Python 2 to 3 (at least by 3.3 or so) was one of the easiest transitions I've ever done. There's a library ("six") to help, and in almost all cases you can write 2-and-3 compatible code, which means you can go piece-by-piece. (Unless your manager makes drive-by commits of py2-only code, months after you all agreed that all new code should be py3-compatible, and then leaves town for a multi-week vacation...) Dependenc…
I think many people underestimate the challenge that the 2 to 3 migration presents for large enterprises. The core issue is that even though the migration for any given module is normally really easy, the total effort required to migrate is still essentially O(n) in module count/file count, because even with current tooling you still need to have an engineer look at every module to do the change safely. Even if it only takes ~5 minutes per module to make the changes and validate that it works correctly, this becomes a giant undertaking when you have tens of thousands of files to migrate.
The fact that it takes a long time also creates other problems. Your business isn't going to hit "pause" on other development, so there will be changes constantly introduced into modules you've already "swept". It's going to be hard to make sure 100% of your engineers and code reviewers are knowledgeable about the specific requirements to make sure the code works in both 2 and 3, so you would really like some automated safeguards to make sure they don't introduce anything that won't work in 3. Pylint helps with this, but won't catch everything. Unit tests are obviously essential, but:
1. Even a well-tested project won't have tests that cover 100% of code paths and behavior.
2. You're stuck running the tests on both python2 and python3 for the duration of the migration, which doubles the resource (compute, memory, etc.) cost of your Python CI and regression testing infrastructure for the duration of the migration.
I see far too many commenters attributing the delayed migration to laziness or complacency. In reality, most big companies have passionate Python advocates who really want to be on Python 3, but the scale of the problem and the lack of tooling to tackle it with a sub-O(n) amount of effort make the overall project risky and expensive for the business.