Generative AI and Augmented Business Analytics for Managerial Decision-Making: A Scopus-Based Bibliometric and Thematic Analysis, 2019-2026
Keywords:
Generative AI, Augmented Analytics, Business Analytics, Business Intelligence, Large Language Models, Managerial Decision-making, Bibliometric Analysis, ScopusAbstract
The business landscape is changing with the introduction of generative AI and augmented analytics, which transform business intelligence from descriptive reporting to a more conversational experience, from automatic insight generation to the ability to explain decisions or use AI to guide managerial judgment. In this study, fragmentation is tackled by conducting a bibliometric and thematic analysis of 92 documents retrieved between 2019 and 2026 from the Scopus database. The analysis includes performance analysis, citation analysis, country and source mapping, keyword co-occurrence, bibliographic coupling and thematic mapping using Bibliometrix/Biblioshiny, and Excel. The results indicate a young field that is growing quickly with 77.2% of documents published in 2025-2026, and an annual growth rate of 63.32%. The corpus is dominated by conference papers, which reflects the early dissemination of knowledge, and the core conceptual vocabulary includes business intelligence, large language models, artificial intelligence, generative AI, natural language processing and augmented analytics. The thematic structure indicates that the field is characterized by a focus on decision making, language models and business intelligence, and the need for trust, explainability, effectiveness of validation, data governance and human-AI collaboration is not fully integrated. The study makes a significant contribution by shifting the focus from GenAI as a mere technical extension of BI to a new decision-intelligence capability. It also proposes a conceptual framework linking generative AI, augmented analytics, business analytics capability, managerial decision quality, governance mechanisms and business performance.
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Copyright (c) 2026 Dr. Khurram Shahzad Khan, Dr. Maseehullah, Mr. Sajid Yaqoob, Ms. Hina Jamil (Author)
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