Project Manager With 30+ Years of Experience Shares How He’s Deploying Microsoft’s AI Copilot Across His Organization
Experience: Jeff Chamberlain has over 30 years in project management, covering various domains including FinTech and IT.
AI Adoption: AI is transforming project management, enhancing tasks like writing plans and managing communications.
Microsoft Tools: Chamberlain emphasizes Microsoft 365, particularly Outlook, as vital for efficient project management workflows.
Project Insights: Recent projects utilized Microsoft Copilot, demonstrating practical applications and training benefits for teams.
Future Roles: AI will shift project management roles toward relationship management and overseeing AI outputs, fostering collaboration.
With over 30 years of experience, Jeff Chamberlain has seen project management tech evolve from simple spreadsheets to AI.
We caught up with him to understand how this PM veteran is rethinking rituals and deploying AI across his organization.
Here’s what he had to say.
Unlock for Free
Create a free account to finish this piece and join a community of forward-thinking leaders unlocking tools, playbooks, and insights for thriving in the age of AI.
Already a member? Log In
30+ Years of Experience in Project Management
I’ve been a project manager for over 30 years across domains like FinTech, Healthcare, IT, telecommunications, and even Outdoor Adventure. I’ve also been an authorized training partner for PMI.
Right now, I’m the Manager of Broadband and Enterprise Projects for the Frederick County Maryland Government. I supervise a staff of project managers inside our IT department and oversee how we manage delivery across many divisions.
I’m responsible for strategy and governance — but I still manage projects myself, too.
A Project Manager’s Day-To-Day Use of AI
First, a clarification. We’ve been in the AI era really since we became “good” at the hive data mind that is the internet.
Furthermore, while AI has certainly become more sophisticated, it is neither “artificial” nor “intelligent.” It’s just an advanced data model — with a more natural language query interface.
All of this has been around for a while. The difference, now, is that we’re finally getting the tech closer to the non-technical user and making it accessible.
That said, I use it a lot — particularly with some of my more challenging tasks:
- Writing project plans
- Reviewing legal documents (contracts, SOWs)
- Managing my inbox
- Crafting scripted responses for repetitive requests
- Building out requirements
- Polishing my own documentation set
It’s powerful. But I still insist on a human review, as a rule.
Automating Project Management Processes in Municipal PMOS With AI
As far as my organization, as much as we prefer not to use AI as a super search tool, our reality is that municipal PMOs often play a little “catch-up” to our private sector counterparts for multiple reasons.
But we automate several items in our process — things like:
- Onboarding
- Project approval
- Project launch
- Notifications
I’m a big fan of automating those repetitive tasks, but anything requiring a review or oversight needs our eyes on it. It is a “trust but verify” process.
With AI, trust but verify. That’s the process.
Using the Microsoft 365 AI Stack for Project Management
We currently rely heavily on the Microsoft 365 product stack.
In the last two years, I have been slowly increasing our SmartSheet footprint in the county and using some of its AI tooling, which primarily focuses on formulary and sheet development.
And I'll go back to the basics here and say that my favorite AI tool by far is Outlook. I appreciate that more tools are being integrated, but you cannot beat Outlook for communications, setting reminders, categories, flags, conditional formatting, and many, many other features.
In fact, I have something I refer to as “the boss rule.” It highlights my emails using conditional formatting when I’m the only one receiving an email from my boss. It calls my attention.
Outlook is an extremely underrated tool in a time of instant messaging, texts, and chats. And its AI, via Copilot, is incredibly helpful.
Case Study: Piloting Microsoft Copilot for Project Planning and Training
In my organization, we have a bit of a hybrid management setup. While I might be a project manager in charge of the PM team, I’m also a division manager, so it’s a bit of a unique role.
I had the opportunity to run a highly visible project deploying Copilot (Microsoft’s AI tool) to a pilot audience — a Copilot pilot, if you will. We used the tool for several aspects of project planning.
I took the opportunity to help train a very skilled project team in some project fundamentals. We then used Copilot to help write the project plan, including the proper formatting of risks and issues, and our executive summaries. In fact, it created the initial draft.
Then, one of our SMEs used the tool to help script and edit the training that we delivered. This training was delivered to our pilot group, which included several senior county executives.
Throughout the project, we held office hours where we taught prompt engineering and troubleshot various issues that came up during the pilot. We found many unique use cases. I took a lot of pride in that I was a significant source of these use cases.
Finally, at the end of the project — incorporating community feedback collected throughout the pilot — one of the department managers built out a very detailed project report on our findings with the tool. Impressive work.
Overall, it was a significant project success, and I’ll be discussing it for years to come.
Building a Scoring System With Microsoft Copilot
I also used Copilot to help build a system that uses independent values for scoring a project into one of four categories of increasing complexity.
It's necessary because we get a lot of requests, so scoring and ranking are very important.
This, combined with a similar approach to ranking and incorporating a human element, has allowed us to, at the very least, identify where our resources are being pulled.
How Writing Better AI Prompts Mirrors Agile User Stories
One of the most useful things I’ve learned is the value of a well-engineered prompt.
For instance, you can take a risk that has been identified, then use a prompt to ask for expert advice:
“We have identified an increased vulnerability to unauthorized access due to the absence of multifactor authentication. What would Kevin Mitnick (known hacker turned industry expert) suggest we do to mitigate this risk? Please provide not only examples of impact but also at least three mitigation strategies.”
That kind of prompt structure — specific, contextual, action-oriented — feels a lot like writing a good user story.
Here’s an example of a recent prompt I wrote:
“Draft an email to inform stakeholders about a [project delay/scope change/budget increase]. The email should:
→ Acknowledge the issue honestly.
→ Explain the cause concisely.
→ Propose a solution or mitigation plan.
→ Provide a revised timeline, if applicable.
→ Offer to discuss further if needed.”
It’s been helpful. But anything that requires judgment or oversight? That’s still on us.
Blending Agile and Traditional Project Management Methods
Speaking of user stories, we aren't fully Agile.
I’m pushing for a bit of stasis in my project world right now. I’ve seen some very good projects using one of the many Agile choices of methodologies, but there is a concern over implementation, and defining "done".
I love the user story aspect of requirements, and I try to incorporate those — along with a rapid change approval process. And I’m a huge fan of the retrospective.
While not pure Agile, it certainly defines “hybrid.”
How AI Is Reshaping Project Management Roles and Teams
I hear this one from younger project managers a lot — "Is AI going to take my job?" It can be a scary world when, less than three years ago, this was niche tech outside of high-end labs. Now it’s on your phone.
My response is always: "If you don’t understand something, you probably shouldn’t be working in it."
Looking ahead, I have a few predictions:
- The project manager’s role will pivot into a more human-centered role. In other words, we no longer manage tasks; we manage the relationships in a project. We also provide oversight to the AI language model output.
- We, as project managers, will need to coach our teams on not just working with each other, but also with AI.
- Project teams will look different. Perhaps we’ll see “Pods” of expertise supplemented by AI tools that allow us to have multiple opinions on best practices and focused decision-making.
- The role of the Agile user story will become more relevant, as — if you break it down — a well-engineered AI prompt is pretty identical in form to a user story.
The project manager’s role will pivot into a more human-centered role. In other words, we no longer manage tasks; we manage the relationships in a project. We also provide oversight to the AI language model output
Advice for Delivery Leaders Adopting AI in Project Management
Don’t run down the hill. The technology is still being hammered out. Look at your organizational pain points and start there.
Keep asking yourself:
- “Does this need automation/AI?”
- “Is this really something we should scale?”
If you’re looking at one-and-done type tools, operations, or projects, maybe automation or AI isn’t the right fit.
Follow Along
You can follow Jeff’s work via LinkedIn as he continues exploring and implementing AI-driven systems inside Frederick County Government.
More expert interviews coming soon on The Digital Project Manager.
