Artificial intelligence in microbial biotechnology for food security: current state and challenges
11 October 2026 · Microbial Metabolic Engineering and Bioproduction · Artificial Intelligence Applications · Smart Agriculture and AI
AI applications in microbial biotechnology could support food security, but weak data, opaque models and high costs limit their use. The review assessed machine learning and deep learning for classifying microbes, modelling metabolism, designing microbial production systems, finding biofertilisers and biological controls, and improving CRISPR-based precision fermentation. It also covered searches for microbes that benefit soil health. The authors identify adoption, model interpretation, ethics, computing demands and absent standards as further barriers. Progress depends on solving these practical and ethical problems.