6 Ways to Use GenAI in Agronomy and Ag Retail
Editor’s note: In a recent issue of Upstream Ag Professional, agribusiness analyst Shane Thomas delves into why the key is not just adopting AI, but applying it in a way that solves specific constraints and augments real agronomic expertise. Here’s a summary of that article:
The integration of Generative AI (GenAI) presents a significant opportunity for agronomists to enhance efficiency, deepen agronomic knowledge, and improve customer engagement, even with limited budgets. While enterprise-level AI solutions receive much attention, many agronomists can leverage cost-effective tools to optimize their workflow.
1. Deep Research Tools for Agronomic Learning
Agronomists must stay updated on active ingredients, fertilizer formulations, and agronomic practices. GenAI-powered research tools, such as ChatGPT’s Deep Research and Perplexity AI, can streamline this process by aggregating, summarizing, and analyzing research. These tools help compare findings and contextualize information, though they should complement—not replace—traditional journal reading.
2. Custom GPTs for Agronomic Data
By structuring crop protection data, agronomists can create AI-driven knowledge bases for quick reference. A tailored GPT can compile state/provincial crop protection guides, historical efficacy data, and trial results. This would allow agronomists to analyze product performance across different environments, aiding in informed recommendations.
MORE BY SHANE THOMAS
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3. AI-Assisted Customer Communication
Regular customer interactions build trust and engagement. AI can assist in generating personalized agronomic newsletters, reducing the time required to draft content. By inputting key bullet points, AI can structure updates tailored to specific regions or customer needs, making communication more efficient.
4. AI-Driven CRM Voice Systems
Logging customer interactions in CRM systems is valuable but time-consuming. AI-powered tools like “CRM Caller Buddy” allow agronomists to dictate follow-up details, which AI transcribes and organizes. Further integration with AI agents like Lindy.ai could assist in task management, such as generating crop plans or notifying teams about product orders.
5. Personalized Sales & Marketing Assets
AI enables precision marketing by creating customized sales materials tailored to each farmer’s operation. By leveraging AI-generated insights and integrating them into branded templates, agronomists can deliver highly relevant recommendations, improving engagement.
6. AI-Enhanced Fertility Recommendations
AI can streamline fertility planning by analyzing soil test results and generating baseline recommendations based on an agronomist’s unique approach. Hiring AI developers through platforms like Upwork could help customize such a system.
GenAI isn’t replacing agronomists — it’s enhancing their expertise. By strategically leveraging AI for research, customer engagement, CRM management, and personalized sales, agronomists can gain an information advantage, improve decision-making, and deliver superior service — all within a minimal budget.
For more in-depth coverage, visit Upstream Ag.
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