In thyroid surgery, preserving the recurrent laryngeal nerve is critical to prevent vocal cord dysfunction. Intraoperative nerve monitoring (IONM) has become a valuable adjunct to direct visual nerve identification, improving functional assessment and reducing the risk of nerve injury. With increasing surgical complexity and the growing availability of data, artificial intelligence (AI) is emerging as a powerful tool to complement IONM systems. AI enables real-time signal interpretation, predictive analytics, and improved decision-making through the use of machine learning and deep learning algorithms trained on large datasets of electromyographic signals. This integration not only holds the potential to improve patient outcomes but also lays the foundation for a new era of precision thyroid surgery. This article reviews the current applications, benefits, and limitations of AI-assisted IONM in thyroid surgery and highlights future directions for innovation and clinical applications.