In the context of hand surgery, artificial intelligence (AI) encompasses computer vision, large language models (LLMs), machine learning (ML), and robotics. While computer vision achieves human-comparable accuracy in fracture detection and LLMs streamline “ambient” documentation, clinical implementation remains limited. ML offers predictive power but is currently hampered by the “black box” nature of its algorithms and a lack of external validation. These are combined into robotic platforms with the potential to transform upper extremity prosthetics. Combining these advances with human oversight seems the most likely path for safe and effective implementation of AI in clinical practice.