A blueprint for transformation: strategic planning, evaluation, and implementation of artificial intelligence in hospital settings—a narrative review

Background and Objective: The integration of artificial intelligence (AI) into hospital settings offers a transformative opportunity to improve clinical decision-making, operational performance, and patient outcomes. Yet, many health systems struggle to move AI initiatives beyond tactical pilots, owing to gaps in strategic alignment, governance, and organisational readiness. For healthcare executives, the central challenge is not the availability of AI solutions but the capacity to implement them safely, ethically, and at scale within a complex clinical ecosystem. This practice-oriented narrative review aims to provide healthcare administrators and executive leaders with a structured blueprint for navigating the organisational, clinical, and governance challenges of deploying AI-assisted tools.

Methods: We conducted a narrative review with framework synthesis. Peer-reviewed literature was identified through targeted searches of PubMed, Scopus, and Embase (January 2014 to February 2026), limited to English-language publications, and supplemented with selected grey literature describing established maturity and risk frameworks. Sources were synthesised narratively against five predefined blueprint domains.

Key Content and Findings: The blueprint addresses five domains: strategic planning and readiness assessment; governance and ethical oversight; technical infrastructure and data management; clinical integration and workflow optimisation; and continuous evaluation and improvement. Drawing on established frameworks, implementation experience, and empirical evidence, we offer actionable recommendations, including establishing clear governance structures, aligning AI use cases with organisational strategy, managing clinical and operational risk, preparing and engaging the workforce, and measuring value over time.

Conclusion: This review consolidates dispersed guidance into a single executive-facing framework that leaders can adapt to develop context-specific AI strategies aligned with organisational values, patient safety, and measurable improvements in care. It may inform future implementation research, executive practice, and health policy on safe, scalable AI adoption.