AGCO wanted employees to use AI in a **governed, secure way**, not through disconnected tools and shadow IT. Employees were already working every day in **Microsoft Word, Excel, PowerPoint, OneDrive, and SharePoint**, so choosing **Microsoft Copilot Studio** for agent creation and **Microsoft 365 Copilot** for productivity meant they could:
- Work inside familiar tools instead of learning entirely new platforms.
- Keep data and workflows within enterprise security and compliance boundaries.
- Pair **citizen development** (non-technical makers) with expert support from AGCO’s AI leaders and Microsoft specialists. As AGCO’s CDAIO Todd Bailey put it, the goal is **not to experiment with AI for its own sake**, but to apply it where it matters most—helping AGCO **move faster, reduce friction, and support better decisions** for farmers and customers. This approach lets AGCO reimagine how work gets done while maintaining clear governance, measurable ROI, and alignment with real business needs.

AGCO treats **AI literacy and governance** as the foundation for scaling agents. Key elements of their approach: 1. **Start with volunteers and literacy** At a leadership meeting with about **2,200 people**, AGCO asked who wanted to build agents—**around 900 employees** immediately volunteered. Training started the next day, and a **maker community in Microsoft Teams** was set up so people could ask questions and help each other. 2. **Pair citizen makers with expert support** AGCO’s AI leaders and Microsoft specialists work alongside teams. Employees bring **friction points and gaps** in their work; AI champions help shape the right **agent, automation, or workflow**. As Aryn Drawdy notes, the focus is not “How can AI help?” but **“Where are your friction points today?”** 3. **Governed path from idea to enterprise agent** AGCO is building an **agentic framework**, not one-off bots: - **Hundreds of citizen-built and team agents** are already in use.
- **Several hundred enterprise agents** are in production, with several hundred more moving through cohorts to be consolidated and optimized for enterprise use. 4. **Continuous expansion with control** The maker community has grown from the original **900+ makers to roughly 2,000** across AGCO. Licenses are requested, ideas are shared, and solutions are refined into **governed, business-ready deployments** rather than isolated experiments. This model lets AGCO scale AI agents quickly while keeping them **connected, governed, and aligned to real business outcomes**.

AGCO’s AI agents are reshaping how work flows across manufacturing, quality, supply chain, and sales by targeting specific friction points. Some of the most notable impacts include: 1. **Faster quality reviews in manufacturing** Previously, quality and warranty processes could stretch over **weeks or even months** as small expert teams reviewed issues, validated data, and aligned on next steps. With AI agents: - Some quality reviews have been cut **from weeks to about an hour**.
- Agents help **interpret, validate, and advance** quality issues more quickly.
- Expert knowledge is still central, but it’s easier to apply it where it’s needed, reducing delays and improving visibility. 2. **Smarter supplier and contract decisions** A **supplier agent** reads contracts and flags where AI suppliers could add value and potential savings over the next **one to two years**. This helps AGCO: - Identify cost-saving opportunities earlier.
- Make more informed decisions about where to apply AI in supplier relationships. 3. **More effective sales conversations with agronomy insights** An **agronomy agent** combines AGCO agronomy studies, sales guidance, and web content so sales teams can: - Connect specific agricultural issues to the right machines and solutions.
- Turn internal expertise into actionable guidance at the moment of customer interaction. 4. **Momentum across the business** AGCO now has: - **Several hundred enterprise agents in production**.
- **Several hundred more** moving through structured cohorts for optimization.
- A roadmap focusing next on **supply chain, product management, and customer acquisition** through 2026. Across these areas, the common thread is **turning expertise into accessible, in-the-flow-of-work intelligence**—helping teams move faster, reduce friction, and support better decisions for manufacturing teams and farmers.