AI innovations are increasingly pivotal to healthcare transformation, reshaping clinical care, organizational processes, and policy frameworks. Yet, the adoption of AI in healthcare encounters significant obstacles, rooted in the intricate dynamics between micro, meso, and macro-level systems, governance structures, and the readiness of organizations to integrate AI.

These challenges are further exacerbated by the need for specialized healthcare AI talent and the indispensable role of public-private partnerships in driving innovation. These partnerships introduce additional layers of complexity, involving value paradoxes, misaligned economic incentives, and stringent regulatory landscapes.