With stressed margins and an overwhelming amount of data, ag retail managers are looking for clarity. Ever.Ag’s Ben Sloan explains how to turn AI into a tool for protecting margins, reducing shrink, and driving real-world ROI.
“There’s so much coming at us. How do we know what the trusted partner or the best solution that’s part of that,” says Ben Sloan at Ever.Ag. “And there’s an opportunity to identify our biggest problems right now, and then which can be solved right now with AI.”
Sloan says the artificial intelligence (AI) tools are available, but first, the most important step in getting started is making sure businesses are asking the right questions—that’s what leads to the right answers. Here are some examples.
3 areas in the ag retail business where AI can be applied:
- Showcase and share knowledge
- Automate work
- Identify gaps in the business
Spread Tribal Knowledge, Strengthen Teams
“I often hear, ‘John’s our guy at this location who takes care of us,’” Sloan says. “There’s immense benefits to share that tribal knowledge programmatically via these tools.”
As an example, new team members can use AI agents to upskill their knowledge faster. This helps flush out unwritten practices or insider, generational know-how.
A requirement to get there is capturing daily interactions of your team every day. This provides the repository to train the AI on and then build from.
Do More Value-Driven Work, Faster
“AI can automate the components of grunt work, or busy work, that is really about leveraging efficiency,” Sloan says. “It creates more capacity on a per-person basis because you can automate components.”
He adds Ever.Ag is promoting it’s retail customers keep humans ‘in the loop’ for now as they build these systems to ensure accuracy and is encouraging a crawl, walk, run approach.
Where You’re Missing Opportunities
With a handful of examples, Sloan says identifying gaps in the business and helping retailers address those is giving real-world ROI on investments in AI.
One is through an Inventory Insights product built for Merchant Ag ERP currently being piloted by five ag retail businesses.
“We looked at the problem of shrink, and if a standard U.S. business would have a shrink of 1-2% a year, if you’re a $100 million business, 1% shrink is $1 million. There’s a lot of juice to squeeze here as a result,” Sloan. “So we singularly apply an agent toward it,broke it down into three discrete problems, and then chained all those agents together to create a workflow for the user.”
This includes:
- Demand forecasting
- In-season management
- Post-season inventories/end of season balances
“We can give the right insight for the type of problem we’re looking to build upon with a timeline for those items. So based on what you did in-season, it maybe changes the demand forecasting,” he says. “It’s how can we curate the right data based on the context to get to the agent to deliver an insight.”
That’s one example of how AI agents are informing workflows and giving customers actionable insights.
Another example is in Roger, Ever.Ag’s agribusiness logistics software. With repeatability in loads from week to week, AI can help simplify workloads by automating dispatches set to be confirmed by the human staff member.
“Just as simple as creating copies, it’s a 4x to 5x reduction in the time it takes to do the same task in the workflow,” he says.
For agronomics, Ever.Ag’s FieldAlytics is deploying AI to give prompts, apply standards, and output insights. And customers who use multiple Ever.Ag products can layer those applications.
“Take FieldAlytics and Merchant Ag, there’s new insights that we can generate because we can connect those two datasets for that customer if the appropriate permissions are defined,” Sloan says. “I very much believe in the capabilities that Agentic tools are presenting themselves near term.”
AI Provides Unique Insights to Individual Businesses
Building on the adage that “when you’ve seen one co-op, you’ve seen one co-op,” Sloan says it’s powerful when a retail business applies its own data in these case studies and applications of the tools available.
“Everyone is delivering fertilizer, selling seed, applying things, but we all do it just a little bit differently. And I believe integrating both the work aspect, but then the customer’s own internal SOPs will really bring value to the customer base,” he says.
