Assessing Readiness for Artificial Intelligence-Enabled Personalized Medicine: A State-of-the-Art Review of Organizational Maturity Assessment Across Academic, Community, and Safety Net Health Systems

Background/Objectives: Unequal organizational resource levels may present obstacles to accessing AI-assisted personalized medicine. The goal of this state-of-the-art literature review is to examine how current readiness and maturity assessments address academic, community, and safety net healthcare settings, and to identify gaps, enabling us to provide a basis for further development of new frameworks. Methods: A search of four major databases (PubMed; Scopus; Web of Science; CINAHL) was performed. In addition, a supplementary targeted search approach was employed to locate relevant assessment materials and previous foundational work. Our synthesis included an examination of the development, measurement, settings, and accessibility of assessments. Results: There were 97 reports in the final inventory of eligible reports. Our findings supported local planning more clearly than comparisons of scores across academic, community and safety net healthcare systems or predictions of personalized-care outcomes. We also identified eight areas for research priority: clinical pathway relevance, representation, institutional context, shared capabilities, organizational measurement, scoring and safety, comparative and outcome validation, and practical access. Conclusions: Further comparative studies are needed to evaluate how well the current assessments assist in decision-making regarding AI-assisted personalized medicine in different healthcare settings. This review serves as both a gap register and research agenda to initiate the process toward developing future maturity frameworks.