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REVIEW article
Front. Artif. Intell.
Sec. AI in Finance
Volume 8 - 2025 | doi: 10.3389/frai.2025.1568266
This article is part of the Research Topic Applications of AI and Machine Learning in Finance and Economics View all 8 articles
AI Revolution in Insurance: Bridging Research and Reality
Provisionally accepted- 1 Luxembourg Institute of Science and Technology (LIST), Esch-sur-Alzette, Luxembourg
- 2 Kemmy Business School, University of Limerick, Limerick, Ireland
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.
Keywords: artificial intelligence, Regulations, health insurance, Property insurance, Automotive Insurance, PRISMA
Received: 29 Jan 2025; Accepted: 24 Mar 2025.
Copyright: © 2025 Bhattacharya, Castignani, Masello and Sheehan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Sukriti Bhattacharya, Luxembourg Institute of Science and Technology (LIST), Esch-sur-Alzette, Luxembourg
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