The global financial markets are experiencing a major turning point this week as investors wake up to the hard truth about artificial intelligence spending. For months, markets had been riding on pure excitement about AI, but that enthusiasm is now hitting a wall of reality. The key issue is simple: companies are spending enormous amounts of money on AI infrastructure—equipment, data centers, and computing power—but it is not yet clear if they will make enough money back to justify these investments.

The S&P 500 index, which is the most watched measure of the United States stock market, is currently sitting on what technical traders call a "cliff edge." The index shows a clear "Head and Shoulders" pattern forming on its daily price chart. This is an important technical signal that often appears right before major downturns happen. The critical level everyone is watching is the 6,790 mark. As long as the market holds above this level, traders believe there is still a chance for small bounces or sideways movement. However, if the market closes below 6,790 on a daily basis, it could trigger a wave of selling that sends prices much lower.

One of the biggest changes happening right now is the split between different types of stocks. The NASDAQ, which contains many technology companies, is already falling hard because so many AI companies trade there. Meanwhile, the Dow Jones Industrial Average, which includes older, more traditional companies, has actually held up better because money has moved into what investors call "defensive stocks" like Walmart. This difference, called a divergence, is a warning sign that the market may be getting weaker overall.

The real story behind all this is that investors are finally asking the hard question: will all this spending on AI actually work? Big technology companies are spending over $700 billion this year on AI infrastructure, which is much more than they spent on similar technologies over an entire decade in the 1990s internet boom. Some experts compare this situation to a trader using excessive leverage—if the investment does not pay off quickly, it could blow up the entire account. The problem is that smaller technology companies that have borrowed heavily or spent all their cash on AI are in the most danger. Giants like NVIDIA or Alphabet have enough money to survive if things go wrong, but medium-sized companies could face bankruptcy.

Another twist in the market is that the relationship between interest rates and stock prices has completely flipped. For many years, investors believed that lower interest rates were good for stocks and higher rates were bad. But that thinking is changing. Now, when interest rates go up, investors see it as a sign the economy is strong, so the market goes up too. When rates go down, investors worry it means the economy is slowing down, so the market drops. This represents a major shift in how traders should think about economic news.

Despite the bearish outlook, traders are still finding opportunities. NuScale Power, a nuclear energy company, crashed 75% from its peak but is now entering what value traders call a "buy zone" between $10.25 and $11.25. Similarly, Netflix might offer a good entry point around $68 to $69 if the stock continues to fall. This is where experienced traders wait patiently for a falling stock to hit bottom before trying to catch it like a skilled player catching a falling knife.

The broader market insight is that the software industry has been hit especially hard, with about $2 trillion in value wiped off software company stock prices because investors worry that artificial intelligence programs might replace many software services that currently exist. Companies in legal services, IT support, consulting, and even logistics are being repriced downward as investors question whether AI will make their services less valuable. This repricing is happening faster than many expected and is creating significant opportunities for disciplined traders who can spot the difference between stocks that are fairly priced and stocks that have fallen too far too fast.

Exports are also warning that this market repricing could swing too far in the other direction. While it is true that some companies will lose out to AI, the real challenge is that we will not have enough evidence until the end of 2026 to know for sure which companies are the long-term winners and losers. This uncertainty means that big mood swings in the market will probably continue throughout this year and beyond as new information comes out about which AI investments are actually working.