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A/B tests can tell you causation. If they are correctly randomized and the tested change doesn't induce any other unintended changes, then they can tell you that the change causes whatever are the observed changes in your target metric. The challenge is controlling all other factors.

You're correct that they can't tell you the the root cause of why your change causes a particular difference, but that's a separate issue from correlation and causation.