Architecture may be one of AI’s hardest pursuits. Unlike coding or writing, the data that could be used to train an architecture AI model is not widely available (or stealable) online. Rather, it’s stored away in the servers and physical filing cabinets of individual architecture firms. Digital drawings, 3D models, and even hand sketches are the blood and guts of an architecture project, and they’re all vastly more complicated than the résumé writing or HTML coding that AI tools have quickly mastered.  None of the big AI labs are currently attempting to tackle this challenge. That’s leaving the job up to the companies that actually hold all the data: the architecture firms themselves. Architecture firms, both small and large, are actively building out their AI capabilities. They’re hiring data scientists and machine learning specialists. They’re running Shark Tank-style AI ideas competitions, vibe-coding bespoke plugins and apps to automate highly specific tasks, and even developing their own hyper-niche large language models that can help them create building forms and floor plans that reflect their signature style. [Image: Courtesy Gensler] All this effort amounts to a broad recognition from across the industry that it’s a sink-or-swim moment for architecture. As the practitioners change the way they work—and as client expectations shift—some architecture firms are starting to realize that their own portfolios contain exactly the kind of information that can help them stand out in a business that’s only getting more competitive. “Everyone has their little gold mine they’re sitting on, with all this data of past projects they’ve done,” says Faizan Zaidi, director of design technology at the architecture firm Spectorgroup. “But the question comes down to which firms are willing to build the tools on top of it.” Architecture’s AI awakening “Four years ago I got introduced to Dall-E, which I think was, for a lot of us, an awakening,” says Matthias Hollwich, cofound

← Back to Designed News