You are almost right. Your only mistake IMO is in confounding Music with "Music composition":

To use your expression, Music (and not sound) is indeed, "perhaps counter-intuitively, harder than image."

You also correctly stated the right reason why: "difference in complexity between the two types of compositions"

However, 40 Years of Electronic Music and Hip Hop music have utterly demonstrated how forgiving we can be of sounds like Cheesy synths and low-res samples loops, if they are culturally "organized".

This is good news for AI!

At least in the short term, the real creative potential of AI in music is in manipulating "Musical Sounds", not in generating "Musical Composition".

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PS : I've recently made a short list of creative musical AI tools here https://rentry.co/Music-Creation-AI-Tool .

Missed an ‘s’ in your url https://rentry.co/music-creation-ai-tools

Images are only correlated on very small space/time scales. Audio/Music has correlation on multiple over-lapping time scales. We know this is true because Video filters are usually very small, bilinear, bi-cubic, operating on only a very small region. A large video filter doesn't make sense because there is no correlation. Audio requires attention to tone, transients, harmonics, voice envelopes, relationships between notes/scales, rhythym, recurring musical passages etc. etc. All these require filtering, or memory based processing over different time scales. So audio/music from a raw data perspective is much more difficult for an AI system compared to images. This is why image related AI is so prevalant, it is the low-hanging fruit due to small amount of correlation that the Neural Net needs to deal with.