As the adoption of Generative AI grows inside the enterprise, automation is entering a new phase, one that blends decision-making, integration, and user interaction in real time. Enter Agent Flows from Microsoft Copilot Studio.
If you’re already building Copilot experiences (or have experience in other flow builders like Langflow or n8n), this new feature offers a promising way to add real-time automation into the conversation itself, without writing code or leaving your design environment. But let’s be honest: it looks like early days. While the potential is clear (and massive), documentation is sparse, and best practices are still emerging.
What is it?
Agent Flows are deterministic workflows built directly inside Microsoft Copilot Studio. Think of them as bite-sized automations Copilots can trigger during a conversation (or sit independently), complete with inputs, logic, and near real-time results.
Some early standout features:
- Natural language authoring: Describe what you want, and Copilot Studio drafts a flow.
- Drag-and-drop interface: Refine the logic visually, no coding required.
- Tight Copilot integration: Pass variables into a flow and return results nearly instantly.
- Monitoring built in: See run history, performance, and error handling, all within the same studio (even seeing the underlying JSON ‘raw inputs’ and ‘raw output’).
What does it mean from a business perspective?
For teams working on AI agents and automation, Agent Flows offer a new way to unify interaction and execution – but it comes with it’s own challenges.
Opportunities:
- In-chat automation: Add real-time decision logic right into user conversations.
- Low-code onboarding: Natural language lowers the barrier for non-developers.
- Cost-effective: No need for a separate Power Automate license, usage is covered under Copilot Studio capacity.
Challenges:
- Lack of documentation: It’s not always clear where Agent Flows errors originate or how to approach building them (having said that, skills and approaches from Power Automate flows may transfer).
- Early-stage feel: It’s promising but still has a maturing feel.
- Governance risk: Without clear guidance, it’s easy to end up with unmanageable flow sprawl.
What do I do with it?
Like most of the emerging toolsets, it’s a bit of an exploration.
- Explore the edges: Start by identifying agent behaviors, like simple processing (see further reading), that could be automated with flows.
- Try natural language: Just describe what you want to automate and see what Copilot Studio generates.
- Connect flows to your agents: Let your agents call these flows mid-conversation for near real-time decisions.
- Keep an eye on performance: Investigate the built-in analytics to refine and improve.
- Plan for governance: Even small automations need naming conventions and retirement plans to stay sustainable.
Agent Flows are a powerful, if under-documented, addition to the Microsoft AI toolbox. They’re clearly still evolving, but if you’re already in the Copilot Studio ecosystem, they’re worth experimenting with.
It’s not about choosing between Agent Flows and Power Automate, it’s about using the right tool for the moment. If you’re building conversational AI, Agent Flows are built for you. If you’re managing large-scale workflows across tools and teams, Power Automate is likely to be the tool of choice.
The tools are here. The use cases are waiting. What will you automate first?
Further Reading
Agent Flows in Copilot Studio – YouTube (Dhruvin Shah)
Introducing agent flows: Transforming automation with AI-first workflows (Sangya Singh)