Major companies like Nvidia, Broadcom and Microsoft have taken hits to their stocks recently. Many investors are pulling their money from Big Tech and moving it to other sectors for investment. Tech giants are going all-in on AI and data centers, but this rapid pace begs the question: How long can this keep up for? With many companies spending faster than profits can catch up, many believe the industry could be turning into a bubble ready to pop, similar to the dot-com bubble.
The AI surge began in 2022 when huge breakthroughs in large language models (LLMs) sparked a wave of excitement and possibility in the tech industry. Big companies like Google, Microsoft and OpenAI raced to the top as early as they could, pouring billions into hardware and new models. These big companies claimed the new advancements would change our society just as much as the internet did over 20 years ago, inspiring investors to invest in the novelty. All that rapid growth set the stage for today’s uncertainty about long-term stability.
“Trillions of dollars have been poured into this technology over the last four years, and all we have are chatbots and tools for writing emails,” TuHS senior Nico Cone said. “In recent months, more investors seem to be losing faith in AI as tech stocks like Meta and Oracle have dipped. These signs tell me that a collapse of AI stock prices may be imminent.”
Economists have warned that the speed of capital investment may be outpacing adoption. Companies are spending billions on GPUs, cloud infrastructure and research before seeing any profit, creating a risky situation for investors.
“Predicting bubbles is very difficult,” explained Christopher Duke, economics teacher. “Economists look for warning signs like very high stock prices compared to company earnings, lots of price volatility, and ‘acceleration’ in stock prices, meaning prices aren’t just going up, but they’re going up faster and faster. Even still, it’s hard to know if we are really seeing a bubble. Bubbles are more likely when dealing with something that is new, which investors have difficulty properly valuing. What is the future potential of AI? No one really knows, and so it invites people to invest large sums of money as they predict incredible applications of the technology, which may or may not be realized in the future.”
All of that uncertainty makes some investors increasingly nervous. “For example, NVIDIA is currently valued about $4.5 trillion, making it worth something like 20 times what McDonald’s is worth,” Duke said. “Is that the right valuation? With AI, some of the signs of a bubble are showing up — AI stocks look expensive and a bit jumpy — but not nearly as extreme as during the dot-com bubble of the late 1990s. Back then, prices skyrocketed much faster and valuations were far more disconnected from reality. History shows that about half the time, what looks like a bubble ends up being real growth, which makes predicting a crash very difficult.”
