<p>Laryngeal cancer is a malignancy of the vocal cords and surrounding tissues and creates considerable distress because it interferes with vital functions such as breathing, talking, and swallowing. Early detection and diagnosis play an important role in improving patient outcomes. Existing methods of testing, imaging, and histopathological examination of the tissues still face major challenges in early cancer detection and defining intricate tumor characteristics. With the increasing importance of Artificial Intelligence (AI) in oncology, it holds transformational capabilities that can revolutionize diagnosis and personalized treatment. This research paper presents the latest advances in AI applications in comprehensive data ranges such as videomics, voice analysis, radiomics, genomics, and clinical examination and assesses them against laryngeal cancer management. By application through Machine Learning (ML) and Deep Learning (DL) algorithms, the AI can analyze complex datasets to understand subtle patterns and clinical outcome predictions with unprecedented accuracy. AI-driven methodologies are promising to identify early-stage cases and provide personalized treatment management. Meanwhile, diverse data collection, robust multimodal data integration, and efficient clinical applicability remain challenges. This analysis collates the important results found within the current literature and identifies crucial research gaps and additional aspects for the future development of improved AI-based diagnosis and prognosis. Merging the bifurcation between conventional medical practices and computational advancements, this study highlights AI’s role in optimizing prognosis and survival for patients suffering from laryngeal cancer. The result indicates how promising AI would be in determining oncology’s future and patient care level.</p>