The rapid digitalization of insurance services is changing how people in Emerging Markets (EMs) and Africa can access financial help. However, this change comes with its own set of challenges. By using tools like artificial intelligence (AI), big data, and automation, digital insurers can offer better efficiency and make services more accessible. This chapter points out that the growth of digital insurance in EMs is held back by issues such as unclear algorithms, inefficient services, and a lack of trust. Using South Africa as a focal case, the chapter employs a computational sentiment analysis approach to examine consumer perceptions of digital insurance services, identifying key concerns that influence satisfaction and trust. The findings contribute to theoretical advancements by extending Expectancy Disconfirmation Theory to AI-driven insurance, refining SERVQUAL dimensions in fully digital services, and highlighting algorithmic trust challenges in financial decision-making. The study also underscores the Digital Divide Theory, demonstrating how disparities in digital literacy and access affect engagement with digital insurers. This chapter discusses the importance of combining automated processes with human help in service models. It also highlights the need for clear AI systems that increase transparency and programs that educate consumers to make things easier to use. Regulators should create policies to guarantee fairness in AI-based insurance and claims handling. Overall, this study stresses the need for innovation that focuses on consumers to ensure that digital insurance in Africa and other EMs remains inclusive, transparent, and sustainable.