Turning Requests Into Azure DevOps Work Items with Power Automate and AI

If you manage a backlog in Azure DevOps, you probably know this problem.

Not every request starts as a nicely written work item. A bug comes through support, an infrastructure request arrives over email, someone sends feedback in Teams, or a business team asks for a new service or capability.

Someone eventually has to take that information, understand it, clean it up and create the actual backlog item.

I recently came across a useful demo from Ritu Hooda from First Bank & Trust, presented during the Microsoft 365 & Power Platform Community call, showing how this can be automated using Microsoft Forms, Power Automate, AI Builder and Azure DevOps.

Watch the demo: AI-Powered Azure DevOps Work Items with Power Automate

How It Works

The flow itself is pretty straightforward:

Microsoft Forms → Power Automate → AI Builder → Azure DevOps

Microsoft Forms becomes the simple front door for the request.

Power Automate picks up the submission, while AI Builder takes the raw information and helps turn it into something more useful — including a proper title, description and acceptance criteria.

The flow then creates the Epic or Work Item in Azure DevOps and can notify the appropriate team.

So instead of asking everyone to understand Azure DevOps Boards and how your team writes backlog items, they simply explain what they need.

Think Beyond Development Requests

What I liked about this demo is that the pattern can go much further than a normal software feature request.

You could potentially use the same approach for:

• Bug reports coming from users or support teams

• Infrastructure requests such as environments, VMs or platform changes

• Feedback and improvement ideas from employees or business teams

• New service requests or capabilities that need evaluation

• Product or platform enhancements that eventually need to enter the backlog

For teams already using Azure DevOps as the place where work gets tracked, this gives people outside the delivery team a much simpler way of getting requests into that process.

Why I Think This Is Useful

Having managed service and platform backlogs, I've seen how much time teams spend converting emails, chats, and stakeholder requests into structured work items. That's why this pattern immediately caught my attention.

The interesting part isn't simply that AI can write a work item.

It's the elimination of the manual translation step that happens beforehand.

People submitting requests don't need Azure DevOps access or need to understand how an Epic, Feature or User Story should be written. The team receiving those requests gets more consistent information, while the backlog owner spends less time converting emails and Teams conversations into something trackable.

And importantly, creating the work item doesn't mean automatically accepting the request.

The product owner, service owner or delivery team still decides whether it belongs in the backlog, its priority, feasibility and what happens next.

AI is helping structure the request — not making the decision.

A Simple Pattern Worth Exploring

I think this is a useful pattern for any team already managing work through Azure DevOps but receiving requests from multiple channels.

Instead of:

Email / Teams / Forms → Manual cleanup → Azure DevOps

you can start moving toward:

Simple intake → AI enrichment → Azure DevOps → Team review

A relatively small automation, but potentially a useful one when you're handling a large number of requests.

Worth Checking Out

The demo is part of the ongoing Microsoft 365 & Power Platform Community Calls, which are open to the community.

Community Calls: aka.ms/community/calls

And if you're thinking of building something similar, this is also worth watching:

Power Automate Error Handling: Error Handling in Power Automate Flows | Try Catch Scope Action

Error handling matters here because you don't want a failed AI enrichment or Azure DevOps step to result in a request quietly disappearing.

For me, that's the real value of this approach — give people an easy way to tell you what they need, while automation takes care of turning it into something your delivery team can actually review and track.

I'm planning to try this out with my own team and see how we can tweak the pattern beyond the original use case — particularly for capturing different types of requests, ideas and improvements and turning them into structured, actionable backlog items. I'll share what I learn along the way.

Stay tuned for more updates...

Microsoft's Copilot Learning Center: A Practical Place to Learn Copilot

Microsoft has put together something genuinely useful for everyday Copilot adoption: the Copilot Learning Center.

Rather than another feature announcement or product overview, the Learning Center provides a practical collection of bite-sized tutorials showing how Copilot can be used across the Microsoft 365 apps people already work with every day.

If you've been exploring Copilot but aren't quite sure where to start, this is a useful place to begin.

What's Inside?

The Learning Center organizes guidance around familiar Microsoft 365 applications, using simple scenarios and everyday tasks.

Word

You can explore examples covering:

• Rewriting and improving existing content

• Turning information into structured tables

• Creating a cover letter using a résumé

• Summarizing longer documents

• Getting started with prompting

• Working with citations and references

• Improving grammar and spelling

• Creating outlines for speeches and other content

Excel

The Excel examples show how Copilot can help users:

• Build trackers and organize information

• Understand complex formulas in simpler language

• Analyze and visualize data more quickly

PowerPoint

The Learning Center also walks through how Copilot can assist with creating, designing and refining presentations — helping users move from an initial idea or source material toward a structured deck.

OneDrive

Copilot in OneDrive focuses on helping users work with the information already stored in their files, including:

• Summarizing files

• Comparing information across documents

• Finding and understanding relevant content

Outlook

For people spending a large part of their day in email, the tutorials demonstrate scenarios such as:

• Drafting emails from a few instructions

• Summarizing lengthy email conversations

• Using Copilot to make writing and reading email easier

OneNote & Designer

There are also examples covering everyday productivity scenarios such as creating a daily schedule in OneNote and generating images from text using Microsoft Designer.

Why I Think This Matters

A lot of Copilot conversations naturally focus on new features, agents and what AI could eventually do.

But adoption happens differently.

Users need to see small, relatable scenarios that help them do something better today.

That could be summarizing a long document, understanding an Excel formula, preparing a presentation, drafting an email or simply organizing information.

This is where the Copilot Learning Center becomes useful.

For organizations rolling out Microsoft 365 Copilot, it can also complement internal adoption programs. Instead of creating every piece of introductory learning material from scratch, teams can point users toward Microsoft's own scenario-based guidance and then build organization-specific training around the use cases that matter most to their business.

My Take

The Copilot Learning Center isn't about another major AI announcement.

It's about something much simpler: helping people actually use Copilot.

With practical examples covering Word, Excel, PowerPoint, Outlook, OneDrive, OneNote and Designer, it's a useful starting point for anyone looking to move from experimenting with Copilot to making it part of everyday work.

Access the Learning Center here: Microsoft Copilot Learning Center

AI Skills Navigator Is Now in Microsoft Copilot: Learning Comes to the Conversation

Microsoft has brought AI Skills Navigator directly into Microsoft Copilot. It looks like a small integration on the surface, but it points to a bigger shift in how AI learning could become part of everyday work.

I first covered AI Skills Navigator when Microsoft introduced it in 2025, and since then the experience has continued to evolve as Microsoft's approach to AI-powered learning has matured.

From Searching for Learning to Asking for It

The usual way to learn something new at work is to open a portal, search through courses, and try to figure out what's relevant. With AI Skills Navigator now inside Copilot, that becomes a conversation instead.

You can simply say what you want to learn, for example:

• "I want to learn how to build AI agents."
• "What should I learn to get started with Microsoft 365 Copilot?"

Copilot then helps connect that goal with relevant learning resources. The shift is simple but important: instead of searching for learning, you start by describing what you want to achieve.

Learning Becomes More Personal

Different people need different learning paths. A developer building agents, an IT admin managing Copilot, and a business user trying to be more productive all need very different things — a single learning path won't work for all three.

By understanding what someone is trying to do, AI Skills Navigator can point them to what's actually relevant, instead of leaving everyone to dig through the same large catalog.

Copilot Keeps Taking On More

There's a broader pattern here too. Copilot is increasingly becoming the place where people start their work with AI, rather than one more app they have to open separately.

Instead of Work, then AI, then a separate step for Learning, these are starting to blend together. You're working with Copilot, you hit something you don't know how to do, and the same conversation helps you find what to learn.

Why It Matters for Organizations

Rolling out Copilot and agents is only one part of the job. People also need to keep building the skills to use these tools well, and those skills keep changing.

Having AI help employees find the right learning, in the flow of their work, could make continuous skilling easier — especially as organizations move from general AI awareness to more specific skills around Copilot, agents, automation, development, and governance. It can also help learning move away from something people occasionally visit in a training portal, toward something that's simply part of the day-to-day.

Final Thoughts

Bringing AI Skills Navigator into Copilot is a small step in terms of access, but a meaningful one in terms of direction. Learning is becoming conversational — instead of asking "which course should I take?", you can start with "this is what I want to do, what should I learn?" and let Copilot help from there.

References

AI Skills Navigator is now available in Microsoft Copilot