Usman Shuja is the Chief Executive Officer at Bluebeam.
People don’t usually think of construction as the birthplace of tomorrow’s artificial intelligence.
The industry is messy, unpredictable and full of moving parts. It’s hardly the controlled environment tech companies prefer. But that’s exactly why I believe construction might be the best place on Earth to shape the future of agentic AI.
Agentic AI—systems that can make decisions and carry out multistep tasks with minimal human input—isn’t as futuristic as it sounds. We already see early versions of it all around us: self-driving cars navigating city streets or trading algorithms reacting to market shifts faster than any human could.
These are forms of AI that act, not just analyze.
And the construction site, with its constant motion and high stakes, is the perfect test bed for what comes next.
Learning From The Chaos
On any given project, hundreds of people coordinate thousands of tasks under ever-changing conditions. As anyone in this industry knows, things rarely go according to plan. That complexity is what makes the jobsite such fertile ground for smarter, more adaptive AI.
At Bluebeam, I’ve seen firsthand how AI is moving beyond theory into real impact. Some of our customers are already experimenting with systems that don’t just find information but help superintendents act on it—automatically generating submittals, flagging inconsistencies between drawings or surfacing insights before small issues turn into rework.
This isn’t hype. Companies like Trunk Tools are showing what’s possible, using AI to process millions of pages of project documents and answer field questions in real time.
Others, like Motif and TwinKnowledge, are building what I think of as institutional memory, training AI on decades of project data so it can anticipate risks and improve coordination.
These aren’t just interesting experiments, either. They’re signs of what’s to come: a future where agentic AI quietly runs beneath every project, catching errors, speeding up decisions and freeing people to focus on the creative and collaborative work that really drives value.
The Real Opportunity
Critics often say construction is too fragmented, too analog, too complicated for AI to make a difference. I see it differently. Those same challenges make this industry the ideal proving ground for agentic systems.
Our workflows are overloaded with data but short on visibility. Teams are stretched thin by labor shortages that show no sign of easing. The cost of miscommunication (both financial and human) remains enormous. Each of these realities creates an opportunity for AI to prove its worth, not in theory but in practice.
Of course, adoption doesn’t happen overnight. The biggest barrier I’ve observed isn’t technical—it’s cultural. This is a human-first industry. People need to trust that technology will make their work easier, not more complicated. That trust is earned one project, one workflow, one tangible result at a time.
At Bluebeam, we’ve learned that trust starts with clarity. We focus on explainability and collaboration, making sure our AI tools work with people, not around them. Progress in construction AI isn’t about replacing judgment but about reinforcing it.
A Smarter Way To Build And Learn
I’ve come to believe that the rough edges of construction—the unpredictability, the friction, the constant adaptation—are exactly what will make agentic AI smarter and more grounded. This environment forces systems to handle the unplanned, the imperfect, the deeply human. That’s not a weakness but a real test of intelligence.
If agentic AI can thrive in the dirt and noise of a construction site, it can thrive anywhere. Still, that success will depend on how we build it: with respect for craft, collaboration and the realities of the field.
The future of AI won’t be shaped only in labs or boardrooms. It will be shaped by the people wearing hard hats, solving problems in real time and refusing to let complexity win.
That’s where innovation gets its edge, and it’s where technology learns what really matters. We’re not just teaching AI to think. In construction, we’re teaching it how to build.
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