PCBC Keynote Warns AI Needs Better Data Flows To Help Builders
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Artificial intelligence may be the latest must-have tool in homebuilding, but the sector's biggest obstacle is structural, not technological. According to futurist Greg Lindsey, speaking at PCBC, decades of investment in construction and property technology have delivered limited gains because projects are still built around fragmented workflows and disconnected participants.
During his keynote, "The Way We'll Build Next: AI & the End of Chain Drain," Lindsey argued that AI will only deliver meaningful productivity improvements if the industry first fixes how information moves— and is lost— across the development chain, from architects and engineers to contractors, suppliers and other stakeholders. He drew on interviews with builders, startups and technology companies to separate where artificial intelligence is already creating measurable value from where expectations have raced ahead of reality.
Lindsey noted that more than $160 billion has gone into property technology and construction technology startups over the past two decades, creating roughly 11,000 companies worldwide. Yet construction productivity has barely budged, a disconnect he said should concern investors who have backed the sector on the promise that technology alone would transform performance. "The answer isn't the tech or the money," he told attendees. "It's the structure that ties it all together."
The Cost Of "Chain Drain"
For Lindsey, the core problem is what he calls "chain drain"—the cumulative loss of information, efficiency and value as each link in the homebuilding process reinterprets project data through its own lens. According to his presentation, architects inflect the brief with a design vision, engineers reinterpret the drawings, and every downstream participant adjusts the plans to assert and prove its own value.
The result, he said, is an industry optimized for individual firms rather than overall project performance. "The building industry is sub-optimized to the point of failure," Lindsey argued, noting that this structure forces teams to relearn lessons that should have been institutionalized from previous projects. Valuable information that could drive continuous learning is repeatedly lost at handoffs between organizations, undermining productivity across the board.
"We go two steps forward and one step back because of these leaks at the handoff," Lindsey told the audience, warning that this pattern shows up in everything from design changes to procurement to field execution. For investors, the implication is that capital deployed into point solutions—without tackling how data is preserved and shared across the development chain—will struggle to produce the productivity gains the market is expecting.
Where AI Fits In For Builders And Investors
Lindsey made clear that artificial intelligence can still play a significant role in reshaping homebuilding, but only if it is deployed with a broader delivery model in mind. According to the panelists and Lindsey's presentation, AI can help identify inefficiencies, automate repetitive tasks and improve decision-making, particularly when it has access to consistent data across projects rather than siloed, partial information.
He cautioned, however, that technology alone cannot overcome a delivery model built around disconnected participants. "AI can't help you solve everything on its own," Lindsey said. "We can't solve this by focusing on our own piece of the puzzle." Instead, he argued, builders and investors should think about AI as an enabling technology that preserves institutional knowledge, captures lessons learned and ties together the many links in the development chain.
In Lindsey's view, the path to real productivity gains in homebuilding is a combination of redesigned workflows and targeted AI tools that keep information from leaking away at every handoff. The presentation framed artificial intelligence not as a magic bullet, but as a way to support a more coordinated homebuilding ecosystem that invests in the structure that binds projects together, rather than just another layer of isolated software.
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