TY - JOUR
T1 - AI revolution in insurance
T2 - bridging research and reality
AU - Bhattacharya, Sukriti
AU - Castignani, German
AU - Masello, Leandro
AU - Sheehan, Barry
N1 - Publisher Copyright:
Copyright © 2025 Bhattacharya, Castignani, Masello and Sheehan.
PY - 2025
Y1 - 2025
N2 - This paper comprehensively reviews artificial intelligence (AI) applications in the insurance industry. We focus on the automotive, health, and property insurance domains. To conduct this study, we followed the PRISMA guidelines for systematic reviews. This rigorous methodology allowed us to examine recent academic research and industry practices thoroughly. This study also identifies several key challenges that must be addressed to mitigate operational and underwriting risks, including data quality issues that could lead to biased risk assessments, regulatory compliance requirements for risk governance, ethical considerations in automated decision-making, and the need for explainable AI systems to ensure transparent risk evaluation and pricing models. This review highlights important research gaps by comparing academic studies with real-world industry implementations. It also explores emerging areas where AI can improve efficiency and drive innovation in the insurance sector. The insights gained from this work provide valuable guidance for researchers, policymakers, and insurance industry practitioners.
AB - This paper comprehensively reviews artificial intelligence (AI) applications in the insurance industry. We focus on the automotive, health, and property insurance domains. To conduct this study, we followed the PRISMA guidelines for systematic reviews. This rigorous methodology allowed us to examine recent academic research and industry practices thoroughly. This study also identifies several key challenges that must be addressed to mitigate operational and underwriting risks, including data quality issues that could lead to biased risk assessments, regulatory compliance requirements for risk governance, ethical considerations in automated decision-making, and the need for explainable AI systems to ensure transparent risk evaluation and pricing models. This review highlights important research gaps by comparing academic studies with real-world industry implementations. It also explores emerging areas where AI can improve efficiency and drive innovation in the insurance sector. The insights gained from this work provide valuable guidance for researchers, policymakers, and insurance industry practitioners.
KW - artificial intelligence
KW - automotive insurance
KW - health insurance
KW - PRISMA
KW - property insurance
KW - regulations
UR - https://www.scopus.com/pages/publications/105003417625
U2 - 10.3389/frai.2025.1568266
DO - 10.3389/frai.2025.1568266
M3 - Review article
AN - SCOPUS:105003417625
SN - 2624-8212
VL - 8
JO - Frontiers in Artificial Intelligence
JF - Frontiers in Artificial Intelligence
M1 - 1568266
ER -