Customer Perceptions Of Ai-Driven Health Insurance Services And Their Impact On Insurance Purchase Intentions

Abstract

This paper examines the integration of Artificial Intelligence in health insurance services, focusing on how customer perception and legal/ethical gaps influence insurance buying intent. The study find that while AI offers substantial benefits in operations, risk assessment, and customer service, its widespread adoption is hampered by significant doctrinal and regulatory shortcomings. Specifically, obscurity and explainability in AI formula and techniques creates a “black box” effect that erodes consumer trust. Existing legal frameworks such as India’s IT Act & U.S.’s FCRA, were not designed to tackle the unique problems posed by AI, particularly concerning algorithmic bias, data privacy, and liability for errors. These issues create a legal and ethical void that directly impacts customer trust and the willingness to engage with AI-driven services.

The analysis reveals that beyond technical performance, the success of AI in this sector in contingent upon building a trust-based relationship with customers. In order to mitigate perceived risks, insurers must establish strong data governance, guarantee transparency, and keep a person in loop when making critical decisions. The paper concludes that for AI to realize its transformative potential, the industry must proactively develop a new regulatory framework that mandates accountability and fairness. This will not only bridge the existing doctrinal gaps but also build the essential foundation of trust required for the moral and successful blending of AI into the Health insurance industry.