Q: The AEC industry often operates as “islands.” How can data models help break down these barriers and encourage global learning? A: External forces are usually the most powerful drivers of sharing and openness. The most effective are clients and governments. When a client mandates shared data, real-time transparency and collaboration, the benefits become obvious quickly. We’ve seen it on our most successful projects where precise transparency and sharing requirements create clear behaviours and reinforce best practices. At the industry level, governments are crucial. Public agencies manage massive portfolios of infrastructure, and taxpayers deserve the benefits of shared lessons learned from previous projects. Policies that require transparent data sharing can transform the industry from a set of islands into a connected ecosystem. Q: AEC consistently ranks among the least productive industries. How can better data and collaboration change that trajectory? A: From our work with hundreds of AEC clients, we see several recurring patterns that slow productivity: scepticism, reluctance to change, and a comfort with legacy processes. It often takes outside forces to trigger behavioural shifts. An example of this is the effect of COVID, which, within weeks, sparked changes in working practices that would have taken years without the pandemic. Productivity improved briefly, but only because people worked differently, not necessarily better. For example, instead of mailing physical invoices, people started emailing PDFs. It was basically the same workflow, just with different steps. Data and collaboration can absolutely improve productivity, but the benefits must be material and obvious. Incremental or inconsistent improvements won’t move the needle.
Q: How is AI helping to create more certainty in AEC projects? A: AI can provide significant benefits, but only if the industry meets certain maturity thresholds — with data practices being the most important. AI follows the same progression model as any other process improvement: from ad hoc to optimised. The first gate you need to pass through is the quality and context of data. “Garbage in, garbage out” becomes even more literal in an AI world where hallucinations can occur even with curated data. The other essential gates for effective AI adoption are leadership, trust, talent and ethics. Once those are in place, AI can begin to fulfil its promise in the industry. But again, it all starts with fixing the data estate. For AEC leaders, the message is clear. Turning the industry’s terabytes of stranded data into real value won’t happen through more tools or dashboards. It requires a more fundamental rethink of how data is created, shared, governed and used across teams and the entire project lifecycle. Leaders in the industry need to move beyond seeing data as a necessary evil or a compliance requirement. Instead, they should treat it as fundamental infrastructure for solving complex construction and design challenges more quickly and efficiently. The key to solving the industry’s most entrenched challenges, ranging from cost overruns to carbon reduction and workforce safety, lies in a more holistic, systematic approach to tapping its huge reservoir of data. Companies that make this shift now by rethinking how their data is created, aligning that with their goals, embracing new data collaboration models and exploring AI processes will give themselves a clear advantage and a chance to lead the industry into a higher productivity era.
References 1. Blanco, Jose Luis, David Rockhill, Aditya Sanghvi, and Alberto Torres. 2023. “From Start-Up to Scale-Up: Accelerating Growth in Construction Technology.” McKinsey & Company, May 3. https://www.mckinsey.com/industries/private-capital/our-insights/from-start-up-to-scale-up-accelerating-growth-in-construction-technology 2. Symetri. 2025. “Embracing Connected Data in the Construction Industry.” June 12. https://www.symetri.us/insights/blog/embracing-connected-data-in-the-construction-industry/ 3. Mischke, Jan, Kevin Stokvis, Koen Vermeltfoort, and Birgit Biemans. 2024. “Delivering on Construction Productivity Is No Longer Optional.” McKinsey & Company, August 9. https://www.mckinsey.com/capabilities/operations/our-insights/delivering-on-construction-productivity-is-no-longer-optional 4. Analytics8. 2025. “What Is Data Mesh, and Do I Need It for My Organization?” October 15. https://www.analytics8.com/blog/what-is-data-mesh/
22 | GHD | Nexus Magazine
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