Not all projects are beholden to the rules of the mythical man month.
And even for those that are the primary reason they are is basically the lack of a fast, efficient way to transfer built up institutional knowledge, which may be far less of a factor for AI collaboration.
If I've been working on a project for the past year as the sole developer and I could copy a snapshot of my brain to a portion of your brain that you can access without interrupting me, adding you on as a collaborator is very unlikely to make the project later and very likely to make it go much faster as you could very quickly 'hit the ground running'.
A lot of the problem with the current limits of human intelligence is really bandwidth problems with getting information transferred in and out of our meat brains effectively. Our bandwidth for knowledge import/export is DREADFUL.
AI collaboration (even assuming that bandwidth limitation goes away or is vastly reduced) would still introduce the issue of increased communication requirements, but compared to the initial transfer of acquired knowledge that one isn't as big a deal in my experience and only becomes problematic at great scale.
Perhaps more relevantly, I think there's a more basic questionable assumption - the idea that Church-Turing is the best computational basis for AI.
I strongly suspect this is not true - because even after all this time, our best abstract models of computation are still extremely brittle and fragile.
In a hand-wavey sense, as soon as you start allowing for arbitrary inputs and context awareness, you're no longer dealing with a simple Turing architecture but with something else entirely.
Adding people to a late project makes it later.