Fairgrove Property Management

AI’s Practical Role in Construction Decisions

Inspections are one of the clearest near-term opportunities for AI.

A superintendent, project manager, technician, or inspector can already capture a significant amount of information with a phone, photos, or video. AI can take that simple inspection and quickly help identify concerns, organize the information, create a report, and generate follow-up items. It will not replace an experienced person walking a project, but it can dramatically enhance what that person is able to accomplish. More importantly, by making inspections faster and easier to document, I think we increase the likelihood that they actually happen consistently.

That creates another major benefit: catching defects, incomplete work, and schedule delays much earlier, when they are generally easier and less expensive to correct. We are already seeing platforms such as OpenSpace use visual jobsite data to document conditions, create punch items and observations, and identify progress and risks earlier.

The same principle extends to procurement: how can AI improve procurement decisions without replacing field expertise?

Construction procurement involves much more than choosing the lowest bid. Scope, contractor capability, historical performance, schedule, exclusions, change-order risk, and local market conditions all matter.  AI can help leaders compare bids much more systematically—identifying scope gaps, pricing anomalies, exclusions, and differences that can otherwise take significant time to find manually. It can also incorporate historical pricing and vendor performance into that decision.

“AI will not replace an experienced person walking a project, but it can dramatically enhance what that person is able to accomplish.”

But that requires organizations to get serious about their data. If estimates are inconsistent, scopes are poorly defined, vendors are named differently across systems, or historical costs are not categorized correctly, there is very little for AI to reliably analyze.

The technology creates a stronger reason for construction companies to clean up information they should have been managing better anyway. And field experience still matters. An experienced construction professional may know that one contractor communicates better, another consistently understaffs jobs, or that a seemingly straightforward scope is likely to change once demolition begins. AI can inform that decision; it should not make it in isolation.

Finding the Right Construction Role for Robotic

Construction has historically been a slow adopter of technology, but I am not convinced that will be the case with AI and robotics.

We are already seeing practical adoption in several very different areas.

On inspections and project documentation, tools such as OpenSpace and Buildots are using 360-degree cameras, photos, drones, and AI to compare actual jobsite conditions against plans, BIM models, and schedules. Buildots is even using that information to identify potential schedule delays earlier.

At the other end of the spectrum, Gravis Robotics is retrofitting existing heavy equipment, including excavators from multiple manufacturers—with autonomous capabilities. The company says its systems are already deployed on active projects across four continents. And we are seeing robotics move directly into new construction. ICON commercially launched its Titan robotic 3D-printing system for builders in 2026, moving the technology beyond demonstration projects toward an actual construction platform that other builders can use. Those are very different applications, but they demonstrate the same point: this is moving from experimentation into real construction workflows.

The growing range of applications makes the opportunity clear. What is less straightforward is knowing where and how to begin.

Start with the business problem rather than the technology.

Begin by thinking of bottlenecks and where you are losing time, money, quality, or information. Leaders should understand the workflow they are trying to improve, establish the expected outcome, and determine which technology fits with the people already doing the work. This may not always be AI. 

Adoption is also an organizational challenge. Change is hard and most implementation plans fail. People need to understand how the tool improves their work, what decisions remain theirs, and where accountability sits. The strongest implementations will combine technology with experienced operators rather than trying to separate the two.

5. Building Careers in Construction Technology and Leadership

Learn both sides.

Someone who understands technology but not construction may struggle to recognize what actually works in the field. Someone who understands construction but ignores technology risks falling behind as the industry changes. The most valuable professionals will understand construction operations, costs, contracts, field conditions, and people. They will also know how to use technology and data to improve those systems.

You do not need to become a software engineer or robotics expert. You do need to remain curious and understand what these tools can and cannot do. Be flexible; this change is going to be rapid and continuous for several years. Construction is ultimately a very practical industry. Technology succeeds when it makes projects safer, faster, more predictable, or more economical. The people who can connect new technology to those outcomes will have significant opportunities to lead.