Title: Artificial Intelligence-Driven Decision Intelligence for Organizational Transformation
Authors: Mai Abdelghani
Volume: 10
Issue: 6
Pages: 21-29
Publication Date: 2026/06/28
Abstract:
Artificial Intelligence (AI) adoption has expanded rapidly across organizations; however, many firms continue to struggle to translate AI investments into scalable organizational value and sustainable transformation outcomes. Existing literature indicates that organizations often implement AI as isolated models, dashboards, or automation tools without embedding these technologies into organizational decision workflows, governance structures, and operational processes. Consequently, Decision Intelligence (DI) has emerged as a decision-centric approach that integrates data, analytics, AI, human expertise, workflows, and governance mechanisms to improve organizational decision-making and strategic performance. This study aims to develop a conceptual framework explaining how AI-driven Decision Intelligence can support organizational transformation through structured and governable decision systems. Using an integrative conceptual methodology, the study synthesizes prior literature from Decision Intelligence, AI-driven decision-making, digital transformation, organizational transformation, and AI governance. The proposed framework consists of four interconnected building blocks: inputs and foundations, AI-driven Decision Intelligence capability, governance layer, and transformation outcomes. The framework explains how predictive, causal, prescriptive, and generative AI technologies can be integrated with organizational workflows, decision logic, human roles, and governance systems to enhance decision quality, accountability, consistency, and responsiveness. The study further emphasizes that governance mechanisms such as human oversight, monitoring, audit trails, escalation procedures, and risk controls are essential for ensuring trustworthy and explainable AI-enabled decisions. The study concludes that organizational transformation is achieved not through AI technologies alone, but through embedding AI into transparent, governable, and continuously learning decision workflows. The proposed framework contributes theoretically by positioning Decision Intelligence as a higher-order organizational capability that operationalizes organizational transformation through structured decision systems and continuous feedback loops. Practically, the framework provides organizations with a decision-centric roadmap for implementing AI responsibly and effectively to improve operational performance, organizational learning, accountability, agility, and long-term competitiveness