MIT Technology Review0 Hot6 phút
Agriculture is ready for AI, but its data isn’t
AI adoption in agriculture is hindered not by technology but by poor data foundations. Predictive models can improve crop yields by 26% and reduce water use by 41%, but only when built on clean, consistent, and governed data. Agricultural operations face unique data challenges including fragmented IoT sensor data, complex land-level attributes, and compliance requirements. Data readiness requires a unified data model connecting customers, suppliers, products, and pricing, along with fast pipelines and ongoing governance. Reltio, an SAP company, is presented as a solution for unifying fragmented enterprise data to enable trustworthy AI outputs.