Every new tool that promises to save time in construction comes with a fair question: what happens when it gets something wrong on a project where being wrong is expensive, or dangerous?
Research on generative software in construction is honest about this tension. Alongside the real gains in collaboration and faster decision-making, the same research flags serious open questions: how private project data stays private, how these tools avoid baking in bad assumptions from whatever they were trained on, and who is actually accountable when a tool-assisted decision turns out to be wrong.
None of these are reasons to avoid the technology. They're reasons to be deliberate about where it gets used. A tool that helps draft a report and gets checked by a person is a very different risk than one making an unsupervised call on a structural decision. The research is clear that getting this balance right will take real coordination between the companies building these tools, the industry using them, and regulators setting the rules.
This is exactly the kind of caution baked into how Predictye thinks about its own roadmap into the construction space: useful automation where it clearly helps, a person in the loop where it clearly should, and honesty about which is which.
Source: Rane, 2023.
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