The digital evolution of hearing: a comprehensive review of artificial intelligence–powered cochlear implants and hearing aids

Abstract The integration of artificial intelligence (AI) into audiology is progressively transforming the diagnosis, assessment, and treatment of hearing loss. This review presents a structured narrative analysis of contemporary AI-powered hearing aids and cochlear implants, highlighting current applications, clinical implications, technical challenges, and future directions. Advances in AI-driven algorithms have evolved these devices into more efficient and user-centered systems designed to address individual listening needs while minimizing the limitations of traditional signal processing. Specifically, AI applications enhance the precision of hearing assessment, support the automation of fitting procedures, and enable the personalization of auditory rehabilitation programs. Where available, methodological details—such as sample size, training–validation strategies, and performance metrics—are considered to provide transparency. Recent developments have significantly improved real-time sound processing, resulting in clearer auditory perception, particularly in acoustically complex environments. Furthermore, personalized programming strategies and adaptive learning systems have been shown to streamline routine clinical workflows, enhance professional efficiency, and improve long-term user satisfaction. By synthesizing recent evidence, this review aims to provide clinicians and researchers with a comprehensive overview of the evolving role of artificial intelligence in modern audiological practice.