Artificial Intelligence, Assessment Integrity, and Professionalism in Medical Education: Global Disruption and Lessons from the Gulf Cooperation Council Region

Abstract

Artificial intelligence (AI), particularly generative AI, is rapidly reshaping medical education worldwide. While AI-enabled tools offer significant opportunities for personalized learning, feedback automation, and clinical reasoning support, they simultaneously challenge foundational principles of assessment integrity and professional conduct. Traditional assessment models—largely predicated on individual authorship, knowledge recall, and observable performance are increasingly strained by AI systems capable of generating sophisticated responses, analyses, and clinical narratives. This disruption has prompted urgent reconsideration of what constitutes academic honesty, valid assessment, and professional identity formation in contemporary medical training. This article critically examines the intersection of AI, assessment integrity, and professionalism in medical education from a global perspective, with particular attention to the experiences and emerging lessons from the Gulf Cooperation Council (GCC). The GCC provides a distinctive context characterized by rapid digital transformation, centralized accreditation and licensing systems, high-stakes assessments, and strong sociocultural norms governing professional behavior. These features make the region an instructive case for understanding how medical education systems respond to AI-driven challenges at scale. Drawing on international literature, policy documents, and regional practices, this paper argues that AI should be understood not merely as a technological tool but as a normative disruptor that compels a re-examination of assessment validity, ethical responsibility, and professional identity. The article proposes a shift from reactive prohibition toward principled integration of AI within assessment and professionalism frameworks. It concludes by outlining future-oriented recommendations for educators, institutions, and regulators aimed at preserving trust, fairness, and professional standards in an AI-augmented educational landscape.

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