Authors:
Khin Yadanar Hlaing, Hlaing Htake Khaung Tin

Addresses:
Faculty of Information Science, University of Information Technology, Yangon, Yangon Region, Myanmar.

Abstract:

Business Intelligence (BI) has served as a long-time backbone for data-driven decisions but has struggled to turn insights from analysis into action. Decision Intelligence (DI) has emerged as a new approach to addressing this epistemic gap, embedding data analytics, artificial intelligence (AI), and decision theory to support faster, smarter, and more accountable decision-making. This paper demonstrates how DI enhances next-generation BI systems by integrating decision logic, causal reasoning, and human oversight into conventional analytics processes. Grounded in recent literature and applications across healthcare, finance, and supply chain management, this paper shows how DI can transform BI from a descriptive reporting function into a discipline of decision engineering. Despite these advances, unresolved challenges remain, and direction is needed on explainability, ethical governance, and organizational adoption. By triangulating insights from leading research and practice-based literature, this paper identifies future directions for how Decision Intelligence Influences Business Intelligence frameworks, shifting BI systems from analytics tools to a platform for intelligence and informed action.

Keywords: Decision Intelligence; Business Intelligence; Artificial Intelligence; Predictive Analytics; Human–AI Collaboration; Decision Making; Business Environments; Organizational Actions.

Received on: 23/05/2025, Revised on: 14/07/2025, Accepted on: 03/10/2025, Published on: 07/03/2026

DOI: 10.69888/FTSFD.2026.000621

FMDB Transactions on Sustainable Finance and Data Science, 2026 Vol. 1 No. 1, Pages: 10–18

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