The role of artificial intelligence in the insurance sector: An examination on opera-tional efficiency and customer experience

This thesis aims to examine the role of Artificial Intelligence (AI) technologies in the insurance sector, focusing on operational efficiency and customer experience. With the acceleration of digital transformation, AI has triggered a profound shift in the structure and functions of the insurance industry. Applications such as claims management, risk assessment, dynamic pricing, fraud detection, and customer service significantly enhance operational processes by reducing costs, increasing speed, and providing more personalized services. However, these advancements also raise new concerns regarding data security, algorithmic bias, ethical responsibilities, and regulatory compliance. The first chapter outlines the purpose, scope, and methodological framework of the study, emphasizing why AI has become a strategic component in the insurance field. The second chapter defines AI, discusses its historical development, categories, and technological foundations, including machine learning, deep learning, natural language processing, and robotic process automation. It also presents the general structure, historical evolution, product types, key stakeholders, and digital transformation of the insurance industry, thereby constructing a comprehensive conceptual framework. The third chapter investigates international AI applications in the insurance sector, analyzing practices in countries such as the United States, the United Kingdom, Germany, China, and Japan. Case studies from innovative InsurTech companies like Lemonade, ZhongAn, and WeFox are included. Additionally, global policies and regulatory frameworks, including the European Union's AI Act, are discussed. The fourth chapter focuses on AI implementation in the Turkish insurance market. It offers detailed examples of AI usage in areas such as risk evaluation, pricing, automated claims assessment, customer interaction, fraud detection, and policy management. The fifth chapter evaluates the benefits of AI (e.g., efficiency, customer satisfaction, cost savings) as well as the challenges it brings, including ethical dilemmas, workforce transformation, data privacy, and regulatory ambiguity. The sixth and final chapter presents key findings and proposes forward-looking strategic recommendations. These include corporate transformation strategies, digital talent development, ethical governance, compliance with evolving regulations, and fostering InsurTech collaborations. Future research suggestions address topics such as AI implementation in SMEs, algorithmic transparency, data ethics, and hybrid human-AI workforce models. This study aims to offer a strategic roadmap for the ethical and sustainable integration of artificial intelligence in the insurance sector and to contribute meaningfully to both academic literature and sectoral practices in Turkey.