Efficiency cycle creates consumption growth spiral in AI industry

An analysis describes how a chain of cause and effect in the AI sector perpetuates continuous growth: more efficient models reduce computation costs, lower costs drive greater AI adoption, and increased usage generates new demand for computational power and energy resources. The text warns that without accounting for these secondary effects and system feedback loops, the industry risks maintaining a false perception of sustainability based solely on technical efficiency metrics.