Congress recently sent a House proposal to create a federal framework to govern the development of artificial intelligence. However, a different battle is taking place in construction over construction data due to the need to train AI agents to be able to do everything from reviewing project documents to preparing a bid or even inspecting welds at steel fabricators’ facilities.
OpenAi, the maker of ChatGPT, recently signaled that it would comply with a recent executive order from the Trump administration that would allow federal regulators to assess the impacts of foundation models like GPT or the family of large frontier foundation language models behind Anthropic’s Claude AI. While governments are increasingly invested in reviewing how these grassroots models will affect users and even workplaces, the AIs emerging in construction are not based on general data pulled from the web.
Rather, they rely on construction-specific data to help AI agents understand embankments, mechanics’ embargoes, geometric symbols on 2D plans, and all the design and construction processes that have managed to preserve themselves through, in the first place, the CAD revolution and even 3D building information modeling.
While agentic AI has already been a boon for preconstruction processes such as estimating and document review, making AIs understand geometry remains a moving target. This has made construction data to train AI agents a highly desired commodity for tech companies with construction management platforms. Whoever has access to project data and uses it to train their AIs is now thinly veiled by these platforms.
Last year, Procore banned Trunk Tools, a popular provider of AI agents used by large general contractors like GIlbane Building Co. and Suffolk Construction, access to its application program interface, which made it much more difficult for contractors using Procore as their construction management system to use Trunk Tools and its agents.
Procore said it was only protecting “the integrity and security of all our customers’ data as AI rapidly reshapes the technology landscape,” but the popular platform quickly acquired DataGrid, another contractor AI service provider that even has its own agent builder for GCs to use their own data to build their own agents. The integration of DataGrid as a companion natural language AI agent to the Procore platform was quick.
Construction is unique because many contractors and even architects and engineers have closely guarded project information to give themselves a competitive advantage for decades. Indeed, the science and engineering behind advancing construction is valuable and does not come cheap, especially when designs like the Sydney Opera House can be built.
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Historical construction data becomes more valuable the more you have it, but these platforms that lock guard and hoard construction data, with the consent and agreement of their customers, threaten to undo the progress in open information sharing thanks to the application program interfaces and standards that came with 3D building information modeling in the late 90s and early 00s.
Unfortunately, the promise of BIM was never fulfilled due to similar privacy and competition issues. The need to preserve processes that limit risk and minimize the sharing of project information on a need-to-know basis prevented BIM from being the model-based collaborative platform it promised. Between 2005 and 2012, BIM moved from an ideal of all stakeholders working together on a shared model to cloud platforms for automating RFIs and change orders, processes that are less than collaborative and open.
A construction technologist who has built an agentic AI platform once told me “if we’re just making a better trade-order platform, then we’ve missed the script to make models that don’t require trade-orders.”
Like many industries, construction is on the precipice of agentic AI changing the processes it relied on and automating repetitive tasks that have long held back best delivery practices and efficiency.
It will be a huge missed opportunity if vendors serving construction choose the process and risk mitigation methods of the past instead of recognizing the possibility and opportunity presented by open standards, data sharing, and truly looking at every architect, engineer, contractor, specialty contractor, and even owners and their representatives.
This may seem like a utopian vision of building teams working together in harmony with none of the problems inherent in building or advancing design. Indeed, I may be a dreamer, but I am not the only one. The dream of coordinated BIM and teamwork in the model is only enhanced by agentic AI and the automation of repetitive tasks in both design and construction. Let’s not repeat the mistakes of the past when it comes to sharing construction data.
