A systematic review of 161 peer-reviewed publications found that AI research in food safety has expanded rapidly, rising from one study in 2012 to 46 in 2023. The review shows that machine learning and deep learning are being studied for pathogen detection, chemical contamination prediction, food fraud screening, outbreak surveillance, and regulatory decision-making, but data gaps, class imbalance, privacy limits, and model interpretability remain major barriers.