Feedstuffs in Focus

Digital bridges: When technology strengthens human connections in agriculture

• Feedstuffs

Share episode

The agricultural landscape is evolving rapidly, and artificial intelligence (AI) stands at the forefront of this transformation. Jacqui Fatka, farm supply and biofuels economist with CoBank, takes us on a comprehensive journey through AI's emerging role in agricultural retail and farm supply cooperatives.

Far from threatening the traditional relationships between farmers and their trusted advisors, AI offers powerful tools to strengthen these connections. As Fatka explains, "That relationship is paramount. Farmers really depend on that trusted partner with those ag retailers." The technology enables agronomists to develop more precise prescriptions, capture critical field observations, and respond proactively to emerging threats – all while preserving the human touch that agriculture demands.

The accessibility of AI continues to grow, with entry points spanning from simple front-office applications to sophisticated supply chain optimization. Microsoft Teams' Co-Pilot feature, for instance, can streamline communication and documentation, while more advanced implementations might connect divisions within organizations that previously operated in silos. Fatka emphasizes the importance of privacy considerations and finding partners who truly understand agriculture's unique challenges rather than generic AI providers promising unrealistic returns.

Perhaps most significantly, AI offers a solution to one of agriculture's persistent challenges: preserving institutional knowledge when experienced staff members retire or change positions. By capturing detailed customer profiles and operational insights, AI systems create continuity that benefits both businesses and the farmers they serve, especially in today's tight labor market. As Fatka notes, "The relationships and how you really lean into knowing that producer, that grower, having it captured in an AI system, allows that easy transition." 

Discover how this powerful technology is reshaping agricultural service delivery while honoring the human connections that remain at the heart of farming communities.

Sarah Muirhead:

Back office front office. Will AI empower or disrupt agriculture, retailers and farm supply cooperatives? Welcome to Feedstuffs in Focus, our podcast taking a look at the big issues affecting the livestock, poultry grain and animal feed industries. I'm your host, Sarah Muirhead. This episode is sponsored by United Animal Health, a leader in animal health and nutrition. You can learn more about United Animal Health and how they're working to advance animal science worldwide by visiting their website at www. unitedANH. com. Joining us to talk about the potential influence of AI on agriculture, retailers and farm supply cooperatives is Jacqui Fatka, farm supply and biofuels economist with CoBank. Jacqui, you've completed an analysis of the value that AI can have for agriculture, retailers and farm supply cooperatives. Let's talk about that. Let's start by in the general sense what opportunities does AI offer farm suppliers?

Jacqui Fatka:

Yeah well, CoBank is a major partner in financing a lot of our ag retail space, from your local grain co-ops, you know, all the way through the supply chain, and I think every day we are hearing in our regular news cycle just this expansion of AI and artificial intelligence and we're starting to use it on our phones and our everyday work tasks, and so I really wanted to dig into some of the ways that ag retailers can use this as a way to really enhance what they're doing, improve operational efficiencies but, you know, the most important thing for them is to be able to serve their farmer customers and how they can use these tools to simplify things, enhance their offerings and really just bring together a lot of those tools that aren't quite as scary as maybe they once were, or even as high of a cost as they once were several years ago.

Sarah Muirhead:

Now, as you mentioned, ag co-ops and retailers. They serve kind of as that critical relationship bridge between farmers and input suppliers, but there's kind of some new distribution models and disruptive technologies in some ways that are kind of challenging that. So it sounds like AI then is an opportunity for kind of the preservation of that relationship that's long existed and really a way to keep ag co-ops and retailers as an important part of that overall ag supply chain. Is that kind of the way to look at that?

Jacqui Fatka:

Absolutely. I mean that relationship is paramount. You have to have a good relationship. Farmers really depend on that trusted partner with those ag retailers and so being able to have the best agronomic advice, understanding what you know, what that farmer may need. But you can't just enter in all that data into an AI system, right, that relationship is what really matters.

Jacqui Fatka:

And so you know, say, an agronomist goes out to a farm and is talking with that farmer and maybe they've worked with that farmer for several years. They may know some of the particular nuances of that farm or what that farmer maybe prefers, and so we like to call it a ground truth of you know. You may have the AI spit out a recommendation, but that agronomist still needs to look over that recommendation and give that to the farmer. So the AI might speed things up, enhance things. So that's one thing, right, just developing the prescriptions. But every time an agronomist goes to a farm, they can hit record and start recording that conversation, track some details, or maybe they can instantly say what are the open orders for this farmer, and that's another way to do. It can instantly say you know what are the open orders for this, this farmer, and you know that's. That's another way to do it.

Jacqui Fatka:

Also, we know that there's different scouting that happens.

Jacqui Fatka:

That can happen with AI or weed detection.

Jacqui Fatka:

You know that those identify, identifying those, sense and respond use cases, like we know that there's a heat, a heat, you know, extra heat coming this week, or we've seen some pests identified in this neighboring farm.

Jacqui Fatka:

So being able to reach out to that farmer and say you know, hey, we identified that maybe some potential concerns could be coming, would you like to look at that? And again, it's all about bridging that relationship with the grower, your customer, and and being able to really lean into. You know all of the details too, even you know knowing that maybe someone just had a birthday or you know one of their kids graduated. Right, like capturing some of that information to really lean into that, that that relationship, right, so you see a farmer is calling you and you can quickly enter into maybe the AI system of this contact and you may have a whole profile on that particular farmer and being able to just really lean into that importance of the relationship. It's not just dollars and products sold. A lot of it is an ongoing understanding of who that farmer is, what they like and also some of those even personal information to really meet their needs and what they need on their farming operation.

Sarah Muirhead:

So there's value in adopting AI, but how does one determine when to get involved and where to start?

Jacqui Fatka:

Yeah. So that was one big reason why I wanted to look into this report, because I think again back to the fact that AI is becoming more common just in everyday life for people. So there's kind of a lot of different entry points that ag, retailers, co-ops, people within the supply chain can start to look at. You know one of those is just in the front office. You know the folks who are working on meetings. You know Microsoft Teams has an ability to. You know co-pilot allows, you know, a lot of simplification of writing emails better. You know, maybe writing a job description more specifically, recording your online meetings or just if you have even a meeting where people are all in the same room recording that, instantly having key takeaways that are pulled from that and action items being able to capture some of that. So you know that's one easy kind of entry point is some of the front office things. You know. Obviously there's some opportunities to. You know the customer relationship management systems.

Jacqui Fatka:

A lot of those CRMs aren't always designed to really look at the selling inputs and the routine duties of an agronomist, but if we can use AI to help talk to those together, right. But then there's even the fact that we have a lot of times. A grain co-op, for instance, has an agronomist and has a team that's working to help that farmer grow the highest yield, best performing on their land, right, but then they're not necessarily working with their grain merchandisers to say, okay, well, we know that this farm is going to have X amount of bushels, likely this fall, based on all of these variables that we've helped them determine. So then also within your own organization, talking between divisions, helping them identify where things might, you know how you could say, hey, we just saw a $4 increase. You know, we hit $4 corn or $4.50 corn. You know, let's try to price out some of that, looking at working together within divisions.

Jacqui Fatka:

But then also, too, the supply chain management. We know that AI can help us identify maybe the most efficient routes on things. If we know that last year we sold X amount of product out of this facility and we didn't sell as much out of a different facility, but we had the equal amounts at both. Right, being able to shift and identify where we might need to have an increase in supply or make sure we're ready for that, or back to that identify and use scenarios. We see a disease or a past pressure in a specific area. We want to make sure that our supply chain is ready to meet that too. So having AI helps kind of piece all of those different variables together and put it at our fingertips.

Sarah Muirhead:

I know some AI tools are free, you know, and some you pay for. But how do you determine what that level of investment should be, and is it best to be an early adopter or kind of to, you know, wait in a little bit and see how things are progressing? Any kind of advice or overall thinking in that regard?

Jacqui Fatka:

Yeah. So I mean, one of the biggest things that I kept hearing is make sure you understand the privacy of the different tools you're using. You know, we hear a lot about ChatGPT and Grok and some of those tools. The problem is, if you put a customer information in there that then becomes public, and so what we, you know, knowing those guardrails and establishing those guardrails within your company is really really important to know that if you are going to, you know practice different things or put in input different information, know where it's going. There's a there's a case, apparently, that a dentist put in all the personal information into a letter so that he could send out something to everybody you know, letting them know when their next appointment was, and then, all of a sudden, all of that personal information was then public. And so you know, that's one of the most important things is establishing those guardrails, understanding privacy and then also too, I think, finding partners that really understand agriculture.

Jacqui Fatka:

The whole world is just kind of exploding, with different companies who are saying, you know, promising huge ROIs and offering the world.

Jacqui Fatka:

But finding those ag partners, those companies within this AI space that really understand agriculture, is really important because you and I know how unique and as well as diverse the ag industry is. So knowing some of those unique challenges within this business system with a partner is really good. And also, too, if you're an organization, having somebody within the organization that kind of is the AI point person, being able to help everybody on staff kind of navigate some of the opportunities, is also really beneficial to be able to again help just ease into this space because the cost is actually gone down quite a lot. There's some tools that aren't very much. You know there's some ag specific companies that are out there that really do work with you, regardless of your size. So you know it doesn't have to be a huge cost. You know some of those bigger companies are able to capture larger ROIs because there's more opportunity for them to capture those savings if you're looking at supply chain management. But in some ways it really does enhance it kind of levels the field in some ways as well.

Sarah Muirhead:

You mentioned ROI. Is there something a level of ROI in terms of what you can expect to achieve, or how best do you go about measuring that? It probably depends on how much your adoption is of AI and how quickly you adopt it, but is there a general rule that folks should think about?

Jacqui Fatka:

You know when I was talking with people, it really does, as I just mentioned. Sometimes those larger companies can see, you know, even 70 times ROI if they really basically if it was able to shine a light on an extreme inefficiency that they didn't see before. You know you think about supply chain and how it moves and you're thinking about trains and unloading. You know there's a lot of opportunity. So it kind of depends on what level of adoption. You are right. So you know, incorporating a co-pilot, recording, a transcription right and key takeaways, you're not going to have a huge ROI on that right, but you know some of those supply chains. You're able to see a lot more value. But you know also to the, sometimes it's not necessarily savings, it's just amplifying what somebody can do.

Jacqui Fatka:

Right, like you think about an agronomist and a lot of times agronomists feel really overwhelmed with all the data that they're trying to capture when they go visit a farm or they're entering things in and so being able to they don't have to manually enter it and having some kind of system that would record, condense and then you know, create that, you know generate that kind of profile of that customer.

Jacqui Fatka:

That kind of profile of that customer that saves a lot of time. That probably saves even maybe having to hire an administrative assistant for some of those agronomists, right? So there's varying levels of cost savings, time savings, and sometimes it's not necessarily a savings, but again it goes back to how do you better serve your farmer customers and how do you do your job better. And the other thing too and we haven't talked about this yet is we have a lot of turnover in this space too, and so the relationships and how you really lean into knowing that producer, that grower, having it captured in an AI system, allows that easy transition. If an agronomist decides to leave or retire or go to another company, that profile is still there for that next person that they come in. So it helps just augment what they're doing on the ground too. So you know you can't really put an ROI on that, but we know how valuable it is because, again, it goes back to how you best serve your farmer customers.

Sarah Muirhead:

Yeah, there's lots of information and knowledge you can lose. Valuable it is because, again, it goes back to how you best serve your farmer customers. Yeah, there's lots of information and knowledge you can lose when someone retires or moves on, and if you can preserve that, that certainly puts the new person at a good starting point. So it sounds like there could be. I know people always fear this, but in terms of a staffing standpoint, there could be some staffing advantages as well from AI adoption.

Jacqui Fatka:

You know, it's kind of been a fear and an opportunity, right. And so, again, right now, especially AI is an augmented intelligence, right, like, we still know that there's some hallucinations, we still know that there's some issues. I talked earlier about that ground truthing, being able to have somebody who really understands what is going on and verifying it. We can't just flat out trust whatever is being spit out by. You know, these different AI tools they're getting better and they're improving. Ai tools they're getting better and they're improving.

Jacqui Fatka:

So, you know, I think we definitely see that there's opportunities for it to augment our labor, maybe allow agronomists to maybe cover more acres, you know, serve more farmers, be able to maybe have fewer people. But you know, we're challenged right now with meeting all of these labor, filling all these labor spots on some of these, you know, very rural, remote grain locations, and so you know, there's always a certain level of jobs that may be replaced or, you know, made different because of this. Right, like, even a drone operator, they are going to need different skills than maybe an operator fly, you know. Or a sprayer unit, right, but it's different, but you need both of those skills.

Sarah Muirhead:

So some opportunities, probably a few challenges just how you manage AI adoption and execution as you move forward and bring it into your operation. You mentioned grain operations, but I'm assuming, too, there'd be a lot of application when it comes to livestock operations, and nutritionists and veterinarians could use a lot of these tools, perhaps in the same way that you're talking about agronomists using these tools.

Jacqui Fatka:

Absolutely, and it's funny because in the livestock industry, ai has a total different meaning, right, artificial insemination or artificial intelligence. But you know, we definitely there's a lot of tools in the livestock space that are already helping us know what the animals are, you know if they're almost sick or you know their levels are changing, and that's the great thing is, there's so many tools that we've started to dabble in in the overall ag space. But just the bigger stepping back and seeing how technology worldwide is advancing so fast, we want to make sure that ag is able to participate in this right. We we don't want there to be a digital divide and you know, an AI divide because the ag sector isn't able or willing to to to to dig into this. And you know one of the, the folks that I talked to, said it so well to to to dig into this. And you know one of the folks that I talked to said it so well he's like sometimes we're waiting for people, we're we're not giving the next technology, but we should really encourage our, our producers, the people that we're, that we're servicing, to go where we want them to go, not meet them where they are right, like we.

Jacqui Fatka:

Ag is very good about technology adoption but looking back, they've also been burned in some of these right Like bad technologies or technologies that were really cost costly, that maybe didn't have a good return on investment. But now we're starting to see things decrease in cost. The opportunities for everyone in the ag space is really expanding and at the end of the day that's going to really be important as we look at somewhat tighter margins you know, just a constrained overall ag financial environment able to continue to farm another day, to have that money, to continue to reinvest and be profitable, and that just kind of snowballing effect of technology adoption and the ways that it can trickle through the whole supply chain.

Sarah Muirhead:

Our thanks to Jacqui Fatka, farm supply and biofuels economist with CoBank. This episode has been sponsored by United Animal Health, a leader in animal health and nutrition. You can learn more about United Animal Health and how they're working to advance animal science worldwide by visiting their website at www. unitedANH. com. I'm Sarah Muirhead and you have been listening to Feedstuffs in Focus. If you would like to hear more conversations about some of the big issues affecting the livestock, poultry grain and animal feed industries, subscribe to this podcast on your favorite podcast channel. Until next time, have a great day and thank you for listening.