Artificial intelligence is being hailed as a revolution in efficiency, but AI productivity gains remain elusive at scale despite enterprises pouring billions into experimentation. This paradox reflects a recurring pattern in the history of innovation: Groundbreaking technologies often spark massive investment long before they deliver measurable results.In the case of AI, companies are hiring talent, building tools and testing automation strategies, yet productivity numbers barely budge. It’s not necessarily failure — it’s the familiar “J-curve” of progress, where early efforts require heavy input before transformation takes hold