Vendors show impressive demo videos: one sentence as input, a finished floor plan as output. What they do not show: the result cannot be checked against planning law, has no structural logic and is not buildable. AI can sketch ideas – but it cannot replace architects who bear professional responsibility.
A practice buys an AI tool for tender review. Two weeks later, nobody uses it – because the outputs require manual reworking, there is no interface with the existing workflow, and nobody on the team was trained. AI is not plug-and-play. It requires implementation time, process adjustment and an internal owner.
"We now have AI" is not a strategy. Practices that introduce AI without a defined use case pay for licences that are barely used. AI solves specific problems very well – variant development, document summarisation, energy simulation – but only when the scope is clearly defined.
In concrete terms: a mid-sized planning practice uses AI to automatically generate meeting minutes and assign tasks. Time saved: approximately two hours per team member per week. Another practice uses AI image generation tools to produce initial mood images for client presentations – in 20 minutes instead of three hours. These are not revolutionary changes. But they add up.
A practice tests AI-assisted quantity take-offs – and receives unusable results. The reason: the BIM model was never consistently populated with component attributes. AI can only evaluate what is there. Without clean, structured model data, every AI tool remains ineffective – regardless of how capable it is.
In a practice of 12 people, three use AI tools regularly – the others wait and see. This creates parallel worlds: different working methods, inconsistent output quality, friction at handover. The greatest hurdle is not the technology – it is the question of who in the team will carry the change.
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