6 Ways Fruit Growers Can Leverage AI Right Now

Artificial intelligence is not some distant Silicon Valley experiment, according to Walt Duflock. It is already reshaping how growers make decisions, manage risk, and plan for the next generation, the Senior Vice President of Innovation with Western Growers said at the International Fruit Tree Association (IFTA) conference in Fresno, CA.

Duflock, a fifth-generation farmer with three decades in tech, connected today’s orchard pressures, including rising labor and regulatory costs, oversupply in key crops, and shrinking margins, with the practical ways AI can help growers respond right now. His message was not about shiny gadgets but about using AI as a thinking partner to make better decisions faster.

To make the ideas actionable, Duflock broke his approach down into six key ways growers can leverage AI today, each tied to practical decision making in the orchard.

1. Pick One AI Tool and Go Deep

Duflock’s first rule is simple: Choose a single AI tool and stick with it. He selected ChatGPT over two years ago and emphasizes depth over variety. Constant use builds familiarity, sharpens your questions, and creates a personal history of prompts, projects, and data.

For fruit growers, that could mean:

• Drafting emails to lenders, shippers, or partners
• Summarizing market reports or research articles
• Turning meeting notes or field day presentations into internal memos

The key is to build fluency in one system rather than bouncing between apps.

2. Feed It Real-World Data

AI is only as useful as the information it has. Duflock feeds USDA census data, CDFA reports, spreadsheets, and Word documents into his AI. The goal is context, not generic answers.

Growers can use:

• Historical yields by block or variety
• Cost of production spreadsheets
• Pest pressure or spray logs
• Packout and quality reports

Instead of asking, “What should I plant?” ask, “Given 10 years of yields and prices, which scenarios look strongest for the next decade?” AI frames options clearly without replacing judgment.

3. Bring Your Whole Operation into the Model

Duflock urges growers to include agronomic, financial, and operational data. This could include:

• Soil tests, tissue analyses, and irrigation records
• Labor hours by task
• Input usage and block performance
• Replant history

With this data, AI can help answer questions such as:

• Which blocks are underperforming after all costs?
• Which labor-saving investments actually pay off?
• How do pruning or training systems affect long-term economics?

The goal is not a perfect digital twin, but a problem-solving environment built from scattered data.

4. Organize AI Work Like Your Farm

Duflock structures AI around topics, creating folders or threads for labor economics, regulatory costs, or export competitiveness. Growers can mirror this approach with workspaces for:

• Variety and block planning
• Labor and H-2A modeling
• Water and irrigation
• Capital projects and equipment ROI

This structure makes it easy to return months later and see previous analysis rather than starting fresh.

5. Stress-Test Capital Decisions

AI can evaluate capital and growth strategies before money is spent. Growers can model:

• Buying or leasing acreage
• Adding packing, storage, or processing assets
• Assessing distressed facilities
• Testing debt structures or partnership arrangements

AI helps generate questions for advisors, build draft pro formas, and surface risks, making conversations sharper and more informed.

6. Prepare for AI in Your Pocket

Duflock predicts a near future where AI lives on phones and ATVs. That means:

• Field scouting notes become structured reports instantly
• Photos tagged and analyzed for pests or disorders
• On-the-spot “what-if” scenarios while standing in the block

Growers do not live in front of desktops; AI on the go supports decisions where they matter most.

Duflock’s core message: AI will not solve labor, regulatory, or generational challenges on its own. But used deliberately with real farm data and clear economic thinking, it can help growers:

• See numbers more clearly
• Compare options more rigorously
• Move faster on strategic decisions

In an era of shrinking margins and rising complexity, that edge may be just as important as the next variety, trellis design, or piece of equipment.