AI Between Promise and Practice: Building Meaningful Innovation in AEC

🌍 Introduction: Two Worlds, One Question

This week, I found myself navigating two very different conversations about technology and its impact on how we build and care.
At the BuiltWorlds Conference in Munich, the discussion centered on AI transforming the AEC/O industry, from design to project delivery. Just one day later, at Delft University’s “Technogeographies of Care” symposium, researchers explored what care really means, and how technology and space shape it, sometimes in unexpected ways.

🧠 BuiltWorlds 2025: The AI Reality Check

Across panels and presentations, a few recurring themes stood out.

1. Problem First, Technology Second

AI is powerful, but it is not a strategy by itself. The true challenge is defining the problem clearly before applying technology. Without that understanding, AI risks becoming an expensive distraction rather than a meaningful solution.

2. Bottom-Up Innovation Works Better

Several panelists highlighted that the most successful AI initiatives come from teams on the ground, not only from executive mandates.
While “top-down” innovation sets direction, “bottom-up” innovation, driven by those who actually build, design, and manage data, ensures real adoption and practical value.

3. The Hardest Problem Isn’t Software, It’s Data

Every conversation, from generative design to infrastructure sustainability, circled back to data: cleaning it, structuring it, and communicating it across teams.
The consensus was clear: before AEC companies can leverage AI effectively, they must get their data governance and interoperability right.
Many large firms are already creating in-house innovation teams to bridge data, software, and project knowledge, yet most agree that organizational structure remains a bigger hurdle than technology itself.

🔍 Delft: Rethinking “Care” and Technological Intervention

Switching gears at Delft University’s Technogeographies of Care symposium, the tone shifted from industrial transformation to philosophical inquiry.
Researchers questioned the very premise of technological “improvement.” When I mentioned AI as a potential tool, the response was reflective and sometimes skeptical:

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“Do we really need AI? What kind of care does it provide, and for whom?”

Their discussions reminded me that technology is never neutral. It shapes behaviors, relationships, and outcomes.
The group’s humanistic perspective underscored that even in AEC, AI must be evaluated not only for efficiency, but for meaning—what kind of built environments it enables, and whom it serves.

✈️ Reflection

From Munich to Delft, I am grateful for the chance to engage with such diverse thinkers, from AI engineers to philosophers of care.
It is a reminder that progress in AEC is not just about building faster or smarter, but about building with purpose.
The question is not whether AI will transform our industry, but whether we will let it transform us thoughtfully.

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