AI in the Insurance Industry: Percveptions and intentions to use

As the insurance industry increasingly integrates Artificial Intelligence (AI), it is critical to recognize that while AI can optimize operations and enhance customer service, it also introduces challenges that can affect both insurers and policyholders. This study seeks to understand the precursors to AI-related challenges within the insurance industry and their potential effects. Employing a quantitative methodology, the empirical study was conducted through an online questionnaire. From a non-probabilistic convenience sampling, 152 responses were collected and deemed valid. Analysis through partial least square structural equation modeling (PLS-SEM) indicated that, concerning the behavior of insurance professionals and customers, trust in AI is the predominant factor influencing AI-related challenges in the industry. However, these challenges are also influenced by factors such as data privacy concerns, algorithmic transparency, and the complexity of AI systems. There exists a positive correlation between these factors and AI-related challenges, indicating that as these factors increase, so do the challenges. In turn, these AI-related challenges impact the intention to adopt AI within the industry and the overall satisfaction of insurance professionals and customers. The proliferation of AI-related challenges could lead to hesitancy in AI adoption and a decrease in user satisfaction. Academically, this study expands the knowledge of AI-related challenges in the insurance sector, investigating previously unexplored relationships. From a business perspective, it provides insights into adapting strategies to mitigate the challenges associated with AI, allowing for an evaluation of the impact these challenges have on the industry's operations and customer relations.