Background: The rapid evolution of Artificial Intelligence (AI), is catalyzing a paradigm shift in modern medicine. Otolaryngology, being a data-intensive specialty reliant on complex imaging, acoustics, and endoscopic evaluations, stands at the forefront of this digital transformation. 

Objectives: This presentation aims to explore the multifaceted applications of AI in healthcare in general and in the ENT field, evaluating how these technologies enhance diagnostic precision, surgical planning, and personalized patient care.

Key Applications:

• Healthcare : triage , diagnosis , hospital management and insurance
• Otology- Audiology: AI-driven automated audiometry for the classification of middle ear pathologies from otoscopic images.
• Rhinology: Advanced CT/MRI image segmentation for chronic rhinosinusitis and AI-integrated surgical navigation systems for skull base procedures.
• Laryngology & Oncology: Voice signal analysis for detecting vocal fold paralysis and the use of Convolutional Neural Networks (CNNs) for the early detection of laryngeal malignancies via endoscopy.
• Robotics: The integration of AI in Transoral Robotic Surgery (TORS) to improve haptic feedback and precision.

Conclusion: While AI offers unprecedented opportunities to reduce human error and provider burnout, challenges such as data privacy, algorithmic bias, and the "black box" nature of DL must be addressed. Integrating AI as a "decision-support tool" rather than a replacement for clinical judgment is essential for the future of ENT.  

TBA