Digital Trust and AI-Driven Insurance Services: Their Impact on Policyholder Perception and Adoption in Tamil Nadu

Abstract

The adoption of artificial intelligence (AI) is transforming the insurance industry. Given the growing digitalization of the market in emerging economies such as India, understanding how consumers perceive and are likely to adopt insurance services provided through AI-driven channels is critical for insurance providers and technology vendors. This study focuses on Tamil Nadu, India, and investigates the impact of digital trust and various attributes of AI-driven insurance services on policyholder perception and adoption intention. This study incorporates factors such as algorithmic transparency, digital trust, AI service quality, perceived usefulness, perceived risk, social influence, and policyholder perception into an integrated framework to understand the concept of adoption intention. This study utilized a cross-sectional research design, in which a questionnaire survey of 628 respondents was conducted. The results obtained from applying Structural Equation Modeling (SEM) with the help of the AMOS software revealed that the measurement model obtained was adequate, exhibiting high reliability, convergent validity, and discriminant validity. However, the structural model did not follow the conventional path of technology adoption, as the hypothesized relationships between digital trust, perceived usefulness, perceived risk, social influence, and adoption intention were found to be statistically insignificant. These results suggest the emergence of a ‘post-adoption behavioral paradigm’, whereby digital trust is perceived as a natural expectation, risks are normalized, and individuals display increased individualization in their technology adoption decisions. Most importantly, the relationship between policyholder perception and adoption intention was found to be weak. The study offers new insights through its emerging market-based perspective and helps further knowledge about AI-based insurance adoption by suggesting a move towards experience-oriented and nonlinear theories. Further research must explore the threshold of trust, the process of risk normalization, the role of digital literacy and past experience, and behavioral change among policyholders to create future-generation AI adoption models for digital finance.