6 Smart Tech Trends to Watch in Agriculture in 2026

Smart technology is no longer a novelty in agriculture. It is becoming a foundational part of how farmers and ag retailers plan, operate, and respond to shifting conditions. As the 2026 season approaches, the industry is entering a new phase where connectivity, decision intelligence, and human-centered automation converge to deliver more practical value on the ground. To better understand what is changing and why, we spoke with three industry leaders: Reinder Prins, Head of Marketing at Agworld; Mike Roudi, CEO of Emergent Connext; and Tim Hassinger, President and CEO of Intelinair.

Here are the six trends they say will define agricultural technology in 2026.

1. Adoption Accelerates Where Value Is Proven

Smart technology adoption continues to rise, but it is still uneven across farm sizes and regions. Prins described the landscape as “steady but uneven,” noting that larger, service-driven operations are leading the charge while smaller farms remain cautious.

In 2026, he expects adoption to climb in areas where tools clearly improve margins. “We will see more interest in planning tools and variable rate applications because they save on costs and help manage risk,” he said. Government and private incentives tied to carbon and sustainability reporting will also encourage participation. “Paperwork pain is real, and anything that reduces it will bring people in.”

Roudi sees a slightly different catalyst. “The bottleneck is not technology. It is trust, simplicity, and a clear path to value,” he explained. He believes adoption will soar when farmers experience integrated, reliable systems. “Once everything connects and works every day, adoption will take off like a rocket.”

Hassinger agreed that the turning point for adoption is practical ease. “This is no longer a trial. It is a business decision,” he said. The tools growing fastest today are imagery-based scouting, variable-rate work, and digital tools for planning and tracking field jobs. In 2026, he expects adoption to accelerate when technology fits how people already work and slows when it introduces extra steps.

2. AI and Generative AI Become Field-Ready Decision Partners

AI has been present in agriculture for years, but often in a way farmers do not directly see. “Most AI on the farm today is still under the hood,” Prins said. It powers yield prediction, disease models, irrigation scheduling, and imagery interpretation. What farmers see is not the model, but the alert or recommendation that comes from it.

Generative AI will shift this dynamic. Prins expects it to act more like a conversational agronomy assistant. “It will explain why a recommendation was made and compare scenarios,” he explained. The real breakthrough will come when AI agents work across multiple systems instead of being confined to a single vendor ecosystem.

Roudi believes generative AI will help farmers move from awareness to action. “We are shifting from ‘what happened’ to ‘what should I do next,’” he said. He sees generative AI translating complex, layered data into farm-specific plans delivered in natural language.

Hassinger emphasized improved usability. “AI helps teams act on what matters most. It brings imagery, weather, machine data, and field history into one place so teams can see priorities,” he said. As generative AI matures, he expects straightforward guidance. “The next step is turning data into a simple plan: what to do, why, how confident we are, and how to get it scheduled.”

Several high-impact generative AI applications are emerging:

• Label intelligence for agronomists. Prins sees systems that digest chemical labels, evaluate them against field context, and provide a list of key considerations. “This can prevent off-label or ineffective applications,” he said.
• Virtual advisory support at scale. Roudi noted that generative AI will not replace experts. “It will amplify them,” he said.
• Season planning and variable-rate automation. Hassinger pointed to draft recommendations, automatically organized season plans, and simplified grower updates as early wins. “It helps teams spend more time acting and less time sorting through data,” he said.

3. Connectivity and Interoperability Reach a Turning Point

Connectivity has long been one of the biggest barriers to smart tech adoption. That barrier is finally lowering. Prins highlighted the 2024 SpaceX and John Deere partnership as a milestone and pointed to increasing offline-capable tools that reduce dependence on constant connectivity.

Roudi sees even more significant progress. “We are finally seeing purpose-built rural IoT networks come online,” he said. He noted that Emergent Connext is deploying an IoT backbone designed specifically for agriculture. “Farmers do not have to wait. Every enrolled acre receives reliable IoT coverage from day one.”

Interoperability across systems remains a challenge, although the path forward is becoming clearer.

Roudi said the winners will be companies that offer open APIs and avoid locking farmers into proprietary ecosystems. “Farmers want systems that connect without forcing them to choose between brands,” he explained.

Prins takes a different view on standards. He does not expect unified standards to dominate. “AI makes it easier to create bespoke integrations,” he said. Collaboration will remain important, but rigid, expensive standards are unlikely to define the future.

4. Automation and Robotics Grow More Accessible

Automation continues to advance, but people remain essential. Prins noted that automation performs well on repeatable tasks like mowing or weeding, yet still struggles with context. “When it comes to understanding the whole farm system, we do not have good automation for this yet,” he said. Trust also remains central. “Robots will not replace the relationship between a grower and a good agronomist or retail rep.”

The future is likely to be hybrid. “The best setups in 2026 will be human-in-the-loop systems where automation does the heavy lifting and people decide when to change the plan,” Prins said.

A key question is whether mid-sized operations can afford automation. Prins said yes, but in a modular way. “The shift is happening through task-specific tools and service models,” he explained, citing SwarmFarm Robotics as an example.

5. Data Intelligence Becomes More Predictive, Practical, and Unified

Predictive and prescriptive analytics are improving but still require human judgment. “They help inform part of a decision, but not the whole decision,” Prins said.

Roudi described the shift underway as a move toward proactive intelligence. “We are moving toward systems that forecast issues and recommend actions before they happen,” he said. That shift depends on clean, consistent, real-time data flowing from the field.

Hassinger has seen analytics become more operational. “It is moving from ‘what might happen’ to ‘what should we do next, and when,’” he explained. These tools support labor, equipment, and product planning while making recommendations more transparent.

Unified data systems are also emerging. Prins said agronomic, financial, and environmental data is increasingly treated as a single information layer rather than separate reports stitched together later. Roudi pointed to a growing demand for “one view of the farm.” Hassinger noted that sustainability data is beginning to appear inside normal workflows rather than as a separate reporting burden.

6. Retailers Evolve Into Trusted Data and Technology Partners

As technology becomes central to farm operations, the role of ag retailers is shifting. Prins expects retailers to function as both input suppliers and data partners. “The best retailers already bring together agronomy, logistics, data, and compliance,” he said. He anticipates more dedicated digital agronomy teams forming within retail organizations.

Roudi described retailers as future digital integrators. “Their strength is local relationships. Smart tech gives them new tools to deliver insights, not just inputs,” he said.

Hassinger believes the fundamentals remain the same. “Retailers will still win on trust, local knowledge, and doing what they say they will do,” he said. Smart tech will help them deliver that consistency through better planning, clearer priorities, and more transparent recommendations.

Looking Ahead: The Rise of Connected Intelligence

Asked which emerging concept will have the greatest impact in 2026, all three experts pointed to technologies that simplify decisions and connect disparate systems. Prins sees AI assist tools accelerating work and improving decisions. Roudi expects “connected intelligence,” or the fusion of ubiquitous connectivity with AI and real-time field data, to have the greatest impact. Hassinger anticipates widespread use of decision copilots that turn data into field-by-field priorities.

Put simply, the most transformative technologies will be the ones that integrate people, data, and systems into a unified workflow. In 2026, the future of smart agriculture will not be defined by any single tool. It will be defined by the way everything finally works together.