<![CDATA[Purpose – The purpose of this paper is to propose a novel theoretical framework that explores the integration of Artificial Intelligence (AI) into the medical tourism sector, with the aim of enhancing healthcare accessibility, efficiency, and patient satisfaction. The framework is designed to address the challenges faced by medical tourism destinations, such as high treatment costs, accessibility issues, and operational inefficiencies. Design/methodology/approach – This study employs a conceptual methodology, combining a comprehensive review of current AI applications in healthcare and the development of a new framework tailored to medical tourism. The framework integrates AI-driven predictive analytics, virtual health assistants, and personalized treatment algorithms. Furthermore, a mathematical model is proposed to substantiate the framework, demonstrating its impact on key performance indicators (KPIs) in medical tourism. Findings – The paper finds that AI can significantly improve operational efficiency, reduce treatment costs, enhance patient satisfaction, and increase the competitiveness of medical tourism destinations. The proposed framework shows how AI can address critical challenges such as language barriers, healthcare quality discrepancies, and patient navigation difficulties. Practical implications – The findings suggest that healthcare providers and policymakers in medical tourism destinations can leverage AI technologies to improve service delivery, attract more international patients, and foster economic growth in the sector. The study provides actionable recommendations for the adoption of AI in medical tourism, which could lead to a more efficient, affordable, and patient-friendly healthcare experience. Originality/value – This paper offers a novel theoretical framework that integrates AI into the medical tourism industry, which has not been sufficiently explored in existing literature. The proposed model contributes to a better understanding of how AI can enhance the quality, accessibility, and efficiency of healthcare services for international patients.]]>
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