
This article examines how artificial intelligence agents are fundamentally transforming the insurance industry across multiple dimensions, from risk assessment and claims processing to customer engagement and operational efficiency. The article explores the multifaceted impact of AI technologies on insurance business models and workflows. The research reveals distinct adoption patterns across insurance sectors, identifies critical success factors for implementation, and addresses the complex regulatory and ethical considerations shaping AI governance in insurance. The article demonstrates that while technological sophistication enables significant performance improvements, successful transformation equally depends on organizational readiness, change management approaches, and strategic workforce evolution. The article provides actionable insights for insurance executives navigating the delicate balance between innovation and governance in a highly regulated industry, offering a roadmap for harnessing AI's transformative potential while maintaining compliance and ethical standards. The article contributes to both scholarly understanding of technology-driven business transformation and practical knowledge for industry stakeholders seeking competitive advantage through responsible AI implementation.
Claims Fraud Detection, AI Agents Insurance, Personalized Customer Engagement, Insurance Operational Efficiency, Automated Underwriting
Claims Fraud Detection, AI Agents Insurance, Personalized Customer Engagement, Insurance Operational Efficiency, Automated Underwriting
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
