From Chatbots to Digital Teammates: How AI Agents Fit Into Agribusiness
Editor’s note: In a recent issue of Upstream Ag Professional, agribusiness analyst Shane Thomas says for AI agents to become valuable in agribusiness, they should become part of core workflow — with ERPs or control point systems, or develop a new workflow. Here’s a summary of that article:
There’s transformative potential of Large Language Model (LLM) agents in agriculture, focusing on how they could reshape workflows and enhance decision-making for professionals in agribusiness. LLM agents are advanced AI systems that use large language models to perform tasks autonomously, moving beyond traditional text generation to handle interactions, reasoning, and some level of independent action. These agents can be tailored for specific industries like agriculture — referred to as “vertical agents” — to better understand and respond to the unique challenges, language, and data specific to that sector.
The concept of an “OODA loop” (Observe, Orient, Decide, Act), initially developed for military strategy, illustrates how these agents can continuously process information to support goal-oriented tasks in a rapidly evolving environment. Vertical LLM agents in agriculture could streamline tasks like marketing, customer relationship management (CRM), and product research. For instance, agents could help agronomists identify and reach out to farmers with specific soil needs, draft customized marketing messages, or automate CRM data collection. Such capabilities could save agronomists and sales professionals valuable time by automating repetitive tasks and minimizing manual data entry.
I also want to highlight the importance of “control points” in software — centralized systems where key business actions are executed. For agribusiness, these control points are typically transactional and financial software rather than agronomic software. Integrating LLM agents within these control points would transform them from static systems of record to dynamic systems of intelligence, enabling real-time decision-making and improved workflow efficiency.
MORE BY SHANE THOMAS
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Looking ahead, while a full shift to AI-driven workflows in agriculture may not happen immediately, the rise of LLM agents offers a promising solution to labor challenges in rural areas. As AI agents become more sophisticated and integrated, they are expected to become essential tools for professionals in agriculture, enhancing productivity and decision-making across agribusinesses.
For more in-depth coverage, visit Upstream Ag.
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