The paper investigates how intelligent knowledge systems reshape incentives and responsibilities in corporate crisis governance under the Italian legal framework. It focuses on the interaction between the Code of Business Crisis and Insolvency (CCII) and Legislative Decree 231/2001 on corporate criminal liability, analysing how legal duties of early detection and adequate organisational arrangements intersect with the emerging use of AI-enabled early-warning and monitoring tools. The central question is under which conditions these systems function as levers for sustainable and responsible governance, and when they instead generate new risks of moral hazard, scapegoating and purely formalistic compliance.
Theoretically, the paper bridges three strands of literature: knowledge management and organisational learning, which conceptualise knowledge as a strategic asset increasingly mediated by digital technologies (Nonaka and Takeuchi, 1995; Argote, 2013; Schiuma, 2011); law and economics of corporate crisis and insolvency, which examines how sanctions and incentives shape directors’ behaviour in the vicinity of insolvency (Jensen and Meckling, 1976; Coffee, 2006; Armour and Ringe, 2020); and socio-legal and criminological studies on corporate crime and compliance, which highlight the role of organisational cultures and control architectures in enabling or constraining wrongdoing (Clinard and Yeager, 1980; Braithwaite, 1989; Parker, 2002). Building on these perspectives, the paper proposes to conceptualise corporate crisis governance as a knowledge-based regulatory game in which legal rules, intelligent knowledge systems and organisational cultures jointly determine the information and payoff structures faced by corporate actors.
Methodologically, the study adopts a qualitative, analytical-conceptual design that combines doctrinal analysis of the CCII and Legislative Decree 231/2001 with theory-informed discussion of AI-enabled early-warning and HR-analytics-based frameworks, including prior empirical work by the author on predictive HR analytics for financial risk prevention (Laudonia et al., 2025).
The analysis shows that intelligently designed and well-governed knowledge systems can enhance the preventive aims of the CCII and the compliance-oriented incentives of the 231 regime by reducing information asymmetries, supporting timely escalation and enabling more informed restructuring decisions. However, it also warns against the risks of black-box solutions that may foster over-reliance on algorithms, diffusion of responsibility and symbolic compliance. The paper concludes by outlining design principles for intelligent knowledge systems in crisis governance—transparency, explainability, preservation of professional judgement, robust data-governance and learning-oriented feedback loops—and by deriving implications for regulators, boards and compliance officers concerned with aligning legal accountability, effective risk reduction and long-term organisational sustainability.