From Insights to Trust: A Review of AI-Driven Business Analytics Literature

This paper provides a comprehensive review of the application of artificial intelligence (AI) in business analytics (BA) with a focus on trust and transformative impacts. Employing topic modeling and PRISMA as methods for literature review, a thematic analysis of 61 academic articles published between 2019 and 2024 was conducted, uncovering key trends in trust, decision-making, data- driven processes, and AI-driven transformations. The study identifies five primary themes: the integration of AI in business intelligence and machine learning (ML); organizational strategies for innovation, the role of big data in education and skills development; methodological advancements in AI applications; customer adoption of AI-driven tools; and the broader implications of AI in Business Analytics. Sentiment analysis reveals predominantly positive perspectives on AI’s transformative potential, though challenges such as organizational resistance, skill gaps, and methodological limitations persist. This review highlights the critical need for interdisciplinary research to address these challenges and foster trust in AI-driven business analytics.