Assessing the Impact of Ai-Driven Internal Processes on Organizational Performance in Kenya’s Insurance Industry

This research explores how Artificial Intelligence (AI) is transforming internal workflows within Kenyan insurance companies and, as a result, affecting overall firm performance. Key functions such as underwriting, risk profiling, premium determination, document parsing, claims automation, policy tailoring, and risk assessment are increasingly shifting to AI and Natural Language Processing (NLP) platforms. Positioned at the intersection of growing data resources, human–machine collaboration, and advancing machine learning capabilities, AI is gradually becoming the driving force behind changes in traditional insurance operations. Although the academic community has documented operational improvements related to AI, systematic analyses that directly link these gains to measurable firm-level performance are limited. Using Technology Diffusion Theory, this study adopts a descriptive research approach, surveying all 71 insurance companies licensed by the Insurance Regulatory Authority (IRA) of Kenya. The research combines both qualitative and quantitative methods to assess the extent of AI adoption and the resulting performance outcomes. Findings show a median AI-enabled workflow adoption rate (average rating: 3.833 on a 5-point Likert scale), with this technological implementation currently accounting for 48.6% of the variation in performance observed among respondents.