I was able to build my network as well. The PMP helped me professionally in my career but also expanded my network tenfold.

Building new skills after the PMP

You later earned your PMI-ACP and PMI-PMOCP. What made you continue adding to your skill set?

My PMP certification renewal was coming up. I thought the PMI-ACP would be a good renewal opportunity but also help me professionally. I was not as familiar with agile approaches, and I was typically doing waterfall up until that point. Once I started studying for the PMI-ACP, I thought, “This way of working is just fantastic. I can implement some of these methods into my daily work.”

I’m still using those agile practices today.

Then I earned the PMI-PMOCP in the past couple of years. Once I learned that PMOGA was being acquired by PMI, I thought that was very cool. I started looking into it more, and I had worked with fractured PMOs in prior roles up until that stage.

I discovered that there’s so much that goes on in the background to provide value for organizations with a PMO. It completely changed my mindset. To this day, I’m working to establish our PMOs even further, working with the respective PMOs under the Salesforce umbrella. That’s honestly helping my career even more.

So, PMI has done a lot for me.

How do you feel these certifications complement each other, especially with the PMP as your foundation?

It all intertwines. It’s the structure and having a way to approach any problem that I’m facing— whether that’s organizational, a stakeholder, an accountability standpoint or it’s risk analysis. I think all the certifications I’ve earned along the way have played a role in that in some way, shape or form. I can fall back on any of those learnings and come out ahead because of them.

Why AI requires a different project management approach

What made you feel like AI was a skill set you needed to develop?

Pure chaos. With the PMP, you have the knowledge you need to help tackle projects, but it’s such a new world. I knew there was something missing. Around the time PMI acquired Cognilytica, I achieved my PMI-CPMAI.

Going through the certification helped me learn the patterns of AI and identify other use cases for AI—what is valuable for organizations—and how to measure that value in the beginning of a project, not just toward the end.

And then from a data standpoint, data has always been a deliverable. But when it comes to AI data is the lifeblood of the project itself. So having a good understanding of data, explaining where data is coming from and why it has value is important.

When did you realize AI wasn’t simply another trend and was something project professionals needed to understand?

Almost immediately. It was knowing that, “Okay, we have to have a different approach.” The PMP provides a broad project delivery foundation, while PMI-CPMAI adapts and extends that foundation for the iterative, data-driven nature of AI initiatives. It’s identifying the gaps that were there initially: data readiness, not knowing if a model works until you try and then the idea of building in iteration.

It’s not just thinking long term, but doing short, very fast-paced types of work when it comes to AI projects and having more output. The end goal could be this huge, broad program, but being able to deliver it in different iterations is even faster paced, almost agile-like.

I think a lot of project managers miss that in the shuffle. So having a good understanding of that and realizing that it’s okay to go backward in the process—you don’t have to keep going to the next step just because that’s what the PMP said. You can go back and reevaluate and relentlessly reassess.

Why earn the PMI-CPMAI certification

What ultimately led you to choose PMI-CPMAI and pursue the certification?

If it was going to be a part of PMI, I knew that was a big deal for myself and project professionals everywhere. But it was hard trying to identify a program that delivered what I was looking for. PMI-CPMAI helped open that door, giving me the knowledge and confidence to move beyond simply staying informed about AI initiatives to taking a more active role in the conversations shaping them.

How PMI-CPMAI complements the PMP

How do you feel PMI-CPMAI complements the PMP?

The PMP taught me to deliver what’s asked, but PMI-CPMAI helped me figure out whether what’s asked is the right thing to even build and how to build it when the answer is not known upfront.

Why do you think project management and AI are such a powerful combination?

It’s the future. I think it’s going to be ever-changing for at least the next five to 10 years. We’re the ones that help guide the projects, and right now it’s a brand-new venture.

When it comes to AI, expectations are all over the place. There’s a lot of opportunity here for project managers to step up, increase their AI literacy and become one of the voices in the room—not just listening to what’s happening, but being able to speak to what’s going to be valuable for not just the project itself, but for the organization overall.

How PMP and PMI-CPMAI work together

How do the PMP and PMI-CPMAI work together in practice?

I think there are a lot of similarities. For example, the intake, approval process and reporting discipline behind what expectations are. But I think PMI-CPMAI adds the extra gates to that, especially when it comes to data and identifying what the actual problem is right off the bat.

Is it data-ready? Where is the baseline? Those ideas will flow in like a problem statement, and that’s okay for standard projects. But when it comes to AI projects, you need a little more depth than that.

So, helping the business define whether a suitable solution is the best route and then the clear business value, I think that’s where it helps separate regular projects from AI ones.

Managing AI effectively and responsibly

How are you making sure you’re implementing AI effectively and responsibly?

Governance is our number one. We’ve got review processes every step of the way. It’s doing it against an established body of knowledge, so being able to measure it up against that and have structure surrounding that has paid dividends for us.

For example, we found gaps in our review process by measuring it against an established framework and fixed them. We wouldn’t have known about that had we not put it up against the governance framework. We identified what the mismatches were and were able to fix that to make it more successful cross-functionally. And then it turned into more concrete intake changes.

Where project professionals can create value with AI

Where do you see the biggest opportunities for project professionals to leverage AI today?

The intake and prioritization of it. Being able to define business value right in the beginning will pay huge dividends for project professionals moving forward.

Project professionals will also help lead the adoption. I think that’s probably the biggest. A lot of companies—their team members are slow to adapt because, one, they may not be familiar with AI, they’re worried about job security or whatever that might be. But having project managers provide use cases of what can and can’t be done with AI, the uses of it and being those early adopters is great for other team members to see.

I think project professionals already have that mindset. It’s just that working with AI, and PMI-CPMAI helps give you that additional advantage. And it’s another confidence boost. It’s a whole new world, and it’s like restarting my career again. So, it’s very exciting.

How AI changes the project management mindset

How does managing AI change the way project professionals need to think about a project after launch?

With the PMP mindset, you should deter away from unnecessary change, whereas PMI-CPMAI almost encourages any changes that take place because that’s just part of the project and the mindset you need to work with. Change can be good in a way because these models are always going to need to be updated.

I think a lot of project professionals have a mindset where they get to a release and that’s the finish line. AI is almost completely different to me. That’s almost the starting line because you’re going to have to reassess what these models are doing and who’s accountable for them.

We have team members moving around in the organization all the time, so maybe the stakeholder that was overseeing that and the sponsor of that project have moved on to different roles. So now who’s going to take that? You’ve got to take that into consideration.

And then with all the AI advances that we’re seeing, any changes you make to those may affect something downstream, so you’ve got to be conscious of that.

I think this framework helps provide those project managers with an extra advantage.

Tips for studying for project management certifications

You’ve studied for quite a few certifications. What tips have helped you?

Being intentional about it, not just doing it very passively. If you’re going to dedicate time, make sure that time is absolutely dedicated to what you’re studying. Treating it as a project helped me out. And then if you have a spouse or a family that is very supportive of it, that works out in your favor every time.

How project professionals can help drive AI adoption

What lights you up about the work you do?

Watching people go from nervous to excited about AI. I get excited about this stuff, like when there’s a new tool or new advantage that comes out. Salesforce just launched Claudeforce—a strategic partnership and integration announced by Salesforce and Anthropic in August 2026 that embeds Claude’s reasoning and AI models directly into Salesforce’s data, workflows and governance—and we’re in the very beginning pilot stages of that. But seeing what it can and can’t do is just so exciting.

Leading those adoption efforts and watching people light up themselves once it finally clicks—that’s the best part of it all.

Tags: PMP | PMI-CPMAI | AI | Project Management

Quick answers to common questions about managing AI projects

How does PMI-CPMAI complement the PMP?

PMP develops the skills to lead projects, manage stakeholders and deliver value. PMI-CPMAI builds on that foundation by addressing considerations that become especially important in AI projects, including data readiness, experimentation, iteration, governance and determining whether an AI solution is the right solution to build.

Do AI projects require a different project management approach?

AI projects can require project professionals to work differently because the answer may not be known at the beginning. Data readiness, experimentation and iteration can require teams to reassess decisions throughout the project rather than follow a strictly linear path from planning to delivery.

Why do project managers need AI skills?

As organizations adopt AI, project managers can play an important role in connecting AI initiatives to business value. AI literacy can help them ask better questions, prioritize use cases, guide stakeholders, support responsible implementation and help teams determine where AI can create meaningful value.

What role can project managers play in AI adoption?

Project managers can help organizations identify and prioritize AI use cases, define business value, coordinate stakeholders and support adoption. They can also help teams understand what AI can and cannot do and provide structure as AI initiatives move from an idea through implementation and ongoing evaluation.

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