Every major technology shift of the past three decades has made things cheaper for end users. Streaming made music cheaper. Cloud computing made infrastructure cheaper. E-commerce made retail cheaper. Construction is the one industry where that pattern hasn’t held. The reason isn’t a lack of technology adoption. It’s a structural problem in who captures the value when efficiency improves.
The AI tools entering construction are helping contractors and their subcontractors work faster and more efficiently. But those gains are not being passed on to the owners and developers paying for the projects. KP Reddy, Founder & CEO of Zero RFI, an AI-native owner’s representative firm, has watched that gap play out across projects nationwide.
“If you think about every market where technology has come in, it’s made it deflationary,” Reddy says. “Everything costs a lot less – except in construction. The cost of construction has increased year over year.”
Rising Costs Despite Technology
That increase has continued even as the industry has absorbed significant technological investment. Project management platforms, drone-based site monitoring, Building Information Modeling (BIM) – 3D digital models used to plan and coordinate construction – and AI-assisted scheduling and estimating have all been widely adopted. Yet the cost per square foot to build has not declined in the way that comparable efficiency gains in other industries would predict.
The explanation, according to Reddy, is not the technology itself. It’s where in the supply chain the efficiency gains land.
Contractor Gains, Owner Losses
In construction, the owner or developer sits at the top of a long chain of contractors, subcontractors, consultants, and suppliers. When a general contractor adopts AI tools that make their estimating team 30% faster, or when a subcontractor uses machine learning to optimize crew scheduling, those gains improve the contractor’s margins alone.
“If you’re a contractor and you’re using AI and you say, oh, we’re becoming 30% more efficient, who benefits from that?” Reddy asks. “The construction company benefits. The owner and developer doesn’t benefit from that.”
Contractors are typically paid on fixed-price contracts, where the total price is set in advance, or cost-plus contracts, where the owner pays the contractor’s costs plus an additional fee. Both types are usually negotiated before AI tools are deployed. Efficiency gains realized during execution flow to the contractor’s bottom line, not back to the owner in the form of lower invoices or faster delivery. Unless owners have the tools and expertise to identify where efficiency is being captured, they can’t negotiate accordingly, and they remain outside the value creation happening on their own projects.
The Owner Information Gap
Owners and developers, in Reddy’s view, lack the visibility and analytical capability to understand what is actually happening across the many firms working on their projects. A typical large construction project involves more than 150 separate companies, each with its own systems, workflows, and incentives. Without a way to synthesize that complexity, owners are largely dependent on the information their contractors choose to share.
“You have 150 different companies working on a project,” Reddy says. “Each of them has a different vocabulary.”
This means that even when owners want to push for efficiency gains to be reflected in project costs, they often lack the data to make that case. They cannot easily identify where schedule delays originate, which subcontractors are underperforming, or where budget overruns are being absorbed before they surface in formal reporting. The result is a technology investment that has largely made the contractor side of the market more profitable, without delivering the cost reductions owners might reasonably expect.
The Path Forward
A small number of firms, including Zero RFI, have begun building AI tools to close this information gap. These tools analyze projects on behalf of owners, flagging schedule or budget problems early rather than waiting for them to surface in contractor reporting.
Whether tools like this meaningfully shift the balance is still an open question industry-wide. But the premise, in Reddy’s framing, reorients the debate over AI in construction: the issue isn’t whether AI works, but whether it’s structured to benefit the people paying for the buildings as much as the people building them. Closing that gap will likely depend less on any single firm’s tools than on whether owners, as a group, start demanding visibility into where their money is actually going.
About the Expert: KP Reddy is Founder and CEO of Zero RFI, an AI-native owner’s representative firm applying AI tools to project oversight from the owner’s side of construction, including site selection, design, construction management, and facilities management.
This article is intended for informational purposes only and does not constitute legal, financial, or investment advice. The views and opinions expressed herein reflect those of the individuals quoted and do not represent an endorsement of any company, product, or service mentioned. Readers should conduct their own due diligence and consult qualified professionals before making any investment decisions.
