In a booming yet productivity-challenged construction sector, AI and technology offer innovative solutions like generative scheduling and agentic value engineering. But what does it take beyond the tech? Leadership buy-in and organizational adaptability are crucial for a successful transformation.
This transcript has been edited for clarity.
Why has productivity been stagnating in the capital projects and construction space?
John Parsons: The imperative for productivity in capital projects is greater now than it has been for the past 20 years. We’re seeing an unprecedented boom in construction and new capital projects across industries.
Erikhans Kok: At the same time, there are some real challenges: productivity has been lagging, we see a rise in labor shortages, and capital projects continue to be difficult to execute. Projects tend to go over cost and over schedule. Additionally, there are many contractors involved and so developing and delivering projects has gotten more complex and more competitive.
Johanna Hoyt: Capital projects are still fundamentally running on fragmented workflows, disconnected data, and reactive decision making. The complexity in capital projects has increased, but the operating model hasn’t changed.
Can technology and AI flip the script?
Mark Pitcher: Absolutely, we’re applying technology and AI into the way that we work to improve productivity on these capital projects—from building your initial business case, optimizing your design, improving the way you plan and schedule to executing the work in the field.
Johanna Hoyt: With technology, we’re now able to bridge and connect disparate sets of data within capital projects. Teams can leverage that data and understand the implications in a way they weren’t able to do before and they start to make better informed decisions.
John Parsons: Skilled labor is scarce. Going forward, good planners will spend their time revising and updating plans instead of writing them from scratch. We will have more granular work plans, with technology allowing for greater transparency, data, and dashboards. And with AI agents on top, we can identify where issues are coming up much better.
Which technologies will bring the biggest impact?
Erikhans Kok: One solution is generative scheduling. It takes all the schedule information, combines it with real-world constraints, like cost and labor inputs, and optimizes schedules for a variety of what-if scenarios.
Mark Pitcher: We used generative scheduling with one of our data center clients. They build many of the same projects repeatedly—and the more often you use an approach like generative scheduling, the more value you get out of it. For example, we were able to reduce the time to build a 50-60 megawatt data center from 24 to 16 months.
Erikhans Kok: Let’s also talk about agentic value engineering. This is a capability where companies optimize their designs using agentic capabilities for faster results. It includes a corpus of all previous engineering work which you can draw from to improve the current design, leading to much better designs and cost positions.
What are the key enablers to capture the opportunity that AI presents?
Erikhans Kok: On the one hand, it’s about the leadership buy-in. There needs to be real conviction within the leadership teams that this is a worthwhile effort to go after. Another reason is the organization’s ability to absorb the different way of working, and this is where we see real challenges because asking people to change is difficult.
John Parsons: It’s thinking about how the work gets done, where the real value and the real opportunity is, and then applying the tools to that. Beyond the technology, we also need to bring in our expertise around capability building, change management, and culture change in order to get people to adopt the technology and benefit from it.
Johanna Hoyt: The time is now to really change the way we deliver these capital projects and jump on the opportunity that’s ahead of us.
