Background: Healthcare systems increasingly face pressure to improve population health outcomes while controlling costs, addressing the burden of chronic disease, and advancing health equity. Simultaneously, rapid advances in artificial intelligence (AI), including machine learning, predictive analytics, natural language processing, and generative AI, have created new opportunities to support population health management. Although numerous studies have examined specific AI applications, healthcare organizations continue to face challenges integrating AI into comprehensive population health strategies.

Objective: This article proposes a strategic framework to guide healthcare organizations in leveraging artificial intelligence to improve population health outcomes while supporting organizational performance and health equity goals.

Methods: Drawing on literature in population health management, artificial intelligence, healthcare leadership, complex adaptive systems theory, learning health systems, and strategic management, a conceptual framework was developed to identify the organizational capabilities required for effective AI-enabled population health management.

Results: The proposed framework conceptualizes AI as a strategic organizational capability rather than a standalone technology. The framework consists of six interrelated domains: (1) data infrastructure and integration, (2) predictive intelligence, (3) population health intervention design, (4) health equity and social determinants, (5) governance and ethical oversight, and (6) continuous learning and improvement. Collectively, these domains provide a roadmap for healthcare organizations seeking to translate AI capabilities into improved health outcomes, enhanced population health management, reduced disparities, and sustainable organizational performance. The framework further identifies critical leadership responsibilities, governance mechanisms, and workforce competencies necessary for successful implementation.

Conclusions: Artificial intelligence has the potential to transform population health management by enabling proactive, data-driven, and equitable interventions. However, realizing this potential requires more than technological adoption. Healthcare organizations must develop strategic capabilities that integrate advanced analytics, organizational learning, ethical governance, and cross-sector collaboration. The proposed framework advances theory by conceptualizing AI as a dynamic organizational capability, contributes to practice by offering a structured implementation roadmap, and informs policy discussions regarding responsible and equitable AI adoption in population health systems.