Toward an AI Maturity Model in Healthcare: Identifying Core Dimensions and Critical Success Factors

Abstract

Artificial Intelligence is increasingly recognized as a critical enabler for transforming hospital operations and improving healthcare delivery. However, the absence of healthcare-specific maturity models limits the systematic adoption of AI in clinical settings. This study addresses this gap by conducting a structured literature review of existing AI maturity models and critical success factors across domains. The analysis identifies six core dimensions: technology, data, strategy, people, organization, and regulations. These findings highlight the multifaceted nature of AI integration and underscore the need for a tailored approach in complex healthcare environments. By providing a conceptual foundation, this work advances the development of future AI maturity models to support healthcare leaders in assessing AI readiness, ensuring strategic alignment, and facilitating structured AI integration within hospital settings. Further empirical validation is needed to refine the framework for practical application.

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