Technology
Structured Data Positions Contractors to Take Advantage of AI Boom
Burns & McDonnell's Brett Poulos says firms seeking access to each other's data may drive more mergers and acquisitions
If contractors want to get the most out of artificial intelligence, Burns & McDonnell's Brett Poulos says they will have to clear a major hurdle first: organizing their data.
Poulos, national director of preconstruction and estimating at Burns & McDonnell, says structuring your data, establishing clear governance, training employees and conducting pilot programs before deploying new tools are what it takes to get the benefits of AI tools.
"Really, the backbone of several of our initiatives was to standardize and structure our data," Poulos says about his firm's AI efforts.
In a report published last month, McKinsey Global Institute says “AI is unlikely to be an extinction event for AEC firms, but it could meaningfully change who leads the industry. Early adopters are reporting productivity gains from design, modeling, and construction-feasibility workflows, though these advantages will likely soon be table stakes.”
It projects that the AEC industry could bring roughly $228 billion in annual value in the U.S. by 2030.
“As work becomes faster and cheaper to deliver industrywide, the leaders will be firms that use AI most effectively to control client relationships, workflows, and their underlying data,” it states.
With many contractors still in the early stages of adoption, Poulos says there are risks if companies plunge into implementing AI without establishing a proper foundation.
He says the first priority should not be purchasing the latest AI platforms, but to ensure that your data is organized in a way that AI systems can use it effectively.
“Until that data is structured, it’s very hard to manage and it’s very hard to leverage and ingest into an AI ecosystem or into your decision-making capabilities,” he says.
There are enormous amounts of information generated over the course of a project, including design documents, schedules, procurement records, cost estimates, progress timelines and operational data. Much of that data currently exists in separate systems.
Poulos says those disconnected systems limit the industry’s ability to use AI to make better decisions.
“We’re in an industry of making decisions,” he says. “Our ability to deliver projects is really based on the quality of those decisions, and the quality of data we provide back to our clients to help them make better decisions.”
Poulos says firms that can connect information across the entire timeline of a project, from design through construction and execution, will be best positioned to get the most out of AI.
As an example of a project in which Burns & McDonnell effectively used AI, he cites an animal health monoclonal antibody manufacturing expansion it is working on. Burns & McDonnell provided engineering, procurement and construction services for a multimillion‑dollar renovation while the facility remained in near‑continuous operation. Work took place under active USDA and EU regulatory oversight, adding another challenge to every decision.
Burns & McDonnell used reality capture, continuously updated models and AI-enabled progress tracking to identify potential issues earlier, better plan shutdowns, and reduce rework before it reached the field, he says.
Poulos says the push for more integrated data could impact the industry in unexpected ways, including a possible increase in mergers, acquisitions and strategic partnerships between contractors and design firms looking to tap into each other's data.
While he described that prediction as a “hot take,” he believes companies will increasingly recognize that owning a single slice of project information limits their ability to generate insights.
“I think companies are going to realize that if they only own individual silos of those data processes—like if you only own the construction data and another firm owns the design data—it’s harder to leverage the data and make decisions earlier in the process.”
He stressed that acquisitions are not the only way forward. Independent firms will continue to have a place in the industry because not every project requires integrated delivery. However, projects with demanding schedules or tight budgets, will benefit from earlier collaboration.
“When a client needs to make earlier decisions based on market volatility, long lead times or they have speed-to-market concerns … it’s more moldable earlier in the design process if you are able to make those decisions," he says.
Incorporating data earlier in the design phase will allow project teams to make changes before costly engineering work has been completed.
He emphasizes that companies embarking on an AI journey also need to train employees before deploying it companywide. “With new technologies and the emergence of AI, our entire firm has been trained on utilization and usage of AI,” he says.
Polous says firms also need clear policies that define what information may be used with AI tools and what must be protected.
"“It’s not just training the people, but it’s also creating the semantic architecture of what is accessible, what we can put in, and the governance that’s required around that," he says.
Without guardrails, companies risk exposing sensitive project information or creating inconsistent AI practices across the organization.
And try out AI in pilot projects first, he adds.
“You wouldn’t want to roll it out enterprise-wide without having test cases for successful pilots,” he says. “You want to ensure that, one, it brings a return on investment and two, that it’s actually feasible to accomplish.”
While there is much enthusiasm about AI's potential, Polous says successful integration of the technology requires organizing years of project information, establishing governance rules and testing applications.