Michelle Montgomery champions AI-supported farming for smarter greenhouse management
“Having one collective source of data allows you to look at every input.”
NORTH AMERICA – Michelle Montgomery is helping greenhouse growers across North America use artificial intelligence to simplify operations and cut costly mistakes.
As an Artificial Intelligence Solutions Specialist at Source.ag, she brings her own experience as a grower to support others in improving how they manage data and make decisions.
Montgomery, who previously served as a Head Grower in Kingsville, Ontario, says she experienced the limits of manual data management firsthand. “We were very data-driven when we started,” she recalls.
“But all of it was done in Excel sheets or Word files. We did crop registration, production tracking, and variety trials — at one point with about 150 varieties in the greenhouse — all in one file. It was very hard to analyze.”
According to Montgomery, manual input often slowed operations and increased the risk of error. “We had people in the greenhouse weighing vegetables, writing everything down on paper, and then entering it into Excel,” she says. “Human error was a huge issue. If you try to do it fast, mistakes happen.”
Bringing structure through AI
Montgomery joined Source.ag to help growers replace spreadsheets with a unified digital system that collects and analyzes farm data. The company’s software connects environmental sensors, irrigation schedules, pruning records, and harvest data into one platform.
“Part of why I joined Source.ag was the way the technology brings everything,” she says. “Having one collective source of data allows you to look at every input — not just what the plants are doing, but how the environment and actions around them interact.”
The AI models used by Source.ag simulate how crops will respond to specific management decisions and weather conditions. This helps growers prepare for potential challenges instead of reacting after the fact.
“Instead of reacting after something happens, growers can forecast outcomes and make adjustments in advance,” Montgomery explains. “If a particular approach isn’t going to work, you can see what alternatives exist and plan accordingly.”
Forecasting harvests and reducing guesswork
One of Source.ag’s most applied tools is Source Harvest Forecast, which predicts crop timing, yield, and fruit weight up to eight weeks ahead.
Montgomery says this allows farmers to plan labor, logistics, and distribution more accurately. “With Source Harvest Forecast, you can see up to 8 weeks in advance how your produce will develop and adjust your harvest schedules accordingly,” she says.
“It’s about reducing surprises and making operational decisions based on data rather than guesswork.”
The system also learns from past crop cycles, enabling continuous improvement. “It’s about helping them be better and giving them a clearer view of what’s happening in the crop,” she adds.
Supporting growers on the ground
In her current role, Montgomery works directly with growers to ensure they understand how to use the platform effectively. “My job is to make sure growers know how to gather information, look at it, and optimize it for their own use,” she says.
“It’s not just another source of data; it’s something that supports decision-making and operational planning.”
She stresses that the technology is meant to assist, not replace, human expertise. “I always say that I’m a grower helping other growers. I know the frustrations. If I can take one small thing off their plate, or show them a better way to look at their data, that’s what I want to do.”
As Source.ag expands its presence across North America, more growers are adopting AI-supported farming to improve accuracy, reduce waste, and make informed decisions.
Montgomery believes this shift marks a practical step forward for greenhouse operations, where data serves as a trusted partner in every growing season.
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