The AI-Driven Resilience Engine: Research on the Framework Construction and Behavioral Logic of BCM Agents

Abstract

With the deepening of digital transformation, the business environment and cybersecurity threats faced by enterprises are becoming increasingly complex and volatile. Traditional Business Continuity Management (BCM) models, which rely heavily on manual labor and passive response, can no longer meet organizations' urgent demand for "resilience." The explosion of Generative Artificial Intelligence (GenAI) and Agent technologies provides a novel paradigm for the intelligent and automated reconstruction of BCM. This paper takes the "BCM Agent Framework and Behavioral Logic Diagram" as its research object, systematically deconstructing its core closed-loop logic of "Continuous Perception, Generating Recommendations, Guiding Actions, Validating Capabilities, and Promoting Growth." Firstly, the paper analyzes the pain points of digital transformation currently facing BCM. Secondly, it deeply dissects the seven-layer architecture system of the BCM Agent, focusing on the core engine's seven capability modules, the structured precipitation mechanism of the organizational memory base, and the seven-step closed-loop behavioral logic from perception to capability enhancement. Thirdly, combining the latest practical cases in the financial industry and intelligent operations, it demonstrates the core value of AI-BCM Agents in risk prediction, automated emergency response, and cross-departmental collaboration. Finally, drawing on research results from core journals in the past three years, this paper proposes future trends and governance challenges for BCM Agents, providing theoretical references and practical pathways for enterprises to build a "trustworthy, visible, and controllable" digital resilience system