Harnessing Artificial Intelligence for Corporate Crisis Management and Foresight

Traditional corporate crisis management remains largely reactive, rooted in manual monitoring, static risk frameworks, and experience-driven decision-making. These approaches often prove inadequate in today’s volatile business landscape, where crises can emerge and evolve rapidly across digital, financial, and operational domains. Empirical studies indicate that delayed detection and fragmented responses contribute to the escalation of many corporate crises. Artificial Intelligence (AI) offers a transformative approach, enabling organisations to shift from reactive to proactive crisis management. Through advanced technologies such as machine learning, natural language processing, computer vision, graph-based analytics, and generative models, AI systems can process vast volumes of structured and unstructured data, detect early indicators of potential disruptions (including subtle anomalies, patterns, and shifts—referred to as “weak signals”), and support timely, data driven decision-making. This review synthesises current academic and industry literature, presents a structured methodology for identifying relevant studies, and critically examines AI’s capabilities, applications, and limitations in corporate crisis management. Particular attention is paid to issues of human trust in AIgenerated insights, transparency, and ethical considerations— key factors influencing adoption. The paper also outlines open research challenges and suggests pathways for developing AI enabled, trustworthy, resilient crisis management frameworks