We are certainly not alone in our interest in how artificial intelligence will shape agriculture in the coming years. We’ve been learning out loud about both the tech that might emerge, but also about how AI might shape existing tools, especially agtech software. In our recent report, Yield Maps Killed AgTech Software, Can AI Fix It?, we put forward some of our research and theories, and we got a ton of great feedback. Today, we’re going to respond to some questions and discuss further learnings from the report. 

Joining me in the task is both my co-founder Matthew Pryor and Rhishi Pethe, author of Software is Feeding the World. Together, the three of us tackle topics including: 

• What we got right, what we got wrong, and the kinds of things (like AI business models in agtech) that we’re still thinking about
• The existing problem with ag software tools like yield maps, and how AI may hold the secret to unlocking real value for growers
• When (or whether) generative AI tools will be reliable enough to trust, and when (or if) farmers will then buy-in

Useful Links:

• Yield Maps Killed AgTech Software, Can AI Fix It 
• Future of Ag Podcast on Generative AI (with Tim Hammerich)
• Getting into the Weeds: The AI Data Dilemma
• AgTech… So What? Bonus Episodes: Three Fears of Farm Data and Farm Data Fears: More Harm Than Good? 
• Wait, but Why Episode on Exponential Thinking and AI
• Check out Metal Dog Labs
• Shane Thomas on Generative AI in Agriculture 

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