Automation cannot rescue a broken workflow
AEC project risk begins not with catastrophic failure but with small transfer errors at handoffs. Automation is about consistency, not speed: split work into automatic execution, AI assistance and human decision, make exceptions visible, and measure prevented risk rather than hours saved.
This is Part 1 of doAZ's three-part series 'AEC AI IS NOT A MODEL PROBLEM', which reframes AI and automation as a question of operating systems and workflows rather than model performance. Starting from the version confusion that occurs routinely on real projects, it shows how risk grows in the handoffs between one task and the next, and argues that automation should be understood not as a technology for replacing people but as a control that keeps required work from being skipped.
It then sets out a method for separating work into three layers — rule-based automatic execution, AI assistance, and final human judgment — principles for designing workflows that account for exceptions, a metrics framework that measures prevention rather than time saved, and practical guidance on how to keep a first automation project small, citing official sources such as ISO 19650 and the NIST AI RMF.
전체 문서Automation cannot rescue a broken workflowOpens the full article in a new window (Korean)열기 →We run a verification demo on one real set of your drawings.
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