AI Could Save Farming Knowledge Before It Disappears

According to AgFunderNews, the global agriculture industry is facing a growing succession crisis as aging farmers retire without transferring decades of operational knowledge to younger generations. Industry leaders and technology experts now argue that artificial intelligence could become a key tool to preserve farming expertise, improve decision-making, and help independent farms survive in increasingly volatile markets.

The issue goes beyond economics. As explained by SWARM Engineering CEO Shail Khiyara in an opinion piece published by AgFunderNews, much of modern agriculture still depends on knowledge stored in the minds of experienced farmers. That includes understanding weather patterns, soil behavior, irrigation timing, supplier reliability, crop rotation strategies, and market risks.

“When the farmer exits, the land remains. But the intelligence that made it productive disappears,” Khiyara wrote, according to AgFunderNews.

The article highlights the story of American farmer Don Guinnip, whose family has farmed the same land since 1837. At 74 years old, with no successor prepared to continue operations, his farm represents a wider trend affecting agriculture worldwide.

The numbers illustrate the scale of the challenge. In the United States, farm bankruptcies reportedly increased 46% in 2025 compared to the previous year. The USDA also estimates there are now more farmers over the age of 75 than under 35.

The same demographic pressure is affecting other regions. Japan’s farming population continues to shrink rapidly, while the European Union reports that more than half of farm managers are over 55 years old. In countries such as Portugal and Spain, the aging of agricultural workers is becoming a structural concern for long-term food production and rural economies.

According to AgFunderNews, the debate is now shifting toward whether AI-powered agriculture systems can help close the knowledge gap before experienced farmers leave the industry.

Unlike traditional precision agriculture tools focused mainly on machinery, sensors, or automation, newer AI systems aim to support operational decisions in real time. These platforms combine weather data, logistics information, market prices, supply chain disruptions, and production constraints to recommend actions while conditions are changing.

Khiyara argued that this approach could help younger or less experienced operators make better decisions without requiring decades of trial-and-error learning.

For example, AI systems can simulate multiple production scenarios for grain operators, detect moisture variability before it affects profitability, or help new farmers evaluate crop rotations and pricing strategies before investing capital.

“This is what I mean when I say AI stops being a tool and starts becoming a partner,” Khiyara stated, according to AgFunderNews.

The discussion also reflects concerns about the future structure of agriculture. Without better succession systems, many experts fear the continued consolidation of farmland under large corporations and institutional investors with greater access to technology and capital.

Supporters of AI adoption argue that making advanced decision systems accessible to smaller operators could help preserve independent farming and create opportunities for a new generation entering agriculture without family experience.

At the same time, the article warns that technology alone will not solve agriculture’s structural challenges. Trust remains essential in the sector, and farmers have historically rejected tools that fail to deliver clear operational value.

Still, advocates believe the next phase of agricultural technology will focus less on maximizing yield and more on preserving decision-making intelligence across the full lifecycle of a farm operation.

For many in the industry, the central question is no longer whether AI belongs in agriculture, but whether farming can maintain its continuity without it.