<![CDATA[Background: This research is motivated by the low adoption rate of Artificial Intelligence (AI)-based information systems in the insurance claim process, particularly Business Rules Management Systems (BRMS), even though these systems are designed to improve efficiency and consistency in decision-making. The main problems lie in the lack of user trust, limited training, and the role of leadership in supporting digital transformation. Objective: Therefore, this study aims to analyze the factors influencing the intention to use insurance claim information systems using a modified Technology Acceptance Model (TAM) approach, expanded with the variables of Trust, Transformational Leadership, and Training. Methods: This research employs a quantitative approach with a survey method targeting Claim Adjusters at the insurance company under study. Data were collected through questionnaires and analyzed using a structural model to test the relationships between variables, including Perceived Ease of Use, Perceived Usefulness, Trust, Transformational Leadership, Training, Intention to Use, and Actual System Usage. Results: The results show that Transformational Leadership positively affects Trust, Trust significantly affects Intention to Use, and Training affects Perceived Ease of Use. Furthermore, Perceived Ease of Use influences Perceived Usefulness, which ultimately impacts Intention to Use and the actual usage of the system. These findings confirm that human and organizational factors play a crucial role in the successful implementation of technology, in addition to the technical factors of the system itself. Conclusion: In conclusion, the successful adoption of AI-based information systems in the insurance industry is determined not only by technological sophistication but also by the level of user trust, the effectiveness of training, and the support of transformational leadership.]]>
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