New AI Spending Metric Captivates Tech, Wall Street, and Washington

Economists claim AI investment drove half of U.S. growth in 2025, but some question the validity of the metric.

Published on Feb. 23, 2026

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A new economic indicator focused on technology companies' massive spending on artificial intelligence has transfixed Silicon Valley, Wall Street, and Washington. Some economists have calculated that AI investment accounted for half or more of U.S. economic growth in 2025, effectively propping up an otherwise sluggish economy. However, experts are divided on the accuracy and usefulness of this metric.

Why it matters

The prominence of this AI spending metric highlights the growing influence of the tech sector on the broader economy. If the metric is accurate, it could reshape economic policymaking and the way growth is measured. But if it is an unreliable indicator, it could lead to misguided decisions by investors and policymakers.

The details

The new AI spending metric has captivated various stakeholders, from tech companies to Wall Street analysts to policymakers in Washington. Proponents argue that the massive investments in AI by leading technology firms have been a major driver of U.S. economic growth, even as other sectors have struggled. However, some economists are skeptical of the validity and usefulness of this metric, questioning the methodology and data sources used to calculate it.

  • In 2025, the new AI spending metric emerged as a closely watched economic indicator.

The players

Donald Trump

The former U.S. president who expressed interest in the new AI spending metric as a potential indicator of economic health.

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What they’re saying

“It was a very intuitive story.”

— Donald Trump

The takeaway

The prominence of the AI spending metric highlights the growing influence of the tech sector on the broader economy, but its accuracy and usefulness remain subject to debate. Policymakers and investors will need to carefully scrutinize this metric to avoid making decisions based on potentially unreliable data.