20 June 20264 min read
AI makes it easy to ship more. DORA's data says that's the problem.
Google's 2024 DORA report found that as teams adopted AI, delivery throughput and stability went down, not up. The culprit isn't bad AI code. It's batch size: AI removes the friction that used to keep change sets small, and big batches break delivery.
Short version: the pitch is that AI makes your team ship faster and more reliably. The largest study of software delivery we have found the opposite happening: as teams adopted AI, their delivery got less stable. Not because the AI writes bad code. Because it writes a lot of code, fast, and volume without discipline is how delivery breaks. The tool didn't fail. The operating model around it did.
What the DORA 2024 data actually says#
DORA is Google's long-running research program on what makes software teams deliver well. Its 2024 report surveyed a large population of engineers, about 76% of whom were already using AI for part of their work. The finding that didn't make the keynote:
- A 25% increase in AI adoption was associated with an estimated 1.5% drop in delivery throughput and a 7.2% drop in delivery stability.
- DORA's read on why: AI makes it easy to generate more code, which inflates change set size, and larger batches carry more risk. That's not a new claim. It's one of the most consistent results in their entire body of work.