Whether generative AI has actually entered its 'trough of disillusionment' or the hype cycle model doesn't fit this tech

Generative AI has been declared both washed up and just starting, often in the same news cycle, which says more about the hype-cycle model than about the technology itself. The trough of disillusionment framework assumes a clean sequence — inflated expectations, collapse, gradual climb — but adoption and sentiment data don't move in that tidy order here. Enterprise usage keeps expanding in some sectors while public sentiment sours in others, and investment behavior doesn't track neatly with either. The pieces collected here pull apart that mismatch: where the standard model's predictions hold, where they fail, and what metrics people are actually using when they declare the hype "over" or "real."

adoption data vs. sentiment data · critiques of the hype-cycle model itself · enterprise usage trends · investment and funding patterns · public opinion shifts · definitions of "trough" and "plateau" in this context