AI in Agriculture is applied in two distinct areas. The first is field operations: evaluating images from drones and satellites to monitor crop condition, early detection of diseases and pests from photographs, yield prediction, and optimising the dosing of fertilisers and sprays according to variability across the plot. The benefit shows up in input consumption, which is the largest cost item. The second area is administration, of which there is a disproportionate amount in the sector – records for the paying agency, materials for the single application, tracking deadlines and processing documentation for subsidies. In both cases, the condition is digital record-keeping of plots and interventions; without it, there is nothing to work with. Part of the investment tends to be supported through project schemes.
See also: Grants for Farmers, AI use case, Grant for Company Digitalisation.
