Business Intelligence and Business Process Management in the Era of Generative AI: A Review of Big Data Analytics, Process Mining, and Decision Support Systems

Business intelligence (BI) and business process management (BPM) have traditionally addressed related managerial problems from partly separate perspectives, while big data analytics, process mining, generative AI, and decision support systems are increasing the pressure toward integration. This review examines how these domains relate within a shared business-processing and decision-making context. Methodologically, the paper adopts a narrative review approach based on peer-reviewed literature published from 2015 onward, drawing on Google Scholar, Scopus, and Web of Science, and synthesizes the literature thematically across conceptual foundations, data and computational infrastructures, process intelligence, generative AI, application domains, and implementation tensions. The review finds that the literature does not support the claim that these areas have already converged into a stable, unified field. Instead, it shows a gradual movement toward a layered architecture in which BI and business analytics support organizational insight, BPM and process mining provide process intelligence, big data analytics supplies the evidentiary and computational base, generative AI functions as an interaction and augmentation layer, and decision support systems translate these elements into managerial action. The paper concludes that this emerging integration is meaningful but still uneven, with its practical value depending on interoperability, evaluation realism, governance, and the preservation of human oversight in AI-supported business processes.