Artificial intelligence (AI) is increasingly integrated into modern otolaryngology practice and has emerged as one of the most rapidly evolving technologies in contemporary medicine. Recent advances in machine learning, deep learning, computer vision, and multimodal AI systems have accelerated the development of diagnostic and therapeutic applications across multiple otolaryngology subspecialties.
✦ The floor
Discussion
Signed responses from readers of the wire.
No actionable change — this is a narrative review of AI in otolaryngology broadly; audiologists should monitor the space but current evidence does not support altering clinical workflows based on this article alone.
As AI tools begin entering audiology and ENT practice, a current synthesis of capabilities and limitations helps clinicians and researchers calibrate realistic expectations and identify gaps for future study.
- 01Review surveys AI applications across otolaryngology, including audiology-adjacent areas.
- 02Current limitations of AI in ENT (e.g., data quality, generalizability, regulatory gaps) are addressed.
- 03Future directions and research priorities for AI in the field are outlined.
- 04Published ahead of print in European Archives of Oto-Rhino-Laryngology (2026).
- 05No primary data are presented; conclusions are based on existing literature.
AI has current clinical applications in otolaryngology practice.
opinionpartially supportedAI in otolaryngology faces significant limitations including generalizability and regulatory challenges.
opinionsupported- PMID
- 42745060
- DOI
- 10.1007/s00405-026-10560-x.
- Journal
- European Archives of Oto-Rhino-Laryngology
- Publication type
- review
- Evidence level
- 5
- Population
- Literature on AI applications in otolaryngology
- Intervention
- Survey of artificial intelligence methods applied in otolaryngology
Primary outcomes
Current AI applications in otolaryngology; Identified limitations of AI in clinical ENT practice; Future perspectives and research directions