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AI, copyright, and content licensing in digital agriculture

In this post, we examine that challenge and propose a solution to enable a rapprochement between content producers and data-hungry AI developers: content licensing agreements.

AI-generated image showing hand holding smartphone in front of agricultural field, with icons for various apps superimposed
  • Artificial Intelligence
  • copyright
  • licenses

By Ameen JauharJanuary 22, 2026

The large language models (LLMs) that power most artificial intelligence chatbots and other applications are exponentially more massive than those of earlier systems, relying on vast datasets and billions of parameters to produce their human-like outputs. Such scale is often celebrated as the driver of their cutting-edge capabilities. But scale alone does not guarantee sound results. The reliability (i.e., robustness, accuracy, and trustworthiness) of such systems significantly hinges on the quality and contextual relevance of LLM datasets. In short, not only quantity, but quality of available data for building gen AI models, is critical.

This is a major issue as AI systems expand their footprint across varied industries around the world—with particular implications for AI in agriculture, which has emerged as a priority sector, specifically for generative AI. For example, the African Union Continental AI Strategy, adopted in 2024, aims to leverage AI tools in pursuing its Agenda 2063 development plan and the Sustainable Development Goals (SDGs). Domestic policy documents in multiple African, South Asian, and Latin American countries attest to widespread commitments to use AI to speed agricultural modernization.

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