Powering the food industry with AI

But despite this promise, industry adoption still lags. Data-sharing remains limited and companies across the value chain have vastly different needs and capabilities. There are also few standards and data governance protocols in place, and more talent and skills are needed to keep pace with the technological wave. All the same, progress is being made and the potential for AI in the food sector is huge. Key findings from the report are as follows: Predictive analytics are accelerating R&D cycles in crop and food science. AI reduces the time and resources needed to experiment with new food products and turns traditional trial-and-error cycles into more efficient data-driven discoveries. Advanced models and simulations enable scientists to explore natural ingredients and processes by simulating thousands of conditions, configurations, and genetic variations until they crack the right combination. AI is bringing data-driven insights to a fragmented supply chain. AI can revolutionize th ... Read full article.