The most expensive part of your AI rollout isn't the software. It's the rework.

The most expensive part of your AI rollout isn’t the software. It’s the rework no one is tracking.

None of this is new if you’ve been running AI workflows in production. But now there’s data behind it.

New Workday data: 37% of time saved by AI gets eaten by error correction. For every 10 hours gained, nearly 4 disappear fixing outputs.

And the burden falls on your most engaged users. 77% of daily AI users audit AI work with the same or more rigor than human work. That adds up to 1.5 extra weeks per year per engaged employee spent on cleanup.

Most companies are measuring gross AI productivity. Time saved. Tasks completed. Outputs generated.

Almost nobody is measuring net AI productivity. What actually stuck. What didn’t need to be redone. What moved the business forward.

That’s the gap. And it’s where the real cost hides.

There’s a training problem compounding this. 66% of leaders say AI skills training is a top priority. Only 37% of daily AI users say they’ve gotten more access to training. Companies are expecting high-quality AI-assisted work without giving people the skills to deliver it.

If you run a mid-market company using AI tools today, the question isn’t whether AI is saving time. It’s whether you’re tracking what happens after the first output.