Is code review becoming the first AI bottleneck?

One thing I've been wondering about lately. Most discussions around AI-assisted development focus on code generation.

More code -> Faster implementation -> Higher developer productivity.

But code generation is only one step in the delivery pipeline.
If AI allows engineers to produce significantly more code, somebody still has to review it, understand it, maintain it, and eventually debug it.

For those of you working on teams with meaningful AI adoption:

- Have you noticed any change in review load?

- More review time?

- Larger PRs?

- Review fatigue?

- Changes to review practices?

Or has this turned out to be a non-issue in practice?
I'm especially interested in observations from real teams rather than predictions.