AI-driven digital transformation (AIDT) plays a crucial role in enabling organizations to adapt to the rapidly changing landscape of digital innovations and modern technologies. However, it also brings forth its own array of challenges which are even more pronounced in hospitals, which often operate in crisis mode, where the margin for error must be minimal, even amidst resource constraints and unforeseen pressures such as the COVID-19 pandemic. Hence, the question arises: How does a high-demand context such as a hospital facilitate its AIDT amid the pressures of constant patient care and evolving medical technologies? To address this question, we have been conducting an in-depth case study by examining CHUM’s School of AI in Healthcare (SAIH). By studying its approach, challenges, and functions, we aim to provide insight into navigating AIDT in healthcare. Upon completion of the research, we will provide actionable recommendations that can be implemented in similar high-pressure contexts.