Companies claim AI is revolutionary for productivity, yet economic studies, including one by OpenAI itself, show no correlation between spending on AI and increased revenue per employee. The hype about transformative efficiency is not reflected in actual economic output.

Despite AI's narrative as a labor-replacement technology, NVIDIA's booming chip sales are occurring alongside strong job growth. This suggests that, for now, AI is acting as a productivity tool that is creating economic expansion and new roles faster than it is causing net job destruction.

Despite strong productivity numbers alongside flat job growth, economists believe it is too early for AI to be the primary driver. The gains are more likely attributable to businesses becoming more dynamic and achieving better labor-market matches following the pandemic disruptions, rather than a widespread technological revolution.

Current spikes in labor productivity are not evidence of AI's impact. They are more likely a statistical artifact caused by a compositional bias towards capital-intensive sectors and companies forcing remaining employees to do more work in a weak labor market. The true AI productivity effect is not yet visible in aggregate data.

Productivity models often wrongly assume time saved by AI is redeployed into other work. In reality, many employees use efficiency gains to finish early. This 'human slack' factor dampens macro-level productivity gains, except in highly driven fields like tech, where workers use it to work even more.

Contrary to popular narratives, recent U.S. productivity growth isn't yet driven by AI adoption. Adjusted for capacity utilization, San Francisco Fed data shows productivity is flat or negative. The observed gains come from employees and machines working harder, not smarter through new technology, delaying the anticipated AI dividend.

Initial data from industries with high AI exposure shows productivity gains are driven by increased output, not reduced labor hours. This counters the common narrative that AI's primary effect will be immediate, widespread job displacement, suggesting a period of augmentation precedes automation.

General-purpose technologies like AI initially suppress measured productivity as firms make unmeasured investments in new workflows and skills. Economist Erik Brynjolfsson argues recent data suggests we are past the trough of this "J-curve" and entering the "harvest phase" where productivity gains accelerate.

Just as electricity's impact was muted until factory floors were redesigned, AI's productivity gains will be modest if we only use it to replace old tools (e.g., as a better Google). Significant economic impact will only occur when companies fundamentally restructure their operations and workflows to leverage AI's unique capabilities.