This chapter explores the evolving landscape of artificial intelligence applications in Long COVID fatigue research and clinical management. Through an examination of current research challenges, emerging technologies, and future directions, it highlights how AI is transforming our understanding and treatment of this complex condition. The discussion begins with an analysis of the multifaceted nature of Long COVID fatigue, including its varied presentations and the challenges in standardizing research approaches. The chapter then delves into specific AI applications, from advanced machine learning algorithms for analyzing neuroimaging data to integrated monitoring systems for clinical care. Notable developments include AI-driven fatigue prediction models achieving 84% accuracy and monitoring systems that can detect fatigue episodes 12–24 hours before onset. The text also examines implementation challenges in clinical settings, including cost considerations, healthcare equity, and the need for standardized protocols. Looking toward the future, the chapter explores emerging technologies such as quantum computing, neural interfaces, and nanoscale sensors, while addressing critical ethical considerations in AI-driven healthcare. Throughout, the chapter emphasizes the delicate balance required between technological advancement and practical clinical utility, highlighting both the transformative potential of AI and the importance of maintaining patient-centered care approaches.