The convergence of artificial intelligence (AI) and financial technology (FinTech) has transformed the operational architecture of India's insurance industry, redefining how consumers interact with insurers across underwriting, claims settlement, and personalised advisory services. This study investigates the interplay between consumer trust, perceived security, and behavioural intentions toward AI-enabled FinTech services among insurance customers in India. Anchored in an extended Technology Acceptance Model (TAM) integrated with the Unified Theory of Acceptance and Use of Technology (UTAUT), the research examines how perceived usefulness, perceived ease of use, data privacy concerns, algorithmic transparency, and institutional trust collectively shape adoption behaviour. A quantitative, cross-sectional design was adopted, and primary data were collected from 412 policyholders across metropolitan and tier-II cities using a structured questionnaire measured on a five-point Likert scale. Data were analyzed through descriptive statistics, exploratory factor analysis, correlation, and multiple regression using SPSS. Findings reveal that consumer trust (β = 0.412, p < 0.001) and perceived security (β = 0.338, p < 0.001) exert the strongest positive influence on behavioural intentions to adopt AI-driven insurance services. Data privacy apprehension emerged as a significant negative moderator, while algorithmic transparency substantially enhanced trust formation. The study concludes that Indian insurers must prioritise transparent AI governance, robust cybersecurity frameworks, and human–AI hybrid service models to accelerate consumer acceptance. These insights contribute theoretically by contextualising trust–security dynamics within an emerging economy and offer practical guidance to insurers, regulators such as IRDAI, and policymakers seeking to foster responsible AI adoption in the Indian insurance landscape.