The disruption triggered by the coronavirus (COVID-19) has induced unplanned growth across the healthcare industry. Despite these challenges, leaders in healthcare see tremendous potential in AI and analytics to deliver on the promise of higher quality care at a lower cost by empowering their executives, business leaders, clinicians, and nurses by harnessing the power of predictive and prescriptive analytics. Many healthcare organizations are seeking to harness the vast potential of Artificial Intelligence (AI) and its four components -- machine learning (ML), natural language processing (NLP), deep learning, and robotics -- to transform their clinical and business processes. They seek to apply these advanced technologies to make sense of an ever-increasing "tsunami" of structured and unstructured data, and to automate iterative operations that previously required manual processing. I have analyzed and calibrated these technologies leveraging a seminal strategy framework from John Gourville, Harvard Business School professor, predicated on the resistance to patient adoption, as well the degree of change behavior needed from physicians, clinicians, nurses, providers, payers, policy makers and the government, which will likely assure a high probability of success, in my humble opinion and will inform post-pandemic strategy blueprints and scenario/policy planning from these entities.