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Rethinking digital inclusion: User agency in agri-advisory design and delivery

Digital technologies are rapidly reshaping how actors across agrifood value chains access information and market and financial services and how organizations govern resources and respond to shocks.

Woman standing in agricultural field looking at smartphone. Bucket to left. Man, right rear, bent over working.
  • Artificial Intelligence
  • advisory services

By Eliot Jones-Garcia, Niyati Singaraju, Kristin Davis, and Cambria FinegoldAugust 14, 2026

Key takeaways

 

  • Digital inclusion for agricultural advisory tools requires more than access and usability. Farmers should also have agency to shape how technologies are designed and used.
  • Farmers are active innovators, not passive users. Their knowledge, feedback, and adaptations are essential for making digital tools relevant and effective.
  • Low adoption is a predictable outcome of poor design. Digital tools work best when they reflect farmers’ needs, priorities, and local realities.

Digital technologies are rapidly reshaping how actors across agrifood value chains access information and market and financial services and how organizations govern resources and respond to shocks. Generative AI advisory tools, for example, promise to provide farmers with personalized information at any time and at relatively low cost. However, such applications also risk reproducing or exacerbating existing inequalities, leaving some actors, including women and other marginalized groups, excluded or exposed to new forms of harm.

In response, digital inclusion has emerged as a field of research and practice concerned with ensuring that the design, deployment, and maintenance of digital technologies are fair, equitable, and socially responsive. Digital inclusion is typically seen as an outcome of technology design, most commonly framed in terms of accessibility and usability.

Yet this approach, while necessary, often overlooks the aspects of how digital technologies are actually adopted, adapted, or resisted in practice. A farmer may be able to access an AI advisory tool and understand its recommendations, for example, without having any influence over its capabilities to address specific problems, the knowledge or data on which it draws, or the forms of farming it promotes.

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