AI-Driven Business Resilience Frameworks for Digital Economies

Abstract

Digital economies face increasing risks from cyber threats, operational disruptions, and market uncertainties. Traditional resilience approaches are often reactive and insufficient for dynamic environments. This paper proposes an AI-Driven Business Resilience Framework (AIBRF) that integrates data acquisition, AI analytics, risk prediction, adaptive decision-making, resilience orchestration, and continuous learning. By leveraging machine learning, predictive analytics, and intelligent automation, the framework enables proactive risk management and real-time adaptation. Experimental results demonstrate improvements in risk detection, recovery time, decision-making efficiency, resource utilization, and business continuity. The proposed framework provides a scalable and intelligent approach for enhancing organizational resilience in digital economies, while future enhancements may incorporate generative AI, federated learning, explainable AI, and blockchain technologies.