Assessing healthcare readiness for AI: a framework for adoption and implementation
TL;DR
A theoretical framework that categorises individuals within healthcare organisations into seven tiers, based on their engagement with AI, provides a roadmap for designing targeted change management strategies that support upskilling, foster ethical governance and enable responsible, system-wide AI adoption in healthcare and biomedical settings.
Abstract
Artificial intelligence (AI) is increasingly recognised as a transformative force in healthcare, offering opportunities to improve diagnosis, treatment and system efficiency. However, successful adoption depends not only on technological capability but also on organisational readiness and cultural alignment. This paper proposes a theoretical framework that categorises individuals within healthcare organisations into seven tiers: sceptics, explorers, implementers, specialists, innovators, strategists and sentinels, based on their engagement with AI and levels of expertise. By mapping the distribution of these tiers, organisations can identify gaps in knowledge, skills and values that are critical to effective AI implementation. The framework outlines tailored strategies for each group, ranging from foundational education and trust-building for sceptics to visionary leadership for strategists and system-level risk oversight for sentinels. It further emphasises the importance of interdisciplinary collaboration between domain experts and AI practitioners to address challenges such as scaling innovations, aligning with strategic goals and managing ethical risks. This tiered approach provides a roadmap for designing targeted change management strategies that support upskilling, foster ethical governance and enable responsible, system-wide AI adoption in healthcare and biomedical settings.