The needs of design studios
In the daily work of the studios, in fact, the problem rarely coincides with the production of the drawing alone. More often it concerns the coordination between different versions, the control of changes, the verification of inconsistencies, the relationship between tables, calculations, emails, attachments and standards. An increasing amount of material that tends to get lost among software, shared folders and continuous revisions.
This is where many of the new AI tools for the AECO industry are coming into play. Some systems are already capable of:
- automatically compare different revisions of the same paper;
- extract data from technical PDFs;
- check for inconsistencies between documents;
- connect tables and specifications;
- support regulatory and authorization analysis.
In many cases these are not “spectacular” technologies, but tools designed to reduce errors and operating times. For those working in design, the interesting point is that the value of AI seems to be shifting from image generation to information management. And this has very practical consequences for studies too.
Archives are starting to become a strategic resource
Many AI tools only work well if the documentation is relatively tidy: consistent naming, readable folders, traceable revisions, fairly stable graphic standards. In other words, a firm that has built solid internal procedures over the years may find itself at an advantage in adopting these systems. A first useful exercise can be very simple:
- check how the files are named;
- understand where information is lost;
- identify which activities require repetitive checks;
- collect internal templates and standards.
It is precisely these activities, often considered “secondary”, that have become fertile ground for automation today.
Technical drawing is becoming machine readable
For decades tables and documentation were thought of almost exclusively as communication tools between professionals. Today they are also becoming objects that can be interpreted by AI systems. This is an important step because it changes the way the project is organized. It’s not just what an essay represents, but also how much it is:
- structured;
- consistent;
- questionable;
- linkable to other documents.
From this point of view, BIM had already opened a precise direction. AI is further accelerating this process, especially thanks to the integration with linguistic models capable of working simultaneously on texts, tables and drawings.
Some useful insights
For those who want to better understand where the sector is moving, it may be interesting to observe some specific cases:
- Primepoint: AI for reading and correlation of technical documentation (>> Wall Street Journal)
- GreenLite: use of AI in authorization processes and regulatory verification (>> GreenLite)
Rather than tools to be adopted immediately, they can be read as signals of a broader direction. Because the most significant transformation of artificial intelligence in architecture does not only concern the automatic production of images, but the possibility of finally making the enormous documentary infrastructure that supports every project searchable.
The weekly column “Architectural Prompting” is edited by experts Luciana Mastrolia, Giovanna Panucci and Andrea Tinazzo
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