You’ve probably heard the buzz about AI in Project Controls—but it’s more than hype. Artificial Intelligence is no longer the future of project controls—it’s rapidly becoming the industry standard.
From real-time performance monitoring and smarter risk analysis to predictive forecasting and automation, AI is already transforming how projects are planned and managed. Yet many project teams are still stuck comparing budget to actuals, generating delayed reports, and relying on instinct instead of insight.
The truth? AI is already at work around us—and the professionals who understand how to use it will be the ones leading the next era of project performance.
That’s why we hosted a powerful conversation with John Hollmann —one of the world’s most respected thought leaders in cost engineering and project risk—to talk about what AI means for project controls, what’s already here, and what’s coming next.
John has over 35 years of experience, is the founder of Validation Estimating and ValidRisk, and is best known as the “father” of the Total Cost Management (TCM) Framework. He’s also the author of the influential book Project Risk Quantification and has helped shape AACE’s recommended practices and international standards in project controls.
In our conversation, John gave a fascinating look at how AI is transforming our field—and offered a clear message: the change is real, the tools are here, and it’s time to get ready.
Let’s unpack it.
🎥 Watch the full interview with John Hollmann below
A Quick Look Back: Where AI in Project Controls First Intersected
AI and machine learning (ML) may feel new to many of us—but John reminded us that the foundations were laid decades ago.
“Regression analysis was the original machine learning. We just didn’t call it that.”
In the 1980s and 90s, project teams were already applying statistical analysis to large datasets—using regression models to predict costs based on scope characteristics. It was manual, slow, and required analytical expertise, but the principle was the same: learn from historical data to predict the future.
The difference today?
AI can do this automatically, faster, and with greater accuracy than a human ever could. That’s the game changer.
We no longer need to run separate regressions one at a time. Machine learning models ingest entire datasets and identify hidden patterns without us needing to predefine the drivers.
So What is AI in Project Controls?
AI—short for Artificial Intelligence—isn’t a robot walking across your jobsite. It’s the ability of machines to perform tasks that typically require human intelligence: analyzing data, spotting trends, making predictions, and even adapting behavior over time.
In project controls, this means AI can:
- Analyze thousands of data points for patterns
- Predict project cost or schedule outcomes
- Improve forecast accuracy by continuously learning from project data
- Flag early warning signs of delays or overruns
- Reduce manual reporting by automating insights
- Recommend corrective actions based on past project behaviors
- Support scenario planning by simulating “what if” changes to scope, schedule, or cost
- ….
But here’s the thing: AI can’t do any of this without data.
The Bottlenecks in Leveraging AI in Project Controls
⚠️ Project Data That’s Not Ready
While the potential of AI is exciting, John emphasized a hard truth:
“Most project teams don’t have the structured data AI needs to learn from.”
And that’s a problem.
Years ago, many owner organizations—especially in industries like oil and gas—maintained robust databases of quantities, hours, costs, and durations. These datasets were essential for benchmarking, risk modeling, and performance analysis.
But over time, widespread outsourcing, inconsistent coding practices, and fragmented systems have eroded that foundation. Today, many organizations are left with unreliable actuals, incomplete quantities, vague progress metrics, and disjointed WBS and CBS structures.
Without clean, consistent, and structured data, AI becomes nothing more than a marketing slogan.
Before investing in any AI-related tools or initiatives, teams must first:
- Standardize their cost and schedule structures
- Clean and validate historical project data
- Capture actuals and progress consistently
- Store data in formats that support analysis and automation
This isn’t the glamorous part of digital transformation. But it is the most important part. Because without a strong data foundation, there’s no AI future.
⚠️ The People Problem: Silos, Skill Gaps, and Missed Opportunities
Even with good data, success with AI isn’t guaranteed—because people play a critical role.
John pointed out that most project organizations are structured in a way that separates domain knowledge from data expertise.
Estimators, cost engineers, and schedulers understand the project—but not how to build models. Data scientists and IT teams know how to code—but not what matters in a construction estimate.
“You can’t expect a data scientist to become a project controls expert—or vice versa. You need both at the table.”
That means building cross-functional teams that combine:
- Domain expertise (project controls professionals)
- Analytical skills (data engineers, statisticians)
- Business leadership (to champion innovation)
These teams must work together to define what problems AI should solve, how performance is measured, and what decisions the data should support.
Without this collaboration, AI efforts will fall flat—no matter how advanced the technology.
AI in Project Controls Is Coming Faster Than You Think—Will You Be Ready?
Let’s be honest: most project professionals didn’t see this coming so fast.
Artificial Intelligence is no longer just for Silicon Valley. It’s moving rapidly into the engineering, construction, infrastructure, and energy sectors—and it’s already redefining how projects are planned, monitored, and controlled.
AI is no longer a “nice to have.” It’s becoming the backbone of how leading companies:
- Quantify risk with more precision
- Forecast cost and schedule performance in real time
- Monitor progress with fewer blind spots
- Make faster, more confident decisions
Once AI becomes embedded in day-to-day operations, the gap between early adopters and laggards will grow fast.
John Hollmann was clear about the stakes:
“You don’t need to implement AI tomorrow. But if you wait until everyone else has already done it—you’re going to be playing catch-up.”
This is your heads-up.
While many organizations are still cleaning up spreadsheets and arguing about reporting formats, others are feeding structured data into models that flag issues before they become problems.
If you’re still relying on monthly reporting cycles, gut feel forecasts, or performance metrics that tell you what already went wrong… you’re not leading. You’re reacting.
Not Sure Where to Start? Here’s Your Action Plan
John didn’t just issue a warning—he offered a practical roadmap for project professionals and organizations who want to get ready:
Step 1: Fix Your Foundation
Before you can apply AI in Project Controls, get your house in order. That means:
- Cleaning your cost and schedule data
- Aligning your WBS and CBS structures
- Capturing actuals and progress consistently
- Storing data in accessible, structured formats
Step 2: Build the Right Team
You don’t need to do this alone—but you do need the right people:
- Project controls professionals who understand the field
- Data experts who understand modeling and AI
- Business leaders who can remove barriers and sponsor change
Step 3: Start Small and Focused
Don’t wait for a massive digital transformation. Run a small pilot:
- Automate a repetitive report
- Use historical data to test a forecasting model
- Try scenario simulations on a complex project
These early wins build trust, improve skills, and generate momentum.
Step 4: Learn the Language
You don’t need to code—but you do need to understand what AI is, how it works in project controls, and how to communicate effectively with data teams and leadership.
The future belongs to those who can translate between project performance and predictive insight.
Unlock the Power of AI in Project Controls—Without Becoming a Data Scientist
You’ve seen the trends. You’ve heard the warning signs. And now you know what it takes to get ready.
But if you’re like most project professionals, the hardest part is knowing where to begin.
That’s why we created a step-by-step practical training to help you bridge that gap—from understanding to application, from curiosity to capability.
The Applied AI in Project Controls Training Program walks you through everything you need to know to lead (or support) AI-driven transformation in your role—without getting lost in tech jargon or theory.
About the Author, Shohreh Ghorbani:
Shohreh Ghorbani is a dynamic and accomplished professional in the field of project controls. With an extensive background and expertise in project controls, she has been at the forefront of driving excellence and innovation in the industry.
As the founder and technical director of Project Control Academy, the leading global provider of practical online training programs in project controls, Shohreh has made it her mission to empower professionals and organizations with the knowledge and skills they need to succeed in project controls. Her passion for education and continuous learning has led her to develop comprehensive training programs that cater to the diverse needs of project management professionals worldwide.
Renowned for her captivating and dynamic approach to teaching, Shohreh has garnered acclaim and widespread recognition in the realm of project controls education.
Beyond her professional achievements, Shohreh is deeply invested in building a strong community of project controls professionals. Through her leadership, she has fostered a collaborative environment where individuals can connect, share insights, and support each other in their professional journey.
With her unwavering dedication, expertise, and commitment to excellence, Shohreh Ghorbani continues to inspire and empower project management professionals worldwide, leaving a lasting legacy in the field of project controls.
Meet Shohreh at Project Control Academy or connect with her on LinkedIn.
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