Latest figures point to a growing divergence between rapid investment tied to artificial intelligence and the slower growth seen across much of the U.S. economy. This separation carries important implications for markets and economic exposure.
Data and definitions
The analysis draws on statistics from the U.S. Bureau of Labor Statistics, FactSet, Apollo and Bloomberg; charts were prepared by Axios/Matt Phillips. The report highlights data-center construction costs, which include labor, materials, contractor profits, architectural and engineering work, miscellaneous overhead, interest and taxes — but exclude servers, racks, chips and memory.
Construction spending and concentration of AI investment
U.S. construction spending through August shows a clear pattern: investments related to AI, such as data-center construction, have been expanding quickly while much of the rest of the economy is growing at a slower pace.
Markets: bond issuance and tech valuations
AI-related activity is concentrated in financial markets as well. According to Apollo and Bloomberg, AI-related corporate bond offerings comprised more than half of net investment-grade issuance for the year through the end of August. Equity markets reflect a similar concentration: FactSet and Axios data show the technology sector’s market-cap weight in the S&P 500 is now roughly 40 percent — higher than at the dot-com peak.
That figure understates AI’s footprint: including AI-sensitive hyperscalers such as Meta and Amazon, which the S&P does not categorize within the tech sector, pushes the AI-heavy portion of the index closer to 50 percent.
Implications
The growing gap between AI-related growth and other parts of the economy means the U.S. economy and markets are increasingly linked to AI and to the risks concentrated within that segment. Significant swings in AI-linked valuations, issuance or investment could therefore have outsized effects on broader market performance and on portfolios.
Summary
Through August, investment and market data indicate accelerating concentration around AI-related spending and firms. Policymakers, investors and market participants should monitor these developments and the potential systemic implications of a market increasingly yoked to a relatively narrow set of AI-driven companies and activities.
