AI after the market correction: are there signs of future trouble?

Stock declines are a reason to check risks

On October 30, the Nasdaq fell 2.9%, the S&P 500 lost 1.8%, and the Dow Jones dropped 1.1%. It was a bad day, but all three indices remained in positive territory year-to-date. It is too early to conclude that this correction marks the end of the AI boom. [1]

There are warning signs: heavy spending, an increasing reliance on debt, and profit expectations that have yet to be realized. However, a market correction alone does not prove that a collapse has begun. To reach such a conclusion, one must analyze corporate earnings, liabilities, and access to capital.

Three warning signs

First is the gap between investments and cash inflows. According to S&P Global Ratings, the combined capital expenditures of Alphabet, Amazon, Microsoft, Meta, Oracle, and SpaceX will exceed $1.3 trillion by 2027. The agency expects negative free operating cash flow for all six companies in 2026–2027. This is a forecast for this specific group, not global AI spending. [2]

Second is debt. The Bank of England’s July 2026 report highlights the rapid growth of credit financing for AI companies and the complexity of debt structures. If revenues fall short of plans, servicing these obligations will become increasingly difficult. [7]

Third is high expectations. The same report points to the concentration of stock indices in a narrow circle of AI companies and valuations based on strong future earnings growth. Disappointment in a few major players could hit the broader market. [7]

Physical infrastructure does not guarantee a profit. During the internet boom, fiber optic networks were built, some of which remained underutilized for a time. Servers and data centers have value, but an investor will only profit when demand and pricing ensure a sufficient return on invested capital. [6]

Oracle: targets set, results still to come

At its Investor Day on October 28, Oracle defined timelines for reaching positive free cash flow and the limits for additional financing. These goals allow for performance tracking. For now, these are management promises. [3]

The main risk is the discrepancy between these targets and actual results. If customer payments arrive more slowly while costs remain high, the company will require more financing. Investors should track actual performance, not just the size of announced contracts.

Cheaper models create opportunities for application businesses

According to the Stanford AI Index, the cost of processing requests with models reaching GPT-3.5 quality on the MMLU test dropped more than 280 times between November 2022 and October 2024. This compares different models at the same quality threshold. [5]

This is an argument against the conclusion that the benefits of AI will vanish along with expensive stocks. More accessible models allow for cheaper automation of document processing, customer support, and corporate data search. There remains room for profitable business here.

However, a cheap request does not mean a cheap service. The bill includes integration, support, answer verification, and error correction. One must calculate the cost per completed task. If an active client consumes more compute while paying the same subscription fee, increased usage could reduce margins.

When a correction could turn into a crisis

The warning signs would become much more serious if the following happened together:

• Revenues repeatedly fall short of expectations. Companies lower guidance, clients cut orders, and new capacity remains underutilized.
• Financing becomes unavailable. Borrowers struggle to raise money or refinance debt; the number of delinquencies and defaults increases.
• Cost-cutting spreads through the chain. Major customers delay projects, suppliers lose revenue, and creditors tighten requirements.

This is a crisis scenario, not a description of a proven collapse. The data presented shows vulnerabilities but does not confirm that this entire chain has already been triggered.

So, are there signs of future trouble?

Yes. The gap between spending and revenue, rising debt financing, and high profit expectations are signs of market vulnerability. They increase the risk of a sharp repricing, but do not yet prove a crash is inevitable. The greatest danger is if weaker earnings coincide with debt issues and a loss of access to financing.

For an investor, the goal is to profit from business value growth and its earnings. I would look for companies with recurring customer payments, sustainable margins, and the ability to operate without constant new capital injections. But even a strong business can be a bad investment if purchased at too high a price.

A correction can create favorable entry points. The price drop alone is insufficient: the expected return must justify the risk, and the business prospects must be confirmed by results.