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This paper examines structural differences between human creative workflows and generative AI music systems by synthesizing observations from prior work in creative cognition, AI ethics, and platform studies. The comparison focuses on variations in process visibility, transparency, and production scale, which may influence how authorship, provenance, and cultural value are interpreted in digital music environments. The analysis does not assess aesthetic quality or propose new theoretical constructs. Instead, it summarizes descriptive patterns identified across existing literature. The findings suggest that high-volume generative output, combined with limited process transparency, may resemble dynamics described in prior information-asymmetry research, though the correspondence is not definitive. The study aims to provide reference points for understanding how generative tools operate alongside human creative practices and how these structural characteristics may inform future discussions about digital creative ecosystems.