The Dynamics of Knowledge Growth in Business Intelligence and Analytics: A Bibliometric Investigation

Business Intelligence and Analytics (BI&A) has emerged over the last thirty years as a vital domain for driving organizational performance, digital transformation, and competitive advantage. As the field continues to expand rapidly with the rise of AI-augmented analytics, understanding the structure and direction of existing research becomes critical. Without a clear map of intellectual progress and thematic shifts, both academic and practical efforts risk becoming disconnected and misaligned. As a result, our research objective is to provide a systematic bibliometric investigation of the evolution of knowledge within the BI&A research field. The motivation behind this analysis is to bring clarity to a complex and growing body of literature and to identify strategic pathways for future research and practice. By uncovering the foundations, trends, and turning points in the field, we support a more informed and impactful development of BI&A strategies across sectors. We examine a dataset of 2,374 peer-reviewed articles indexed in Scopus, applying a combination of bibliographic coupling, co-authorship exploration, and keyword co-occurrence mapping. Following the PRISMA guidelines and employing text mining, we create key thematic clusters and trace the emergence of influential research streams. The results reveal a strong progression from early technical focus to more integrated, strategic, and domain-specific applications. This transition highlights the importance of cross-disciplinary collaboration and the alignment of analytics with real-world business needs. Practically, the findings help scholars target under-explored clusters, guide organizations in aligning analytics investments with capability and governance needs, and support policymakers and business leaders in fostering cross-disciplinary and cross-country collaboration to reduce fragmentation and accelerate decision-making.