Stakeholder Perspectives on Health System Readiness for Integrating Artificial Intelligence into Public Health in Saudi Arabia

Background/Objectives: Although artificial intelligence (AI) has the potential to strengthen disease surveillance, predictive analytics, preventive interventions, and population-level decision-making, its successful integration requires health systems to be adequately prepared across technical, workforce, governance, and organizational dimensions. Saudi Arabia’s rapid digital health transformation provides a unique national context for exploring these readiness conditions. This study explored stakeholder perceptions of conditions relevant to health system readiness for integrating AI into public health in Saudi Arabia, including perceived challenges, implementation requirements, and strategic opportunities. Methods: A qualitative descriptive study was conducted using semi-structured interviews with 32 participants, including healthcare professionals, health informatics experts, and policymakers or healthcare planning stakeholders in Saudi Arabia. Participants were purposively selected based on their relevant professional experience. Data were analyzed using Braun and Clarke’s six-phase reflexive thematic analysis. Results: Four major themes were identified: (1) infrastructure readiness, reflecting progress in digital health platforms alongside persistent interoperability and data-integration challenges; (2) workforce capacity, highlighting limited AI literacy and the need for practical, role-specific training; (3) data governance and ethics, emphasizing privacy, accountability, algorithmic bias, and the need for greater regulatory clarity; and (4) perceived strategic opportunities, including preventive care, population health monitoring, disease surveillance, and decision support. The first three themes reflected conditions perceived as relevant to health system readiness, whereas the fourth captured anticipated applications and potential benefits rather than a dimension of current readiness. Overall, participants perceived substantial national strategic commitment and digital health development while identifying important implementation challenges related to interoperability, workforce capability, governance, and regulation. Conclusions: Participants’ accounts suggest that responsible AI integration into public health requires coordinated attention to interoperable infrastructure, workforce competencies, governance mechanisms, regulatory oversight, and human-centered implementation. A phased implementation approach, supported by role-specific AI training and clear governance and regulatory frameworks, may help translate national AI ambitions into safe and effective public health practice. These findings may inform policy development, workforce planning, and implementation strategies for responsible AI integration in Saudi Arabia and other regions whose health systems are undergoing rapid digital transformation.