The concept of governance resilience has evolved beyond traditional crisis management, requiring alignment with digital risks. This transition necessitates smart knowledge management systems powered by emerging technologies. This applied, mixed-methods research utilized fuzzy interpretive structural modeling (FISM) and fuzzy MICMAC analysis to identify the hierarchical structure of factors affecting governance resilience. The study engaged 18 academic experts and executive managers in governance, crisis management, and digital transformation using purposive sampling. The analysis identified 13 factors across governance resilience, knowledge management, and emerging technologies, which function as an interconnected, multi-level system rather than independently. “Security, trust, and data governance” along with “connectivity and integration” occupy the most fundamental level of the model. Consequently, effective crisis management requires, first and foremost, the establishment of secure, reliable, and integrated infrastructures. Organizations must develop integrated knowledge management systems capable of organizing crisis reports, employee experiences, and expert knowledge in an accessible environment. Furthermore, the research suggests fostering knowledge networks across government, academia, the private sector, and non-governmental organizations. Critically, the application of artificial intelligence and predictive analytics must shift from a “technology-centric” to a “problem-centric” approach. Instead of merely adopting disparate technologies, decision-makers should first identify information and operational needs within the crisis management cycle, then select appropriate technologies accordingly. This strategic alignment ensures that technological deployment directly serves the core objective of building a resilient governance framework capable of navigating complex, modern crises.