Why More Firms Are Adding AI to Their Review Process

Ask a firm why they started using AI for plan review and the answer is rarely "because it's new." It's almost always a variation on the same two problems: they can't hire reviewers fast enough, and they don't have time to review the way they used to. Neither problem is going away on its own.

The talent math doesn't work anymore

A reliable plan reviewer isn't made in a semester. It takes years of seeing enough sets, enough failure modes, enough "that looked fine until it didn't" moments to develop the judgment that catches what a checklist won't. Firms can't shortcut that, and they can't hire their way around it either. The engineers who are good at review are usually also the engineers every other part of the firm wants on their project.

Meanwhile the volume of work going out the door hasn't slowed down. More sets, the same number of experienced reviewers, and a talent pipeline that takes years to refill. That gap doesn't close by wanting it to.

Schedules keep shrinking. Review doesn't get more time.

Design timelines compress more than almost any other phase of a project, and review is usually the first place that pressure lands. When a deadline slips, nobody cancels the client meeting. Review gets the days that are left over, which is exactly backwards from how much it matters.

The result is a review process that depends on how much time happens to be left, rather than how much the plan set actually needs. That's not a people problem. It's a structural one, and it shows up as findings that get missed not because anyone was careless, but because there simply wasn't enough runway left to catch them.

What AI actually replaces, and what it doesn't

AI review doesn't replace the engineer of record's judgment, and firms that try to use it that way are missing the point. What it replaces is the exhausting, repetitive part of review: checking every sheet against every other sheet, holding a hundred details in mind at once, verifying that what changed in one place got updated everywhere it needed to. That's systematic work, and systematic work is what AI is good at.

What it doesn't replace is the judgment call that comes after: is this finding real, does it matter for this project, what's the right fix given the client, the site, the budget. That's still entirely the engineer's call, and it always will be.

What adoption actually looks like

Firms that add AI review well don't rip out their process and start over. They add a systematic first pass before the set reaches the engineer of record. The plan set goes in, findings come back pinned to specific sheets and locations, and the reviewer's time goes toward evaluating what's real instead of hunting for what might be there. The review still ends with a human decision on every finding. What changes is how much of the set that human has to search versus verify.

The firms that wait

None of this is urgent in the way a deadline is urgent. But the firms that adopt a systematic first pass now get to redirect their senior engineers' time sooner, toward the client work and the judgment calls that actually need them. The firms that wait will be solving the same talent and schedule problem later, with less runway to do it in.