Advancing laryngology through artificial intelligence: a comprehensive review of implementation frameworks and strategies.

Abstract

Purpose of review: This review aims to explore the integration of artificial intelligence (AI) in laryngology, with specific focus on the barriers preventing translation from pilot studies into routine clinical practice and strategies for successful implementation.

Recent findings: Laryngology has seen an increasing number of pilot and proof-of-concept studies demonstrating AI's ability to enhance diagnostics, treatment planning, and patient outcomes. Despite these advancements, few tools have been successfully adopted in clinical settings. Effective implementation requires the application of established implementation science frameworks early in the design phase. Additional factors required for the successful integration of AI applications include addressing specific clinical needs, fostering diverse and interdisciplinary teams, and ensuring scalability without compromising model performance. Governance, epistemic, and ethical considerations must also be continuously incorporated throughout the project lifecycle to ensure the safe, responsible, and equitable use of AI technologies.

Summary: While AI hold significant promise for advancing laryngology, its implementation in clinical practice remains limited. Achieving meaningful integration will require a shift toward practical solutions that prioritize clinicians' and patients' needs, usability, sustainability, and alignment with clinical workflows.