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AEM White Paper Explores AI’s Growing Role in Agriculture

The report examines three levels of AI integration in ag equipment, from operator-assist tools to autonomous field operations, and highlights use cases already improving farm efficiency and decision-making.

byRita Garwood
September 11, 2026
in EF News, Data and Economy
Reading Time: 2 mins read
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To help non-road equipment manufacturing stakeholders better understand the growing role of artificial intelligence (AI) in agriculture, AEM has released a new white paper — “AI in Agriculture Equipment: Supporting Productivity, Efficiency, and Decision-Making Through Technology”.

The paper outlines how AI is increasingly becoming a foundational component in ag equipment, being integrated directly into machines and systems, and evolving into a “must-have” tool to support real-world farming operations. It can be viewed and downloaded on AEM’s Insights & Resources page.

“AI technology is proving to help farmers in their efforts to be productive and competitive, especially as operational challenges continue to intensify for the ag industry,” said Senior Director of Agricultural Services Austin Gellings, who oversees the AEM Ag Technology Leadership Group that developed the white paper.

“The paper helps illustrate how, when deployed responsibly and supported by appropriate frameworks, AI strengthens farm level resiliency, supports a competitive agricultural sector, and contributes to a stable and secure food system for the future,” added Gellings.

The white paper outlines in detail the three primary levels of AI integration in ag equipment today:

  1. Assist-Level AI, which supports operators through technologies such as guidance systems, implement control and automated equipment functions while keeping the operator in control
  2. Advise-Level AI, which analyzes large volumes of machine and operational data to provide recommendations and decision support
  3. Act-Level AI, which enables machines to execute tasks with greater autonomy, such as targeted spray applications and autonomous field operations

The white paper also:

  • Highlights the industry’s ongoing work to support responsible AI deployment through established standards, safety frameworks, interoperability initiatives and governance practices.
  • Examines several real-world AI use cases already delivering value in the field, including operator decision support, predictive maintenance, data-driven continuous improvement, precision spraying and autonomous equipment operation.

“As global demand for food continues to grow and farmers face increasing pressure to do more with fewer resources, AI-enabled equipment is expected to play an increasingly important role in supporting a resilient, competitive, and sustainable ag industry,” said Seth Zentner, precision farming and systems engineer at AEM member company CLAAS, Inc. and chair of AEM’s Ag Technology Leadership Group. “By turning data into action and helping farmers respond to changing conditions in real time, AI is becoming an essential tool for advancing productivity and supporting food security for the future.”

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