Bridging AI perceptions and insurance purchase intentions: the mediating role of perceived ease of use
Dhrub Ranjan, Sunil Kadyan, Manish SharmaPurpose
The insurance industry is being transformed as artificial intelligence (AI) is reshaping customer interactions, insurers' underwriting practices and service delivery. However, there is limited research or evidence on how customers' perceptions of AI-driven insurance services influence their purchase intentions. Taking inputs from technology acceptance model (TAM), this study investigates the relationship between customers' perceptions of AI-driven insurance services (CP-AI) and insurance purchase intentions (IPI) through the mediating role of the perceived ease of use (PEU).
Design/methodology/approach
A cross-sectional design was used in the study to collect the responses from 490 insurance customers from India who were familiar with AI-enabled insurance services. As CP-AI cannot be directly measured, it was conceptualised as a second-order reflective construct consisting of four important dimensions, i.e. attitude towards AI, AI service experience, trust in AI services and technology readiness. The hypothesised relationships were tested using partial least squares structural equation modelling (PLS-SEM).
Findings
The findings of the study highlights that the CP-AI have a significant positive impact on their purchase intentions. In addition, PEU partially mediates the relationship between CP-AI and their purchase intentions.
Research limitations/implications
The findings indicate that when customer perceptions are favourable, they are more effectively converted into IPI. In other words, if the AI-enabled insurance services are viewed as simple and effortless to use, the favourable customer perceptions are more likely to be converted into stronger IPI. These findings support the premise of the TAM that PEU is an important element linking technology perceptions to behavioural intentions, even in AI-enabled insurance service contexts.
Practical implications
The findings of the study provide practical insights for insurers to improve AI adoption among their customers by designing customer-friendly and easy-to-use AI-driven services, which will further improve customer acceptance and strengthen their purchase intentions.
Originality/value
This study extends research on AI-enabled insurance adoption by examining how customer perceptions influence purchase intentions through PEU. Its originality lies in conceptualising customer perceptions as a second-order reflective construct comprising attitude towards AI, AI service experience, trust in AI and technology readiness. Drawing on the TAM, the study demonstrates that perceived ease of use serves as an important mechanism linking favourable AI perceptions with purchase intentions. Based on responses from 490 Indian insurance customers, the study extends TAM to the AI-driven insurance context and offers practical insights for designing intuitive, customer-centric AI services.