International Journal of Science, Engineering and TechnologyAuthors: Athish Gowda
Abstract: The contemporary corporate environment is characterized by unprecedented levels of volatility and complexity, rendering traditional, reactive risk management frameworks insufficient for long-term sustainability. This review article investigates the transformative role of AI-Enabled Enterprise Information Services (AEIS) in modernizing strategic risk assessment and organizational decision-making. We propose a multi-layered conceptual framework that integrates data hramonization, machine learning, and natural language processing to convert fragmented internal and external data into actionable strategic intelligence. The analysis highlights how AEIS facilitates dynamic risk identification by continuously scanning global signals, such as regulatory shifts and competitive movements, providing a real-time alternative to static risk registers. Furthermore, the review examines the shift from predictive to prescriptive analytics, where AI-driven simulations and digital twins allow executives to model the outcomes of strategic pivots under varying economic scenarios. We explore the enhancement of organizational decision-making through Intelligent Decision Support Systems (IDSS), emphasizing the mitigation of cognitive biases and the transition toward continuous, data-backed monitoring. The article also addresses critical implementation barriers, including the "black box" nature of deep learning, the necessity for explainable AI (XAI) in corporate governance, and the ethical implications of algorithmic bias. By synthesizing current literature and technological trends, this review provides a strategic roadmap for integrating AI into the executive suite, concluding that the future of enterprise resilience lies in the synergy between human intuition and machine intelligence.
DOI: https://doi.org/10.5281/zenodo.18228326
