Purpose: Thyroid cancer is the seventh most common cancer worldwide. Radioactive Iodine ablation (RAI) is a common adjunct treatment post thyroidectomy for intermediate and high-risk differentiated thyroid malignancy. Multidisciplinary team (MDT) meetings play an essential role in thyroid cancer management; however, they can be time-consuming and expensive. Artificial Intelligence (AI) is becoming increasingly used in medical research and treatment, and may play a role in streamlining the MDT process. The aim of this study was to compare recommendations for RAI from MDT discussions and ChatGPT AI analyses. Methodology: A retrospective review of all cases discussed between 2019 to 2024 at a Tertiary centre Endocrine MDT in Sydney, Australia was performed. Only index thyroidectomy cases performed in the public hospitals with MDT discussion regarding RAI were selected for the study. Variables collected included age, gender, AJCC TNM stage, extrathyroidal invasion and decision regarding RAI (RAI, no RAI, or discuss). Histopathological reports of the selected cases were fed to the free online version of ChatGPT and the question whether RAI was recommended was asked. Statistical analyses were conducted in SPSS software. Results: Of 490 MDT cases during the study period, 122 cases were selected for the study. Mean age was 49 years (SD 16 years). A total of 96 cases (78.7%) had concordance between MDT consensus and ChatGPT recommendation with a Cohen’s Kappa value of 0.513. Conclusion: There was moderate agreement as per Cohen’s Kappa analysis between the MDT consensus and ChatGPT recommendation. Therefore, ChatGPT provides a promising tool that can be incorporated in the decision making of post operative thyroid cancer treatment with respect to RAI.