A review published in Trends in Food Science & Technology has assessed how artificial intelligence is being applied across the alternative protein value chain, concluding that the technology delivers the most reliable results when used to guide specific decisions rather than to automate development end-to-end. The paper covers plant-based, fermentation-derived, insect, and cultivated protein systems, examining AI applications from upstream discovery through midstream manufacturing to downstream formulation, nutrition, safety, and consumer analysis. Its authors frame alternative proteins not as single ingredients but as coupled food systems, where composition, structure, processing conditions, and final product performance interact and shape one another. The review argues that these tightly linked relationships make empirical trial-and-error slow, costly, and hard to transfer between raw materials, processes, and production scales. In each case, AI narrows options or extracts patterns from high-dimensional data rather than replacing laboratory work.