If it were as simple as comparing expected values and randomly choosing one option whenever their confidence intervals overlapped, then hesitation would be irrational. In my experience, though, choices are usually more complicated because you have to think about both expected value and variance (or, more generally, the distribution of returns). If A and B look "about the same" but the error bars are giant, it's usually worth the effort to cut them down a bit. Sometimes you find that the ranges still overlap afterwards, at which point you flip a coin. But just as often, you find that one option is now tightly bounded while the other has a very distinctive risk profile - that is, high upside or high downside. Now you've gained valuable information!

The general problem of making choices with limited information reminds me of a thought experiment from business school: suppose you have a startup that's worth $5B if it succeeds or costs $1B if it fails. You could just try it, and succeed with 50% probability, or you could run a test that tells you for sure whether it will succeed or not. How much should you be willing to spend on that test? The expected value is $2B up front, but $5B if you know it will succeed, and you have a 50% chance that the test comes up positive, for a $2.5B expected value if you can run the test for free. That means you should be willing to spend up to $500M on the test! Hence venture capital.