For generations, the invisible threat of mycotoxins—mold-born poisons lurking in grains and crops—has tested the limits of food safety science, demanding slow, costly, and imperfect vigilance. Now, artificial intelligence is stepping into that gap, not merely as a faster tool but as a fundamentally different kind of watchfulness: one that detects contamination with over 90% accuracy, forecasts risk before it materializes, and guides intervention with precision that conventional methods could not approach. This convergence of machine learning, biological data, and predictive modeling represents