Accelerating Research: Can Review Systems Handle AI-Driven Productivity?

AI tools have given us a lot of slop research, but I'm not talking about that. I'm talking about real productivity acceleration due to AI tools (E.g. iterating ideas that would've taken multiple days of tedious coding gets done in a few hours, quick refactoring of latex documents, etc.). Furthermore, I'm sure most of you have heard about AI proving/disproving various mathematical conjectures, and there's no reason that that won't carry over to ML theory research.

So setting aside AI-generated slop, the pace of genuine ML research contributions is accelerating as well. Recently, ICLR 2027 has gotten an insane number of submissions - a mix of bad work and genuine contributions. How do we plan to deal with the increased review volume as productivity explodes? Are we gonna start encouraging reviewers to lean on agentic tools as well? Otherwise I don't see how this is sustainable.