What Investment Data Implies about the AI Transition / Jessica Wachter, Jonathan Wachter.

Format:

Book

Author/Creator:

Wachter, Jessica.

Contributor:

Wachter, Jonathan.

National Bureau of Economic Research.

Series:

Working Paper Series (National Bureau of Economic Research) no. w35290.

NBER working paper series no. w35290

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2026.

Summary:

The five largest U.S. technology firms spent $380 billion on capital expenditure in 2025 and are forecast to spend roughly double that in 2026. These firms risk bankruptcy unless expected profits grow commensurately. We embed this observation in a two-sector open-economy model with rare productivity booms. We calibrate the boom size to match the observed increase in investment projected through 2027, implying that a boom raises AI-sector productivity by a factor of roughly 2.7. We then calibrate a two-year window of a 50% annual probability of an increase of the same magnitude, generating a range of scenarios consistent with the wide variety of industry forecasts, along with an elevated permanent probability tied to the valuation of the aggregate market. The implied additional cumulative GDP growth ranges from 5 to 58 percentage points by 2030, with AI shares of the economy ranging from 8% to 39%. Long-term annual growth is in expectation approximately 7% but with substantial risk. With risk aversion of 3, and an elasticity of intertemporal substitution equal to 1, the risk-free rate increases by approximately half a percentage point, and the equity premium rises by approximately 3 percentage points.

Notes:

June 2026.

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