Despite favorable conditions like tax cuts and deregulation, a broad investment boom has failed to materialize outside of AI. This isn't due to tight credit, but to massive policy uncertainty from unpredictable tariffs and immigration stances, which discourages long-term capital commitment.
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While there's a popular narrative about a US manufacturing resurgence, the massive capital spending on AI contradicts it. By consuming a huge portion of available capital and accounting for half of GDP growth, the AI boom drives up the cost of capital for all non-AI sectors, making it harder for manufacturing and other startups to get funded.
A surge in IPOs and M&A isn't driven by pro-business policies, but by a reduction in policy uncertainty. With a clearer, albeit more interventionist, landscape, companies have the confidence to execute major strategic plans they had previously postponed.
Businesses respond to the uncertainty of trade policy by adopting an "efficiency mindset." Rather than hiring, which carries risks in an uncertain environment, firms are making "no regrets" investments in automation and efficiency. These improvements provide benefits regardless of future tariff levels, making them a safer bet than expanding payroll.
The US economy would have likely shown negative growth if not for the recent AI boom. This surge in AI-related productivity and investment masked the detrimental effects of tariffs, such as rising input costs for manufacturers and slowing growth in other sectors like housing.
The dominant market driver will transition from macro risks like tariffs and policy uncertainty to micro, asset-specific stories. The key focus will be on company-level analysis of AI capital expenditure plans and their impact on earnings.
A surge in business technology investment was misinterpreted as an AI-powered economic boom. It more likely reflected companies front-loading purchases of semiconductors and electronics to avoid paying impending 25% tariffs, rather than a fundamental acceleration in AI-related capital expenditure.
Unlike the dot-com or shale booms fueled by less stable companies, the current AI investment cycle is driven by corporations with exceptionally strong balance sheets. This financial resilience mitigates the risk of a credit crisis, even with massive capital expenditure and uncertain returns, allowing the cycle to run longer.
Businesses can adapt to stable, even unfavorable, policies. However, constant, unpredictable policy changes create an environment of ambient chaos where long-term capital investment is impossible. The lack of continuity, not the specific tariffs, is the primary reason industrial construction spending has turned negative.
Despite AI hype, market valuations haven't reached dot-com era levels. This restraint is largely due to negative macroeconomic factors like trade wars, high interest rates, and a weak labor market, which are acting as a brake on otherwise rampant investor enthusiasm.
As AI investment boosts corporate margins, its negative impact on the labor market is becoming more pronounced. This creates a politically dangerous situation, especially in an election year, suggesting the 'backstop' for the AI boom is less certain than markets have priced in.
