Generative AI for Business Continuity Management: Enhancing Preparedness and Response

Business Continuity Management is increasingly recognised as a cornerstone of organisational resilience and competitive advantage. However, despite its acknowledged strategic relevance, it remains insufficiently integrated within corporate management practices. Persistent barriers, ranging from organisational heterogeneity and fragmented data ecosystems to the lack of standardised operational frameworks, continue to constrain its effective implementation. The technological transformation driven by Industry 4.0 has amplified both the importance and complexity of business continuity, as automation and interconnectivity intensify systemic dependencies and vulnerabilities. This thesis explores how Generative Artificial Intelligence can act as a transformative enabler in addressing these challenges. By bridging the gap between strategic intent and operational execution, Generative AI provides responsive and context-aware intelligence that supports the adoption, coordination, and continuous governance of business continuity processes. Through the analysis of a real-world case study, the research demonstrates how AI-driven solutions can operationalise theoretical frameworks into dynamic, data-informed practices that strengthen preparedness and embed resilience at the strategic core of the enterprise. The findings highlight the transformative potential of Generative AI to make business continuity management more easily adoptable, systematically governed, and seamlessly integrated within organisational structures and decision-making processes, establishing it as a strategically aligned discipline within the modern enterprise.