FIELDS OF DATA

The rise of Alis bringing transparency to farmland values.

- Cassidy Walter

Sometimes the answer to a question is right in front of you, but you can't see it. Like where is the box of tissues in the storage closet? My husband insists we are out of tissues. I insist there is a box in there, he just needs to keep looking. We bicker about it some more, shouting from opposite sides of the house, until I finally join him at the closet and find it myself...in seconds.

Artificial intelligence (AI) is on its way to helping humans efficiently sort through the "storage closet" of farmland data to answer complex questions, such as how much a field is worth and who is likely to buy it. Yet, some say it has a long way to go.

Building on the Data

In some states, farmland sales data can be hard to come by. For others, it is public information that can be requested at county offices, but even then, the information has not been aggregated for easy consumption. Today databases can help farmers and ag real estate professionals investigate not only sales prices but also specifications such as soil type and crop history. Such databases are in their infancy but are the foundation AI needs before it can provide meaningful insights.

"This is why I've been collecting every bit of data I can," says David Whitaker, owner of Whitaker Marketing Group. "Eventually, it's going to be very important."

Whitaker is an ag real estate agent in Iowa, where sales data is reported in every county.

Existing AI technology can efficiently sort through and analyze the sales data he has curated over the years. He can prompt the AI platform to find comparable properties within his dataset that can help him estimate for clients what a piece of land may be worth.