Lindsay's Farm-Tech Pivot: In a Deep Ag Trough, AI Becomes the Growth Story
A one-point Brazil rate cut with a 38% smaller funding pool, a one-time tariff refund, and an AI-in-irrigation ramp in the middle of a cyclical bottom.
LNN · Earnings Call · 2026-07-02
A cyclical trough meets a technology inflection
Lindsay Corporation is grinding through what amounts to a cyclical bottom in agricultural markets. Trade uncertainty, high input costs, and weak farmer sentiment kept the pivot business soft in the fiscal third quarter, and CEO Randy Wood was blunt about the near term: “We do not expect a meaningful near-term recovery in North American demand until these economics improve.” — Randy Wood, Chief Executive Officer · 2026-07-02 Sales volumes fell once again, driving revenue to $160.8M, down 5% year over year — a continuation of the trough the company has ridden all year, as Wood put it back in January: “we would agree that we are bouncing along the trough here.” — Randy Wood, President and CEO · 2026-01-08 Yet buried inside the soft quarter is something genuinely new: a sharper articulation that technology — specifically AI — is the answer to the very profitability problem suppressing the equipment business. With commodity prices below the cost of production for several key crops, growers cannot afford to expand; Lindsay's counter is to sell them software that makes every applied acre-foot of water more productive.The pitch — FieldNet Advisor scheduling plus machine learning on the SmartPivot platform to "pre-diagnose" mechanical failures before they happen — is a company-unique twist on the global AI narrative. And management's confidence in "sustained double-digit technology revenue growth" this fiscal year comes even as research and development spending runs roughly flat year over year, suggesting the AI work rides on an existing install base rather than a fresh spend line.When you look at customers right now selling commodities for less than it costs them to grow them, we've got to find ways to enhance our profitability wherever we can. With FieldNET Advisor specifically, we've really been deploying a lot of AI models to help with irrigation scheduling... they can wake up every morning and know exactly what water is required where, based on historical weather, predicted weather, crop growth stage, soil type.