We know that AI is changing many aspects of modern business, but how could it improve project management offices? Let Rick Morris count the ways.
Through six books (so far) and hundreds of articles and podcasts, Centric Consulting’s Project Management Office (PMO) Lead Rick Morris helps project managers master their field. He has presented dozens of innovative ideas for answering the age-old project manager question, “How do I demonstrate the value of my work?”
For example, in his 2008 book “Project Management That Works“, he has a chapter titled “Real Risk Assessment.” Rather than presenting vague calculations of risk like low/medium/high, real risk assessment painstakingly turns lessons learned into actionable activities to prevent future risks.
By his own admission in the book, this process — while immensely valuable if done well — is tedious and can be difficult to understand for project managers and team members.
But that was 17 years ago. Now, AI is catching up to Morris’s visions, making a real risk assessment more feasible and much richer, because AI can quickly mine years of historical data that otherwise would go untapped.
However, a real risk assessment is only the tip of the AI-PMO iceberg. I talked with Morris about the other ways AI can help project managers and why Centric is committed to its potential to taking PMOs to the next level.
How does AI help with project management?
AI enables the next level of PMO that we’ve always dreamed about but never had the time, effort, or ability to do. With AI, we are finally catching up to ideas I’ve been pursuing and writing about for decades.
AI can make lessons learned truly actionable, rather than documenting them and filing them away, providing specific guidance to project managers based on past experiences within their organization.
For example, it can analyze project intake forms against historical data to identify similar past projects and potential risks, which helps teams avoid repeated mistakes. AI can also help ongoing projects course-correct by identifying similar patterns from past projects and suggesting interventions.
Perhaps most importantly, AI can help quantify the value of PMO activities — like calculating the savings from canceling a project early rather than letting it fail after significant investment — providing concrete ROI metrics that have traditionally been difficult to demonstrate.
How can AI help with risk assessment?
AI is revolutionizing risk assessments by transforming lessons learned from static documents into actionable insights.
Traditional risk assessments result in a simple high/medium/low rating or even numerical scores without meaningful follow-up actions. My idea of the real risk assessment now uses AI to mine historical lessons-learned data and create intelligent questionnaires that not only identify risks but also provide specific mitigations based on past project experiences.
For example, if you’re buying vendor software but haven’t seen a demo, AI could quickly pull up past project failures that lacked software demos and use that data to project leaders to schedule a demo immediately.
AI can also quantify the financial impact of risks by analyzing documents like budgets and change requests. Most organizations have three to 10 years of unused lessons learned data stored in spreadsheets or SharePoint.
AI can extract value from this “sunk cost” of unused data by training models to understand patterns and impacts. This helps project managers benefit from institutional knowledge, even if they’re new to the organization.
Project management comes with a lot of routine, related tasks, like setting up and holding meetings. Teams offers some tools to help do those tasks more efficiently, but what does AI add?
AI offers powerful capabilities for meeting management by extracting insights from data that platforms like Microsoft Teams already collect. Teams knows who was invited to meetings, who attended, when they arrived, and what was discussed.
AI can analyze that data to track attendance patterns, identify which team members might be overloaded, and automatically generate meeting minutes and action items — tasks most project managers still do manually.
Beyond basic automation, AI can also provide higher-level analytics about meeting effectiveness. It can even calculate the cost of meetings by analyzing attendance and the time spent on each topic.
By comparing that data against outcomes, like key decisions made, AI helps teams optimize their meeting practices and potentially reduce wasted time.
One example would be RFP-related meetings. AI analysis can help teams determine which projects they are likely to win or not win, which could lead to better qualification processes and significant productivity gains across an organization.
What other benefits does AI have for project managers?
AI demystifies complex processes and makes those accessible to project managers. In addition to meetings, I use it for everyday tasks like finding Excel formulas. I simply explain what I’m trying to do, and AI not only provides the formula but also explains it in plain language. That means I’m learning the why behind formulas without spending time writing them. That frees me to focus more on higher-value work.
However, I believe AI’s greatest benefit is that it enables project managers to create and track metrics that quantify the value of their activities. This data-driven approach helps PMOs demonstrate their value to the organization in concrete terms.
For example, if you can say to your project sponsors, “Our PMO saved $47 million,” and they ask, “How on earth do you know that?” you can use AI to show them exactly where those savings came from.
This shift from subjective to quantifiable value could significantly elevate the strategic importance of project management within organizations.
What’s next for AI and PMOs at Centric?
In general, our strategy for AI is to embed it into all our offerings. We see it as less of a standalone tool and more of a way to optimize everything we offer to our clients.
For our PMO consulting and PMO-as-a-service capabilities, we are currently prototyping an AI-driven PMO and starting to work with a few forward-looking clients to bring proofs of concept into their environments.
Our goal is to help them optimize lessons learned, brainstorming, price estimations, and real-time course corrections. I am excited to start exploring and sharing what’s possible when you merge AI technology and PMOs.