In Microsoft Digital, the company’s IT organization, our journey to agentic AI has been an evolution—one that began with early experimentation in AI-powered productivity and has grown into a coordinated effort to enable intelligent, scalable solutions across the enterprise.
As AI capabilities advanced, we saw an opportunity to move beyond individual productivity gains and toward something more transformative: Empowering our developers to build intelligent agents that can automate workflows, streamline operations, and create new business value.
Realizing this vision required more than new tools. We needed to rethink how we foster development, govern innovation, and operate at scale.
“We’ve made a lot of progress enabling our developers to build agents that make us more productive. We’re Customer Zero at Microsoft, which means we’re the first to deploy and use the technology and services that we later sell to our customers. Those learnings give us a unique perspective and story to share about the journey our developers have been on with AI and agents.”
Brian Fielder, vice president, Microsoft Digital
Today, we’re sharing the foundation we built that supports this shift.
We’re driving employees across Microsoft to create and use AI agents—from simple, task-focused solutions to enterprise-grade applications available across the company. It’s all supported by a secure, governed, and extensible platform.
“We’ve made a lot of progress enabling our developers to build agents that make us more productive,” says Brian Fielder, vice president of Microsoft Digital, the company’s IT organization. “We’re Customer Zero at Microsoft, which means we’re the first to deploy and use the technology and services that we later sell to our customers. Those learnings give us a unique perspective and story to share about the journey our developers have been on with AI and agents.”
Within the context of Microsoft Build 2026, we’re sharing what it really takes to move from experimentation to impact. Through this collection of stories and resources, we highlight how we’re empowering our developers to build with agentic AI—from establishing governance and platform capabilities to driving adoption and delivering real-world outcomes. Our goal is to provide practical insights you can use to accelerate your own AI journey.
“We hope you find the journey we’ve been on practical and useful,” Fielder says. “When it comes to agents, we’re accelerating fast and scaling at an enterprise level. As our story continues to evolve, we look forward to sharing it with you.”
Guidance for developers: How we manage agentic AI at Microsoft
These articles outline our vision for agentic AI, showing how we’re building a secure, governed, and extensible foundation for AI agents—from Work IQ and Copilot Studio to Agent 365, Azure DevOps, and Model Context Protocol—so developers can create scalable, high-value solutions across the enterprise.
- How Work IQ is supercharging our AI usage at Microsoft
- Shaping AI management at Microsoft with Agent 365 and Copilot controls
- Deploying Microsoft Agent 365: How we’re extending our infrastructure to manage agents at Microsoft
- Unlocking enterprise AI extensibility at Microsoft with Microsoft Copilot Studio
- Powering AI value with Microsoft 365 Copilot extensibility at Microsoft
- How our employees are extending enterprise AI with custom retrieval agents
- Transforming our approach to sensitivity labels at Microsoft with Microsoft Entra
- Reclaiming engineering time with AI in Azure DevOps at Microsoft
- Protecting AI conversations at Microsoft with Model Context Protocol security and governance
UPCOMING POSTS
- Intelligence on tap: Our guide for How Work IQ enables Microsoft 365 Copilot to better understand how we work at Microsoft
- Our guide for deploying Agent 365 based on our experience at Microsoft
- Agentic modernization: Securing Python at scale for agentic AI at Microsoft
Our IT guide to becoming a Frontier Firm
These stories share our IT playbook for becoming a Frontier Firm, highlighting a practical path to enterprise AI maturity through agentic transformation, operational scale, responsible innovation, and partnership—showing how IT leaders can balance governance, modernization, and employee engagement while building an AI-first organization.
- Enterprise AI maturity in five steps: Our guide for IT leaders
- The agentic future: How we’re becoming an AI-first Frontier Firm at Microsoft
- AI at scale: How we’re transforming our enterprise IT operations at Microsoft
- Transforming into an AI-first Frontier Firm in partnership with our works councils
- Fast Train to the AI Frontier: Balancing risk and innovation in the era of AI at Microsoft
Working as developer in IT at Microsoft in the era of AI
These stories explore what it means to work in Microsoft Digital during the AI era, showing how developers and knowledge workers are reshaping engineering, the employee experience, and their own career growth through AI-powered tools, new ways of working, and personal journeys that reflect the evolving culture of IT at Microsoft.
- Powering the new age of AI-led engineering in IT at Microsoft – Inside Track Blog
- The Frontier Firm: How knowledge workers are forging their own AI tools at Microsoft – Inside Track Blog
- The future of work is here: Transforming our employee experience with AI – Inside Track Blog
- Olutunde Makinde: From Lagos to Redmond, a Microsoft IT engineer’s journey – Inside Track Blog
- Building from the inside: Anahit Hovhannisyan’s impact on IT at Microsoft – Inside Track Blog
Key takeaways
From our journey enabling agentic AI across Microsoft Digital, several key principles have emerged to help organizations move from experimentation to scalable, enterprise-wide impact.
- Treat your organization as Customer Zero. Use your own AI capabilities first to generate real-world insights, validate scenarios, and build credibility before scaling to customers.
- Build a foundation for scale. Establish a secure, governed, and extensible platform that enables developers to create AI agents—from simple solutions to enterprise-grade applications.
- Empower developers to drive transformation. Move beyond productivity gains by enabling developers to build intelligent agents that automate workflows and unlock new business value.
- Align governance with innovation. Rethink how you enable development, govern AI, and operate at scale to balance flexibility with responsible use.
- Connect tools, platforms, and workflows. Integrate AI capabilities across your ecosystem—linking platforms, governance models, and development tools to support consistent, scalable adoption.
- Translate experimentation into impact. Focus on turning early AI exploration into coordinated, enterprise-wide efforts that deliver measurable outcomes.
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