Artificial Intelligence in Laryngology: Applications for Voice, Swallowing, and Endoscopic Assessment

Artificial intelligence (AI) is increasingly integrated into otolaryngology-head and neck care, with rapid growth in laryngology due to its reliance on voice analysis, endoscopic imaging, and swallowing assessment. As AI tools move into routine practice, otolaryngology teams play a key role in ensuring ethical, effective, and patient-centered implementation.

To describe current and emerging applications of AI in laryngology with direct relevance to otolaryngology-head and neck care.

A narrative review of the peer-reviewed literature was conducted, focusing on clinically relevant and investigational AI applications in laryngology care. Areas of emphasis included voice disorders and dysphagia, with attention to nursing, speech language pathology, and surgical practice.

AI applications in laryngology care span multiple domains, including automated voice analysis for screening and monitoring, AI-assisted interpretation of laryngoscopy and swallowing studies, noninvasive dysphagia screening using sound or wearable sensors, and tools to support documentation and clinical triage. Collectively, these technologies can improve diagnostic consistency, support earlier identification of complications, and enhance longitudinal monitoring across care settings.

Effective integration of AI into laryngeal care requires coordinated team engagement in data analysis, patient education, and clinical decision support. Understanding AI capabilities and limitations is essential for improving care while mitigating bias and supporting efficient workflows.

AI-enabled technologies have expanded data-driven laryngology care across voice, swallowing, and endoscopic evaluation. Successful adoption depends on data quality, performance, and workflow integration. Interdisciplinary collaboration and ongoing evaluation of safety and equity can enhance the quality and consistency of laryngeal care.