alone. It will come from fairness, transparency, security and empathy. In the age of AI, insurers must remember that the most important asset they protect is not data, but public confidence.
Authored by:
Dr. Rakesh Agarwal
Editor, The Insurance Times
