Based on a data set of 91 papers and 22 industry studies, we analyse the impact of artificial intelligence on the insurance sector using Porter’s (1985) value chain and Berliner’s (1982) insurability criteria. Additionally, we present future research directions, from both the academic and practitioner points of view. The results illustrate that both cost efficiencies and new revenue streams can be realised, as the insurance business model will shift from loss compensation to loss prediction and prevention. Moreover, we identify two possible developments with respect to the insurability of risks. The first is that the application of artificial intelligence by insurance companies might allow for a more accurate prediction of loss probabilities, thus reducing one of the industry’s most inherent problems, namely asymmetric information. The second development is that artificial intelligence might change the risk landscape significantly by transforming some risks from low-severity/high-frequency to high-severity/low-frequency. This requires insurance companies to rethink traditional insurance coverage and design adequate insurance products.

基于91篇论文和22项行业研究的数据集，我们使用Porter（1985）的价值链和Berliner（1982）的可保性标准分析了人工智能对保险业的影响。此外，我们从学术和实践者的角度提出了未来的研究方向。结果表明，由于保险业务模式将从损失补偿转向损失预测和预防，因此可以实现成本效率和新的收入来源。此外，关于风险的可保性，我们确定了两种可能的发展。首先是保险公司应用人工智能可以使损失概率的预测更加准确，从而减少了业内最固有的问题之一，即信息不对称。第二个发展是，人工智能可以通过将某些风险从低严重度/高频率转变为高严重度/低频率来显着改变风险格局。这就要求保险公司重新考虑传统的保险范围并设计适当的保险产品。