Echoing economist Robert Solow's 1987 observation about computers, thousands of CEOs now admit AI has no measurable productivity impact. This suggests history is repeating, where major technological shifts have a long, multi-year lag before their economic benefits are truly realized and measured.

Contrary to its long-term deflationary promise, AI is currently fueling inflation. The massive build-out of data centers, demand for computer components, and wealth effects from tech stocks are creating a demand shock that outstrips the technology's nascent productivity gains, pushing prices higher.

Contrary to the feeling of rapid technological change, economic data shows productivity growth has been extremely low for 50 years. AI is not just another incremental improvement; it's a potential shock to a long-stagnant system, which is crucial context for its impact.

Metrics like new app creation are spiking due to AI tools, but this increased activity doesn't ensure value. This mirrors the smartphone era, where the explosion of photos devalued the marginal photo. AI's productivity may simply create more low-margin noise.

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.

Skeptics argue the AI-driven productivity boom theory is based on thin evidence. The downward job revisions fueling the theory were concentrated in government, mining, and manufacturing—not the white-collar sectors supposedly most impacted by AI, suggesting other economic factors are at play.

The current AI market resembles the early, productive phase of the dot-com era, not its speculative peak. Key indicators like reasonable big tech valuations and low leverage suggest a foundational technology shift is underway, contrasting with the market frenzy of the late 90s.

While AI investment has exploded, US productivity has barely risen. Valuations are priced as if a societal transformation is complete, yet 95% of GenAI pilots fail to positively impact company P&Ls. This gap between market expectation and real-world economic benefit creates systemic risk.

A significant disconnect exists between AI's market valuation, which prices in massive future GDP growth, and its current real-world economic impact. An NBER study shows 80% of US firms report no productivity gains from AI, highlighting that market hype is far ahead of actual economic integration and value creation.