Editor's Note: This article was originally published in the Feb. 15, 2026 edition of Ag Equipment Intelligence. To view AEI content as it's published, you can subscribe to the monthly newsletter here.
In a recent note, Baird analyst Mircea (Mig) Dobre posed the question, “Is AI an enabler or a disrupter?” He noted the recent turmoil observed in software, coupled with the very robust performance of the machinery sector, provide some clues about where the AI trade could be heading in 2026.
“Thus far in machinery, AI has been looked at from the standpoint of the picks-and-shovels trade with a focus on the infrastructure buildout, Dobre said. “We think we are near a new stage where investors will seek companies able to use AI to increase competitive moats/profitability — machinery and rental should fit the bill.”
The Baird analyst said that the firm views AI as a potential disrupter for business models built on information access and digital products.
“It’s not just the notion that Claude Code or Cowork can evolve from simple chatbots to products that can automate enterprise processes or that Anthropic can now do legal work, but also the reality that AI is providing tools enabling new entrants (products, companies) while lowering development costs and thus eroding competitive moats,” he said.
Dobre added, however, that they believe the opposite is true for machinery, acknowledging the physical nature of work. He noted, for instance, that ChatGPT can’t plant soybeans. This limits the potential for disruption, he said.
“Furthermore, the actual deployment of AI on machines leads to productivity increases, which can be used to extract value for the machinery OEM through ROI-based pricing (DE is a classic example of using this technique in precision ag),” Dobre said. “Lastly, AI is likely to raise not lower OEM competitive moats — competition in machinery is based not just on product features but on service/support, physical product reliability and used equipment residual values.”
Dobre went on to say that adding AI to the above adds the dynamic of an intelligent ecosystem of connected machines, which can increase the productivity of fleets — not just individual machines. In turn, this can raise the user cost of switching brands, while at the same time this raises “the cost for a new entrant as the investment necessary to establish physical infrastructure will couple with lack of ability to access data of similar quality as incumbents have access to.”
The Baird analyst noted that manufacturing environments with complex supply chains and inventory management seem particularly well-suited to benefit from AI tools.
