Pandemics, labor shortages, and supply chain instability are just a few of the complex disturbances that healthcare systems are increasingly vulnerable to. Healthcare Resilience 2.0 places a strong emphasis on proactive governance, digital integration, and adaptive capabilities. In order to improve the resilience of the healthcare system, artificial intelligence has become a vital tool for data-driven and adaptable decision-making.The objective of this review is to explore how AI-driven tools improve organizational resilience and adaptive decision-making by methodically synthesizing the body of research on AI integration in healthcare systems.With an emphasis on AI applications in operational management, clinical decision assistance, and strategic planning, a systematic evaluation of recent peer-reviewed publications was carried out. Key resilience-enhancing mechanisms and adaptive management frameworks were identified through the analysis of studies.Healthcare Resilience 2.0 is strengthened by a number of AI-enabled apps, according to the analysis. By predicting admissions and ICU demand, predictive analytics models enhance patient flow management by enabling proactive resource allocation. AI-driven early warning systems lessen systemic load by instantly identifying patient decline and possible outbreaks. During emergencies, AI-driven supply chain optimization improves procurement effectiveness and inventory control. Administrators can also evaluate adaptive techniques in simulated emergency situations using digital twin simulations. When used in tandem, these instruments enhance operational effectiveness, strategic readiness, and responsiveness. AI integration improves adaptability and long-term system sustainability in healthcare operations and governance. In addition to technology deployment, Healthcare Resilience 2.0 calls for strategic alignment between AI systems and corporate decision-making procedures.