Predictive Insurance Marketing in the Age of AI Legal and Ethical Boundaries in a Data-Driven World

Abstract

Background: The integration of artificial intelligence in insurance marketing has transformed how companies assess and predict consumer behavior. “By leveraging behavioral, demographic, and biometric data, insurers personalize services with greater accuracy. However, this advancement raises significant legal and ethical questions regarding data privacy, consent, discrimination, and the adequacy of current regulatory frameworks.
Objective: This study aims to explore how AI-driven predictive marketing is utilized within the insurance sector and to critically examine the associated legal and ethical challenges. The objective is to identify existing gaps in privacy laws, ethical guidelines, and international regulations as they relate to AI's growing influence in consumer-targeted insurance strategies.
Methodology: A systematic literature review was conducted using PRISMA guidelines, focusing on peer-reviewed articles from 2004 to 2024. Databases such as Scopus, IEEE Xplore, Web of Science, and Google Scholar were searched with relevant keywords. Studies were selected based on their relevance to AI applications, data ethics, and legal frameworks in insurance marketing.
Findings: The review revealed that while AI significantly enhances predictive capabilities in insurance marketing, it often operates in legal grey areas, particularly regarding informed consent and algorithmic transparency. Additionally, existing laws show inconsistency across jurisdictions, and ethical concerns such as bias, data commodification, and profiling remain inadequately addressed by both policymakers and insurers.
Conclusion: There is a pressing need for comprehensive, adaptive legal and ethical frameworks to govern AI in insurance marketing. As data-driven models become more prevalent, balancing innovation with consumer rights and fairness is critical. Future policies should promote transparency, accountability, and international cooperation to ensure responsible and equitable use of AI in insurance practices.