Agriculture is drowning in data that can barely be used, according to a report by the Council for Agricultural Science and Technology (CAS). The report suggests that agriculture's data is fragmented, distributed, heterogeneous, and incompatible, and this explains why AI has struggled to gain traction on farms. Unlike other data-heavy industries like healthcare or financial services, agriculture lacks a universal framework for translating between multiple systems generating field-level information. The report also highlights the need for an infrastructure that understands what this data means. According to a McKinsey report, implementing data integration and connectivity in agriculture could add $500 billion in value to global GDP, a 7 to 9% improvement over current projections.