Leading Through Construction’s Next Transformation
Artificial intelligence is moving quickly into the construction industry, but the biggest question facing contractors and owners may not be which AI tools they should adopt.
It may be whether their leaders are prepared for what comes next.
That was one of the central themes of a recent Construction Users Roundtable (CURT) podcast conversation between Greg Sizemore and Brian Gallagher, construction industry strategist, author and Vice President of Corporate Strategy and Development at PPC Partners.
During the discussion, Gallagher argued that construction leaders should stop thinking about AI primarily as another technology initiative.
AI is increasingly a leadership decision.
And that distinction matters.
Construction Doesn’t Have a Technology Problem. It Has a Leadership Challenge.
Construction companies have spent decades implementing new technologies. ERP systems, BIM, VDC, drones, mobile applications, project management platforms and digital collaboration tools have all changed how projects are delivered.
AI is different.
It does not simply digitize an existing process. Increasingly, it can analyze information, generate content, identify patterns, support decisions and perform portions of knowledge work that historically required people.
That means the conversation quickly moves beyond IT.
It becomes a discussion about strategy, organizational structure, talent, risk, productivity and competitive advantage.
Construction executives therefore need to ask a different set of questions.
Where can AI materially improve our business? What decisions should remain human? How will roles change? What proprietary knowledge should we protect? Where could AI create competitive advantage? And perhaps most importantly: Who owns AI inside the organization?
Waiting for the technology department to answer those questions misses the larger opportunity.
The Industry Is Entering the Experimentation Era
Across construction, experimentation is already underway.
Employees are using generative AI to summarize documents, analyze information, draft proposals, prepare meeting notes, research markets, develop schedules and improve communication.
Estimators are exploring AI-assisted quantity takeoffs and historical cost analysis. Project teams are experimenting with automated documentation and risk identification. Business development teams are using AI for research and proposal development. Executives are using AI to synthesize information and challenge assumptions.
But experimentation alone is not transformation.
Organizations can easily accumulate dozens of disconnected AI tools without materially changing performance.
The larger opportunity comes when companies move from isolated productivity gains toward redesigning how work actually gets done.
Instead of asking:
“Where can we use AI?”
Leadership teams should increasingly ask:
“If we were designing this process today with AI available, would we build it the same way?”
That question can produce very different answers.
AI Could Change the Economics of Knowledge Work
One of the most significant implications discussed during the CURT conversation is AI’s potential impact on jobs.
That does not necessarily mean widespread job elimination.
It means jobs will change.
Construction has historically operated with significant administrative friction. Project managers spend hours searching for information. Estimators repeatedly analyze similar documents. Executives consume enormous amounts of data before making decisions. Marketing teams recreate similar content. Project teams document, summarize, organize and communicate information continuously.
AI can increasingly perform portions of that work.
The result could be something construction desperately needs: greater organizational capacity without proportionally increasing headcount.
In an industry facing persistent talent shortages, that is an important distinction.
The companies that benefit most may not be those that simply reduce labor. They may be the ones that allow talented people to spend less time processing information and more time solving problems, building relationships, managing risk and making decisions.
The Workforce Will Expect Something Different
The conversation also touched on another leadership challenge: changing workforce expectations.
Younger employees entering construction have grown up in an environment where information is immediate, technology is intuitive and digital tools are embedded in everyday life.
They will increasingly question processes built around repetitive administrative work, fragmented systems and institutional habits that exist largely because “that’s how we’ve always done it.”
AI could accelerate that tension.
A company asking a young project engineer to spend several hours manually performing a task that AI can complete in minutes will eventually have a cultural problem—not merely a productivity problem.
Technology expectations are becoming part of the employee value proposition.
Companies capable of combining experienced construction knowledge with modern technology may therefore gain an advantage not only in productivity, but also in recruiting and retention.
The Biggest Barrier May Be Organizational
The technical barriers to AI adoption continue to fall.
The organizational barriers are harder.
Companies must address data security, governance, accuracy, intellectual property, training and acceptable-use policies. Leaders must also determine where experimentation should be encouraged and where controls are necessary.
But organizations should be careful not to confuse governance with avoidance.
There is risk in adopting AI too quickly.
There is also risk in moving too slowly.
Competitors are learning. Employees are experimenting. Technology companies are investing billions of dollars. Owners are beginning to expect greater speed, transparency and intelligence from their project partners.
Standing still is itself a strategic decision.
From AI Literacy to AI Leadership
Perhaps the most practical starting point for construction companies is not another software purchase.
It is AI literacy.
Executives need enough understanding of AI to ask better questions, evaluate opportunities and recognize risks. Project leaders need to understand where the technology can improve workflows. Employees need clear guidelines explaining how AI can—and cannot—be used.
From there, organizations can begin identifying high-value use cases and measuring results.
The objective should not be AI adoption for its own sake.
The objective is better business performance.
Faster decisions.
Better risk identification.
Higher-quality information.
Greater employee capacity.
Stronger customer experiences.
And ultimately, better project outcomes.
The Leadership Question
Construction has experienced plenty of technology cycles, and skepticism about the latest innovation is understandable.
AI deserves a different level of attention because its potential reach extends across virtually every function of the enterprise.
Estimating. Preconstruction. Project management. Safety. Finance. Human resources. Marketing. Business development. Operations. Strategy.
The technology will continue improving regardless of how quickly individual construction companies choose to adopt it.
That makes the defining question less about predicting exactly what AI will look like five years from now.
The more important question is whether construction leaders are building organizations capable of learning and adapting as the technology evolves.
The winners in the AI era may not be the companies with the most sophisticated technology.
They may simply be the organizations with leaders willing to rethink how their businesses work.
AI is not just another tool construction leaders need to understand. It is becoming one of the defining leadership challenges—and opportunities—of the next decade.
