AI is changing agriculture, but “we use AI” is not a protectable moat. For ag-tech founders, the real value usually sits in the datasets, labelled training data, model improvement loop, software, trade secrets, and contracts that govern how farm data can be used. This article breaks down what is actually protectable in AI decision tools — and what founders need to lock down before pilots, partnerships, or scaling expose the business.

Biosecurity surveillance is emerging as a major ag-tech growth area, driven by the need for early detection of pests and disease. This article explains how automated monitoring systems work, why trust and data accuracy are critical, and what IP strategies—patents, trade secrets, and data rights—are essential to protect and scale detection technologies.