The real question we should all be asking about AI

The stock market is currently showing a lack of confidence in Big Tech companies. This trend is evident in the recent performance of major tech giants such as Google, Intel, Amazon, and Meta, all of which have experienced significant declines in their stock prices. The Nasdaq, a key index for tech stocks, is also on the verge of a correction, falling just over 1% from its all-time high.

The primary concern surrounding AI is the substantial investment needed to build the necessary infrastructure. AI companies are spending more and more on data centers, which outweigh the profits generated by their businesses. In fact, the total amount spent on AI since 2023 has reached an impressive $1.6 trillion, with projections suggesting that annual spending could hit a staggering $1 trillion in the coming decade, according to JPMorgan.

Despite the overwhelming spending on AI, the bond market appears to be unconcerned by this development. Lenders are readily available to provide debt financing for Big Tech companies to fund their AI endeavors. This situation raises the question of how much longer the bond market will support this nonstop spending spree. The answer to this question will ultimately determine whether AI turns out to be a successful venture or a failure.

The process of generating profit from AI investments involves substantial upfront costs for infrastructure, such as data centers, servers, chips, power, labor, and building materials. These costs are typically paid back to investors within three months to two years after the data center is operational. Big Tech companies, particularly Google, Amazon, Microsoft, and Meta, have been responsible for over a third of all capital expenditures from the S&P 500 in the past year, with this figure expected to rise in the future.

Currently, approximately $250 billion worth of debt is financing these expenditures, with projections anticipating it to peak at 35% of hyperscalers' spending by the end of the year.