WHAT HAPPENED
The Federal Reserve announced this week that it is holding interest rates steady, maintaining the cost of borrowing at current levels rather than raising or lowering them. The decision came after weeks of economic reports and Fed communications signaling that inflation [the rate at which prices rise] has not fallen as quickly as hoped, but also that the job market remains resilient. The Fed did not provide new guidance on when rates might move in either direction, leaving that question open based on future economic data.
Against this backdrop, investors and analysts are now focused on earnings announcements from major technology companies, particularly those heavily invested in artificial intelligence infrastructure. The question drawing market attention is whether companies like Microsoft and Meta will reveal that their spending on AI systems and computing power has grown faster than their revenue, or whether they can demonstrate that these expensive investments are generating returns. No specific announcements have been made yet, but the earnings season ahead is expected to clarify how sustainable the recent enthusiasm for AI stocks has been.
THE ANALYSIS
By Kanin Alldredge, Senior Strategist, The Currency Classroom.
When a company spends heavily on something new, a factory, a technology platform, a new market entry, there is always a gap between when the money goes out the door and when the money comes back in. During that gap, the company either has to believe the payoff will arrive, or it has to have so much cash that the waiting does not matter. With AI spending at the scale we are seeing now, both of those questions are being tested in real time. You are watching a market try to figure out whether the largest technology companies in the world are making a bet that will pay off, or whether they are caught in a spending spiral that can only end one way.
Here is what matters about the Fed holding rates steady: it means the cost of capital [the price a company pays to borrow money] is not going down, and it is not going up. For a company spending billions of dollars on infrastructure that might or might not work, this matters enormously. If rates were falling, if borrowing were becoming cheaper, a company with uncertain returns might still look attractive, because you could at least borrow the money cheaply while you waited to see if the bet paid off. But rates are not falling. The Fed is saying through its actions: you will pay this price to borrow, and inflation is still a problem we are watching. That changes the math for every dollar a company is spending on AI right now.
The reason the market is so focused on what Microsoft and Meta say about their AI spending is not hard to explain. These two companies, along with a few others, have become the primary owners of the AI investment story. Their choices about how much to spend, and their willingness to tell investors that those spending levels make sense, have been the main thing supporting stock prices in the "AI" category. This is important to understand: when we talk about "AI stocks," we are usually not talking about a whole sector. We are talking about a handful of giant companies that have decided to spend enormous sums on this technology, and the thousands of smaller companies, funds, and investment products that have been built on the assumption that this spending will continue and will eventually work. If that assumption cracks, the effect will be swift and wide.
THE ANALYSIS (continued)
The chain of cause and effect runs like this: Companies announce spending levels. Investors decide whether those levels seem wise or reckless. If investors believe the spending is wise, stock prices go up. Money flows into funds designed to capture AI growth. Those funds buy more of the stocks that companies own. That buying pressure pushes prices higher still. A feedback loop forms. Now, the Fed is saying it will not make borrowing cheaper, which is one of the ways a company might justify high spending on an uncertain payoff. Instead, you will have to see returns. You will have to see revenue. You will have to see the gap between the spending and the payoff narrow, or close.
That is what the earnings announcements will show or will not show. They will reveal whether the companies spending the most are seeing their revenue grow faster than their costs, or whether costs are growing faster. If costs are growing faster, the math becomes harder to defend, especially with capital [money available for investment] priced where it is now. This does not mean AI is not real, and it does not mean these companies will stop spending. It means the story changes from "spend whatever it takes and trust the future" to "spend what you can justify with current returns," and those are very different stories for investors.
WHY IT MATTERS
You need to understand this: the enthusiasm for AI stocks over the past year has not been based on proven earnings from AI. It has been based on the belief that these earnings will arrive. When you buy a stock in a company that is spending heavily on something unproven, you are making a bet on the future, you are saying, I believe this will work, and I believe it will work before the company runs out of money to spend or before investors lose patience. The Fed keeping rates steady does not change whether AI will work. It changes the timeline. It makes patience more expensive. It makes the gap between spending and return feel longer.
The second-order effect moves through multiple channels. If investors begin to doubt whether the spending will justify itself, they will sell shares. When they sell, the price falls. When the price falls, the companies find it harder and more expensive to raise new money through the stock market. Some of these companies have been using their valuable stock as a form of currency [a way to pay for things], offering stock to employees, to partners, and in acquisitions. A lower stock price makes that more difficult. It also makes the internal math of the company harder: if we spent a billion dollars on computing power and the value of our stock fell 30 percent, we need to either generate more revenue, or we need to spend less, or both. None of those options is painless.
The third-order effect reaches the broader market. A sharp reversal in AI stocks would confirm something investors have been nervous about for months: that capital [money available for investment] in this cycle has been misallocated [sent to the wrong places]. Not all misallocation is equally damaging, but it does tend to make investors more cautious about other bets. You would see lending standards tighten. You would see less appetite for other high-cost, long-payoff investments. You would see capital flowing away from growth and toward safety. None of that has happened yet. This is why this week's Fed decision and the earnings announcements to come matter so much, they are the test of whether the current allocation of capital can hold, or whether it cracks.
WHO IT REACHES
The most direct exposure belongs to anyone holding shares in the technology companies making the largest AI investments, either directly or through a fund [a pool of money that a professional manager invests across many companies]. If you own a technology-focused mutual fund or ETF [an exchange-traded fund, a type of fund that trades like a stock], you almost certainly have exposure to these companies. You may not know the dollar amount, but it is there. Your exposure is to the question: will the earnings justify the spending? If they do not, your holding falls in value. If they do, you benefit from the upside. This is what it means to have exposure to this trade, you own a piece of the bet, whether you intended to or not.
The second layer of exposure runs through other companies that supply the infrastructure AI needs: makers of computer chips, providers of cloud computing [the servers and software that businesses rent to run their operations], and the companies that transport and manage power for data centers. If the AI spending story slows, these suppliers face reduced demand. They also face the possibility that their biggest customers will demand lower prices because the AI companies are themselves under pressure. The effect ripples outward. Even a person with no direct technology holdings can have exposure through a 401k or pension plan that holds diversified funds, which often include technology companies in their mix.
WHAT IT MEANS FOR EVERYDAY MONEY
The path from this story to your wallet is not direct, but it exists. If companies slow or redirect their spending on AI infrastructure, it affects hiring in technology and construction. It affects the profitability of the companies that supply chips and computing equipment. It eventually affects the price of the products you use, cloud storage, online services, the devices that rely on modern computing, because those prices are shaped by the cost of the infrastructure underneath. The timeline, though, is important: these effects usually take months to appear in consumer prices. A sharp reversal in AI spending this quarter would not show up in your utility bill or your software subscription price this month. It would show up gradually as companies adjust their plans and as the effect cascades through supply chains. What happens faster is stock prices and the effect on investment portfolios, which can matter if you are near retirement or planning to access savings.
WHAT WOULD CHANGE THIS
Watch for three specific things that would either confirm or overturn the reading above. First, listen to what Microsoft and Meta say about their AI spending plans in their coming earnings calls. Specifically, watch whether they commit to the same level of spending next year as this year, or whether they hint at moderation. If they say they will keep spending aggressively and they can point to revenue growing faster than costs, that is one outcome. If they say they need to watch and wait, that is another. The difference is crucial.
Second, watch whether other technology companies with exposure to this spending, chip makers, cloud providers, infrastructure companies, raise or lower their guidance [their forecast of future earnings]. If they guide lower, it suggests the people closest to the AI companies' spending plans are seeing weakness. If they guide higher, it suggests demand remains strong. Third, watch the Fed's own statements in the weeks ahead. If inflation data improves noticeably, the Fed might signal that it is open to lowering rates in coming months. That would reduce the cost of capital and make the case for patient, long-term spending easier to make. No rate cut has been announced, but if one becomes more likely, it changes the math for companies spending heavily on uncertain returns.
KANIN'S CORNER
There is a difference between patience and passivity. Patience is a choice to wait while you gather information. Passivity is the absence of a choice, waiting because you have not decided. Watching the AI spending story unfold requires patience, not passivity. You are waiting to see whether the companies involved can justify their bets, and that is information worth waiting for. The difference is that you are watching for it, not ignoring it. You have checkpoints, earnings announcements, forward guidance, Fed communications, and you are checking them.
What this story also teaches is that the cost of capital matters in ways that are easy to overlook when times are good. When borrowing is cheap and stock prices are rising, spending on uncertain bets feels like a smart move. When capital becomes more expensive and investor patience wears thin, the same spending looks reckless. The Fed did not change the nature of AI this week, it held rates steady. But it did confirm that capital will stay priced at current levels, not cheaper levels. That is a change that matters, and it is a change that many AI investors may not yet have fully priced in. This report is educational information, not financial advice.