Foundational AI in Insurance and Real Estate: A Survey of Applications, Challenges, and Future Directions

Abstract

This paper provides a comprehensive survey on the applications, challenges, and future directions of Artificial Intelligence (AI) in the insurance and real estate sectors. We explore key AI-driven solutions, such as advanced risk assessment, predictive analytics for fraud detection, and smart building management, highlighting their impact on enhancing operational efficiency and decision-making processes. The survey covers a wide range of AI techniques, including machine learning, deep learning, and natural language processing, and discusses their specific applications within these industries. We address critical challenges, such as data quality issues, the need for model interpretability, regulatory compliance, and integration with existing systems. Additionally, we identify emerging trends, such as the adoption of reinforcement learning for dynamic pricing and the use of AI for personalized insurance products. The paper concludes by outlining significant research gaps and proposing a roadmap for future work, aimed at guiding the development of more robust, explainable, and ethically sound AI applications in insurance and real estate.

Keywords

• Artificial intelligence
• insurance
• real estate
• machine learning
• deep learning
• natural language processing