THE ROLE OF ARTIFICIAL INTELLIGENCE IN PERSONALISED MEDICINE: ADVANCEMENTS, CHALLENGES, AND FUTURE PERSPECTIVES

Ioana-Marcela Pä‚curaru (), Ciprian-Sorin Chirvase () and Åžtefan-Ioan Tiriteu ()
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Ioana-Marcela Pä‚curaru: Bucharest University of Economic Studies, Bucharest, Romania
Ciprian-Sorin Chirvase: Bucharest University of Economic Studies, Bucharest, Romania
Åžtefan-Ioan Tiriteu: Bucharest University of Economic Studies, Bucharest, Romania

Business Excellence and Management, 2025, vol. 15, issue 1, 59-84

Abstract: Artificial Intelligence (AI) has emerged as a transformative technology in healthcare, significantly advancing personalised medicine. By leveraging vast amounts of data, AI enhances early disease detection, tailors treatments to individual patients, and optimises medical resource management. Despite these advantages, the integration of AI in healthcare presents challenges, including concerns over data privacy, acceptance among healthcare professionals, and the need for comprehensive regulatory frameworks. Therefore, this study investigates the impact of AI on personalised medicine, assessing its benefits, limitations, and real-world applications. It explores AI’s role in diagnostics, personalised treatment strategies, and the optimisation of medical workflows, while critically examining ethical and legal challenges. The study also underscores the necessity of robust regulations to ensure responsible and ethical AI deployment in healthcare. A systematic documentary analysis of scientific articles, case studies, and healthcare organisation reports forms the basis of this research. Case studies from hospitals and companies that have successfully implemented AI are analysed to evaluate its impact on diagnostic accuracy, treatment efficiency, and medical costs. The findings are correlated with existing literature to provide a comprehensive perspective on current and future trends in AI-driven personalised medicine. The results of this study show that AI has demonstrated significant improvements in diagnostic precision, reduced the time required for disease identification, and enhanced the effectiveness of personalised treatment plans. Studies indicate that AI-driven approaches contribute to cost reductions by minimising late-stage treatments and enabling more efficient allocation of medical resources. However, critical challenges such as algorithm transparency, bias mitigation, and patient data security continue to hinder widespread AI adoption in healthcare.

Keywords: Artificial intelligence; AI in healthcare; Data privacy; Healthcare technology; Personalised medicine (search for similar items in EconPapers)
Date: 2025
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