AI for Agriculture Commodities

The Economist October 25-31st 2025 edition featured an article about weather forecasting. In the article titled “Meteorologic rise: AI weather models and their predictions of India’s rains” the authors tell the story of how computers can predict with greater accuracy when the vital rains needed for agriculture success will arrive and where.  Imagine a three-dimensional grid of the world with each micro-segment of the grid measuring variables for temperature, pressure, wind speed, and such. And then calculating with greater-than-ever precision, the amount of rainfall expected and where it will drop. 

With that insight and power, AI should be able to predict crop results for agriculture commodities in the US. Oranges in Florida, corn in Iowa, soybeans in Indiana, all forecasted with greater accuracy. Those with this information would have a distinct advantage when trading agriculture commodities; if we know the crop will be good and plentiful, then the prices will be lower. Conversely, if we know the crop will be in short supply due to say flooding or freezing, then the prices will be higher. And we can trade accordingly, ahead of the flood and freeze. 

Bigger picture, will this ultimately lead to both the destruction of the agriculture futures market and the potential for lower food costs?  In a world where a few in possession of supercomputers with AI models to forecast weather and crops, once that fact becomes common knowledge, will others want to participate in that market?  In other words, if players in the market know what will happen involving weather and crop outcomes, and the rest of the world has no idea, why would they play in that market?  We’ll see what happens there, as well as what happens when you can potentially better manage food costs through smarter hedging and logistics informed by supercomputer AI models.  Could we see more stable, lower prices for agriculture?