AI-Driven Enterprise Risk Management: A Strategic Approach to Predictive and Preventive Decision-Making

Abstract

In the rapidly evolving digital economy, organizations face increasingly complex and dynamic risks that challenge traditional approaches to Enterprise Risk Management (ERM). Artificial Intelligence (AI) has emerged as a transformative force, offering novel capabilities for data-driven risk prediction, assessment, and mitigation. This paper explores the integration of AI into ERM frameworks, positioning it as a strategic enabler for predictive and preventive decision-making. We examine how machine learning algorithms, natural language processing, and big data analytics empower organizations to anticipate risks with higher accuracy and respond proactively to emerging threats. The study synthesizes insights from current industry practices, case studies, and academic literature to outline a framework for AI-enhanced ERM. It further discusses implementation challenges, ethical concerns, and governance mechanisms essential for successful adoption. The research concludes with actionable recommendations for leveraging AI as a value-creating asset in enterprise risk strategy, thereby fostering resilience, agility, and sustainable competitive advantage in an increasingly uncertain global environment.