Systematic Review: Policy Gaps in AI-Driven Medical Education in Saudi Arabia: Bridging the Divide for Vision 2030

Abstract

Introduction:  Artificial Intelligence (AI) has emerged as a transformative force in medical education, offering new pathways for advancing healthcare systems worldwide. In Saudi Arabia, this transformation aligns with Vision 2030, which emphasizes innovation and digitalization across education and healthcare sectors.

Objectives: This review aims to assess Saudi Arabia’s readiness for integrating AI into medical education by identifying key policy gaps and strategic interventions.

Methods: A thematic synthesis of 20 peer-reviewed studies published between 2018 and 2024 was conducted. Studies were selected based on relevance to AI readiness in medical education, and analyzed to extract common challenges and policy inconsistencies across Saudi institutions.

Results: Four primary policy gaps were identified: strategic, regulatory, instructional, and financial. The findings revealed significant institutional variability in AI readiness, driven by fragmented policies, underdeveloped governance frameworks, lack of faculty training, and insufficient resource allocation. These barriers collectively hinder national efforts toward AI integration in medical education.

Conclusions: To realize the potential of AI within the framework of Vision 2030, a unified, multi-stakeholder policy approach is imperative. Strategic actions—including curriculum standardization, faculty upskilling, policy coherence, and sustained investment are essential to create an AI-ready medical education system in Saudi Arabia.