AI's impact is no longer confined to office work; it's also transforming agriculture. PepsiCo is using AI to help farmers make faster, more informed decisions in the field. Jim Andrew, PepsiCo's EVP and chief sustainability officer, discusses how prioritizing human-first AI tools is supporting farmers and agronomists with benefits like earlier disease detection, precise resource use and resilience amid unpredictable agricultural landscapes.

1. First things first: When we are talking about prioritizing "human-first AI," what does that look like in the context of a farmer's day-to-day decisions?

Andrew: I mean AI that starts with the farmer, not the technology. For a farmer, the day-to-day reality is deeply practical. Their decisions are made in real time, often under pressure. AI can help make those decisions simpler, faster and more informed, while keeping the farmer and their agronomist in control.

• An example: Our AI Agronomy Advisor is designed as a mobile, role-based platform built around PepsiCo crop varieties and growers' workflows. The aim is to turn field observations into actionable recommendations.

Imagine a PepsiCo agronomist walking a field with a farmer, and they see an unhealthy leaf. The agronomist can use the tool to help quickly identify the likely issue, assess severity and determine a practical next step.

That is what human-first means to us:low-burden tools, designed for the field, that help farmers stay productive and profitable while using resources efficiently.

2. Take note: What have the reactions from farmers been, and what is a barrier to adoption that you have encountered?

Andrew: The response from farmers is, "Will this help me make a better decision, save time, reduce cost, protect yield, or lower risk?" If the answer is clear, adoption becomes much easier. Farmers are looking for tools that work in their specific crop, on their land, in their climate, and in the time window they must make decisions.

We've seen strong engagement when AI is paired with trusted agronomists, local context and a clear economic benefit. But there are barriers to adoption:

• Trust: Farmers need confidence that the recommendation is accurate and relevant to their farm.
• Data fragmentation: Farm data can sit in different systems, formats or notebooks, which makes it harder to generate reliable insights.
• Cost and complexity: If a tool requires heavy upfront investment, specialized hardware or too much administrative burden, adoption will be slower.

3. Key numbers: What measurable impact are you seeing from these new AI tools in terms of increases in yield, input costs or efficiency for farmers?

Andrew: Broadly, farmers we work with are using AgroScout in markets including Argentina, Brazil, Chile, China, Thailand and Vietnam. Across these contexts, reported outcomes include earlier disease detection, reductions in chemical use and more than 10% yield increases in some situations.

• Results vary by crop, climate, geography, farmer practices and the intensity of pest or disease pressure in each season. So, not every grower will see the same result every year.

4. More info: Can you share a concrete example of how this changed an outcome for a farmer or farmers that you have spoken to?

Andrew: One of the clearest examples comes from growers in Mexico using AgroScout. Through AI-enabled drone insights, they were able to detect pest and disease pressures up to seven days earlier.

• The technology helped generate a precise view of what was happening in the field, resulting in an approximately 10% reduction in agrochemical use.

5. Okay, but: How do you ensure the AI tools and recommendations can be applicable across different regions and crops?

Agriculture is inherently local, meaning a recommendation that works for potatoes in Egypt may not work the same way for potatoes in Mexico. So, the goal is to build a learning system that can adapt to local conditions while still benefiting from scale.

PepsiCo does that by:

• Building around crop-specific and variety-specific knowledge.
• Pairing AI with local agronomy expertise.
• Using standardization to improve model quality.
• Scaling through pilots, learning loops and regional adaptation.

6. The challenge: What's the biggest sustainability challenge farmers are facing right now, and how do these AI tools help address it?

The biggest challenge is volatility. Farmers are facing more extreme weather, water stress, soil degradation, pest and disease pressure and input cost uncertainty. That makes planning harder and increases risk. Sustainability must be practical and help farmers stay productive, profitable and resilient over many seasons.

This links directly to regenerative agriculture. That's where AI can play an important role in helping farmers measure outcomes, target interventions, reduce complexity and improve results over time. That is why we see AI as a resilience strategy, not a technology strategy.

7. How it's done: What must happen to scale these AI tools globally?

Andrew: Scaling AI in agriculture takes much more than deploying software, tools or models.

1. The tools must be mobile-first, role-based, intuitive, available offline where needed and embedded into existing workflows.
2. The data must be standardized, validated and interoperable.
3. There must be local delivery networks, because adoption happens through trust, training and repeated use.
4. Financing and risk-sharing models must help farmers adopt new tools and practices without bearing all the transition risk themselves.
5. There must be governance and safeguards to ensure the recommendations are transparent, tested, regionally relevant and used with human oversight.

8. Looking ahead: What are the biggest ROIs on AI tools, from both the farmers' and PepsiCo's perspectives?

Andrew: For farmers, the biggest ROI is better decision-making that improves profitability and resilience.

That can show up as: reduced costs, earlier detection, better use of water and fertilizer, reduced chemical intensity, protected or improved yields and less uncertainty. Those are meaningful outcomes because they connect sustainability directly to farm economics.

For PepsiCo, the ROI is supply resilience, productivity and progress against our sustainability ambitions.

• We source more than 50 crops and ingredients across more than 60 countries, so the health of farming systems is directly tied to the health of our business.

Andrew: AI helps align sustainability with business performance. It can make climate risk more visible, efficiency more actionable and resilience more measurable.

That is the unlock — not AI as a standalone tool, but AI as a systems-intelligence layer across agriculture, operations and the supply chain.

Explore PepsiCo's strategy.