AGCO scales employee-built AI agents with Microsoft Copilot Studio
AGCO Corp wanted employees to use AI safely instead of experimenting with disconnected tools outside enterprise governance. With Microsoft Copilot Studio and Microsoft 365 Copilot, AGCO enabled employees to become makers and build agents, pairing citizen development with expert support. AGCO is using agents to interpret, validate, and advance quality issues faster, connect context across design and supply chain systems, and support a growing portfolio of connected agents within an enterprise quality framework.
- Organization
- AGCO Corporation
- Industry
- Manufacturing
- Location
- United States
- Published
- July 2025
Reported outcomes
−97.6%
quality review timeTime & speed
Strategic outcomes
Catalog median for time & speed deployments: −60% across 727 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 3 of 3
- 1AI agents
- 2Workflow automation
- 3Quality management
- Employees were experimenting with AI outside enterprise governance, creating shadow IT risk.
- Quality and warranty workflows stretched for weeks or months because work depended on manual coordination and small expert teams.
- AGCO launched a governed citizen-development program using Microsoft Copilot Studio for agent creation and Microsoft 365 Copilot for everyday productivity.
- The company used Microsoft Teams to support a maker community, trained employees to build responsibly, and paired citizen development with AI leaders and Microsoft specialists.
- Agents were designed to bring the right context into workflows, connect data across design and supply chain systems, and move issues forward faster within an enterprise quality framework.
- Some quality reviews were cut from weeks to about an hour.
- AGCO grew from more than 900 makers to roughly 2,000 employees involved in building agents.
- The company has several hundred enterprise agents in production, with several hundred more moving through optimization cohorts.
- The program accelerated issue resolution, reduced reliance on constrained expert teams, and improved visibility in manufacturing workflows.
Sources & evidence1
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