The 90-day shelf: why construction AI projects fail

Most AI projects have the same life cycle. A pilot gets approved, the demo looks great, two people use it for a month, and by day 90 it's on the shelf with the last three tools. Nobody cancels it. Nobody uses it.

Four reasons projects end up on the shelf

• It was bought as a platform, not built as a workflow. Nobody wrote down which 40-hour task was supposed to become an 8-hour task.
• The data wasn't ready and nobody said so. The demo ran on clean data; your bid sets are scans and emails.
• The people doing the work didn't choose the tool. Estimators and supers route around anything that adds a step.
• Nobody owned it after go-live. A vendor's job ends at launch. Systems without an owner decay in weeks.

The approach that stays off the shelf

• Pick one workflow, not one platform. Name the task, the hours it takes today, and the number it should take.
• Spec before code. Every feature starts as a written specification the operating team signs off on.
• Build it on your documents, in 90 days, on your infrastructure. A production system, not a pilot.
• Hand it over with a named owner, training, and documentation.
• Then pick the second workflow. It's faster, because the data plumbing and the trust already exist.