Artificial Intelligence Integration in Telemedicine: A Methodological Study on Challenges and Opportunities in Libya

Abstract

AI-enabled telemedicine offers substantial potential to improve healthcare access for remote and underserved populations; however, its implementation remains constrained by technical, ethical, and operational challenges. This study addresses the research gap concerning inadequate data-protection mechanisms, infrastructure limitations, algorithmic bias, and low user acceptance within current telemedicine systems. A systematic analytical review of 15 peer-reviewed studies was conducted to evaluate the reliability, scalability of integrating artificial intelligence into remote healthcare delivery as well as safety are both factors. The findings show that existing platforms lack sufficient safeguards to ensure secure and fair data use, while regulatory and infrastructural barriers significantly reduce the effectiveness of AI-supported diagnostic and monitoring functions. The study highlights the need for a structured framework that guides policymakers, system developers, and healthcare providers in achieving ethical, resilient, and scalable AI adoption, thereby promoting more equitable healthcare access in geographically distant settings