How can insurers win customers' trust in AI?
Consumers will switch providers over data privacy or transparency concerns.
Insurance companies may need to explain how they use artificial intelligence (AI) more clearly as customers remain skeptical of the technology, even as employees grow more comfortable with it.
Only 38% of consumers found AI helpful during insurance interactions, according to the 2026 Customer Experience Benchmark report by Smart Communications LLC.
“Customer expectations continue to rise, but many businesses are struggling to keep pace,” Smart Communications CEO Leigh Segall said in the report. “Consumers are telling us they will switch providers when communications fall short... and they are becoming more selective about how and where they trust AI.”
The report found 84% of consumers think companies should disclose when AI is used in customer interactions, whilst 29% had stopped doing business with an insurer because of concerns over data privacy or transparency.
Customer dissatisfaction is also affecting retention. About 63% of consumers globally said they would switch insurers if communications failed to meet expectations, rising to 67% in Singapore.
Only half rated insurers' communications as good or excellent, with unclear messages, complicated forms, and poor coordination across channels among the main complaints.
Employees, however, appear more receptive to AI. A separate report by Howden Group found 64% of workers across Asia trust AI in healthcare, including diagnosis, treatment, and claims, whilst 38% said AI was involved in their most recent healthcare experience.
“As AI becomes more embedded across the healthcare journey, employers play a critical role in ensuring transparency, education, and governance,” Christine Wee, regional director for Asia at Howden Employee Benefits, said. “Employees want clarity on how these tools fit into their care, how their data is used, and how decisions are made.”
The study also found 45% of employers want broader use of AI-enabled healthcare, particularly for diagnosis and screening.
Claim processing, predicting high-cost claims, and virtual general practitioner services were also among the leading applications. Only 3% of employers said they were not considering AI.
Howden said AI could also help manage rising medical costs as Asia's medical inflation rate is projected to reach 11.4%, excluding general inflation, whilst 51% of employers expect healthcare costs to rise.
Questions to ponder:
- Why are customers more skeptical of AI in insurance than employees are in healthcare, and how can insurers narrow that trust gap?
- Which insurance processes should use AI, and which should continue to rely on human judgment?
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EXPERT OPINION
Using publicly available data for AI-based analytics involving customers can erode trust. Customers may be concerned that their information is being inferred from third-party sources, that sensitive details could be misconstrued, or that the analysis may not reflect their real operational context. Even when the data is “public,” the perception of privacy risk and lack of transparency can negatively impact adoption and long-term relationships.
In contrast, a more trusted approach is to use customer-specific domain data (e.g., historical claims/incident information, internal risk assessments, loss control records, and site/facility characteristics). When this is combined with a carefully curated selection of data from the insurer’s own data pool—such as relevant benchmark loss experiences, underwriting guidance, and comparable risk profiles—the analytics become more relevant, explainable, and reliable.
The adoption of AI can improve efficiency and enhance customer experience, but trust will depend on how the technology is designed, governed and implemented. For insurance firms looking to integrate AI across their operations, establishing robust governance frameworks, transparency and clear accountability is essential to earn the trust not only customers, but also all other stakeholders. Adopting responsible AI principles can help address potential issues such as data privacy, third-party usage and regulatory compliance. Additionally, strong AI governance will help identify risks and regularly update security processes, allowing oversight to evolve with the AI landscape. Ultimately, AI should support better outcomes for customers and business, however insurers must ensure accountability, transparency and clear communication how AI is used, how decisions are made and how risks are managed.