I don't think there's a clear line either. Even the Turing Test is notional - a conversation with a high schooler is going to be easier to fake than a conversation with an English professor.
I can imagine in the future there will be some kind of approximate conversational AI rating analogous to Flesch-Kincaid for text.
But I left a problem off my list, which is that we unconsciously demand AI should be better than average human performance.
If you monitor your conversations with people, you'll find there are regular misses where one person either mishears words, doesn't understand what's said, or misinterprets a subtext.
We cut human conversations a lot of slack. We're used to thinking of humans as independent agents, and there are social conventions about asking for more information and admitting - or sometimes denying - mistakes.
But there's an unconscious expectation that AI should operate at a better-than-human level before it's considered reliable.
We're more likely to think "Stupid machine!" if something isn't understood than we would with a human. So AI will have to cross the Uncanny Turning Valley before we really trust it. And because we're dealing with automated interpretations of human agency, errors will be harder to forgive.
You can already see this with driverless cars, where any accident is considered a failure. Even though statistically an AI may be much safer than the average human, it's not considered good enough unless it can deal with situations that an average human would have no hope of dealing with.