World’s Newest Innovation Transforms Age-Old Industry of Agriculture

Generative artificial intelligence (AI) is one of the latest ground-breaking technologies in 2023.

Conversely, people have been breaking ground with agricultural techniques since civilizations began.

As we head into 2024, might there be potentially game-changing synergies between humanity’s newest invention, AI, and one of its oldest industries, farming?

“If you look at the current situation that we’re in with agriculture today, especially in the U.S., labor is the number one challenge across the board. Whether you’re a farmer or you’re a business in the supply chain, you have serious labor problems where you don’t have enough people. The exciting part of AI is that these tools can help fill certain roles in the business that are growing increasingly hard to find or fill,” Jake Joraanstad, CEO at Bushel, told PYMNTS for the “AI Effect” series.

By automating tasks and enhancing efficiency, AI can alleviate the labor challenges facing agribusinesses, many of which are exacerbated by the rural nature of the industry — making attracting talent from urban centers a tall ask.

But that’s not the only area where AI can help push agriculture forward.

See also: Farmers Are Pretty Digital; Their Buyers Are Really Not

“If you zoom out, agriculture is a supply-demand problem,” said Joraanstad, noting that AI’s ability to aid in farmer decision-making is another area where it can have a significant impact.

For instance, farmers often struggle to determine which crop to plant based on market demand. By analyzing vast amounts of data, including market trends and weather patterns, AI can provide valuable insights and recommendations, empowering farmers to make more informed decisions and optimize their crop production.

“In the spring of every year in North America, a farmer has to decide what crop they’re going to plant. And if the farmer was aware of the demand of corn going up, and of soybeans going down, they would know that planting corn this year would be a wise decision. It’s unclear today how to get to that answer,” said Joraanstad, adding that the downstream outcome of this is better prices for consumers at the grocery store.

The Impact of AI-Led Optimization

Financial management is yet another domain where AI can make a difference within the agricultural sector.

Tools that help farmers understand their financial needs throughout the year can lead to better financing options, and by providing insights into crop performance and market conditions, AI empowers farmers to optimize their financial decisions and reduce market volatility.

“Most farms take an operating loan during the year, usually in the hundreds of thousands, if not a multimillion-dollar position. They have to repay that, typically by the end of the year when they finish harvest. If [AI] can help the banks and financiers that work with that farmer to better understand that this farmer’s going to do well this year, then they can have a better rate on their loan,” said Joraanstad, noting that in today’s sky-high interest rate environment, any knock-down is a welcome one.

Supply chain management and market analysis are also areas where AI can assist farmers.

By processing extensive information, AI algorithms can help agribusinesses gain deeper insights into market trends, enabling them to make well-informed decisions regarding pricing and distribution, Joraanstad said.

From Adoption to Implementation

While the adoption of AI in agriculture may encounter challenges such as resistance to change and concerns about fake information, the potential benefits are significant.

“In our experience, farmers are always willing to try new things — and if there is a real pain, then farmers are willing to try whatever exists that could solve that pain,” Joraanstad said. “The problem is they get only one shot a year to get the crop right, to get the operation right. And so they can only try so many iterations.”

“The supply chain players, the agribusinesses in the middle, they’re the ones who have processes in place that they’ve been doing a specific way for a hundred years, and they’re the ones that are the resistors to some of these changes,” he added.

Still, as AI continues to evolve, it is expected to play a crucial role in streamlining agriculture and enhancing farming operations — particularly when applied in concert or combined with other technologies already in use in the agricultural sector.

For instance, satellite tracking and autonomous image recognition can be integrated with AI to monitor crop distribution and assess crop health. Similarly, as plant genetics become increasingly vital in crop development, AI can assist in understanding the complexities of crop genetics and optimizing breeding programs, Joraanstad noted.

Looking ahead, the future of AI in agribusiness holds immense promise.

“We always overestimate the first three years of a technology, and severely underestimate the 10-year time horizon,” Joraanstad said.