A new artificial intelligence model demonstrates a 94.3% accuracy rate in predicting risks of complications following surgery, based on analysis of Greek hospital data. The study, led by researchers at the University of Patras and published in *Applied Sciences*, examined records from nearly 20,000 patients. This high level of accuracy suggests the potential for earlier identification of patients at risk, allowing for proactive intervention and improved patient safety. The AI was trained on existing hospital records, indicating a feasible path for implementation within current healthcare systems. Researchers believe this technology could significantly enhance surgical unit preparedness and optimize patient care. The findings highlight the growing role of AI in improving healthcare outcomes and risk management. Further research will focus on expanding the model’s capabilities and validating its performance across diverse patient populations.