Imagine taking someone who didn't know English words or sounds, sitting them down with a document and dictionary, and asking them to spell-check it. If they could figure out that "butiful" should be "beautiful" in less than a week I'd call that really freaking intelligent. AI researchers of 40 years ago would be astounded by what Word can do.
Route planning is essentially "the" fundamental AI problem. You need to get from A to B and there are 2^100 ways to do it. How do you pick the best one?
Just because you were taught routing in your AI class doesn't make it AI. It is a topic in graph theory and combinatorics. Dynamic programming is a useful technique for solving traditional AI problem formulations, but it isn't AI.
In contrast, your example of the human is like modern AI, specifically unsupervised learning. I'm sure I could get a human doing that kind of pattern matching quite good at it quite quickly.
If I didn't have a learning system I could still write an algorithm for it quite quickly, by computing the Levenshtein distance. But that algorithm would notoriously not understand the context of the sentence, probabilities of words, etc. And indeed Word/Android/iOS spell correct still gets it really wrong much of the time. But the AI used is quite different from old timey backtracking.
Route planning is essentially "the" fundamental AI problem. You need to get from A to B and there are 2^100 ways to do it. How do you pick the best one?