CircleCI’s 2026 State of Software Delivery report has two findings that are already travelling: AI is meaningfully boosting software delivery, but only 1 in 20 teams are capturing that benefit. Both claims are more uncertain than the report suggests, for different reasons.

What the report is measuring

The report’s primary metric is “throughput” – the number of times a CI pipeline runs per day. A CI pipeline is the automated process teams use to build, test and progress code toward production. It is not production deployments, it is not features shipped. The report is using pipeline execution data to infer things about software delivery. That’s not unreasonable – it’s real data – but it’s worth understanding what’s actually being measured before drawing conclusions.

The headline numbers

The report measures throughput on both feature branches and main branches and aggregates both into its headline figures. Throughput as a metric on feature branches is effectively meaningless. Throughput should be an end-to-end metric – feature branches aren’t end-to-end, they get merged to main. The only meaningful “throughput” measure is against the main branch. What the feature branch data actually shows is a lot more code being written, but not much more reaching production.

• Average teams are up 4% on the aggregated figure, but main branch throughput is down 7%
• The top 10% of teams show aggregated throughput up nearly 50%, main branch essentially flat
• For 95% of teams, AI is generating more work in progress that isn’t shipping

The success rate of main branch builds compounds this further. It has fallen to 70.8%, its lowest in over five years – 30% of attempts to merge code for production are now failing.

The 1 in 20 claim

The report identifies the top 5% of teams as the only group seeing meaningful main branch throughput growth – 26% – and uses this to argue that some teams have cracked the AI delivery problem.

But the summary data for that group is odd. Their average CI pipeline duration is 6 seconds. A pipeline doing anything meaningful – compiling, running tests, scanning – it’s hard to think of a single CI step that legitimately completes in 6 seconds. Perhaps it is an error in the report. There’s also data that may be skewing the findings more broadly – one team apparently running 130,000 CircleCI workflows a day would have an outsized effect on any aggregate figures.

What to take from it

The integration bottleneck finding is credible. If you’re generating code faster than your team can review and integrate it, that’s a genuine problem this data is consistent with.

The “1 in 20 teams have cracked it” conclusion is less solid than it appears. Not to say that some aren’t getting benefit I believe there are, however the data here for the teams making that case doesn’t add up clearly enough to draw confident lessons from.