Impacts of Artificial Intelligence Applications on Prescriptive Analytics: Content Analysis Based on Systematic Literature Review

AI applications have rapidly expanded and grown, providing significant advancements to prescriptive analytics in organizations. However, existing research has not yet capitalized on those advancements. While current research has concentrated on fear of people losing their jobs or even lives and not being protected by legislative bodies, a significant gap remains in the absence of AI applications in organizations and how organizations use them for prescriptive analytics. This research aims to fill this gap by designing a framework to show the relationship between AI’s three applications (reinforcement learning, computer vision, and fuzzy logic) and prescriptive analytics in organizations. Qualitative data was collected using an in-depth systematic literature review and was processed using content analysis. Hypotheses were tested using Chi-square analysis. Findings indicate that reinforcement learning, computer vision, and fuzzy logic positively impact prescriptive analytics. Theoretical and practical contributions were offered.