Generative AI has been the most hyped tech development since the release of OpenAI’s ChatGPT in 2022. Since then, AI has taken over parts of everyday life – and the stock market.
However, recently, there have been rising concerns over the “AI bubble” bursting like the “Dot-com bubble” did around 2002.
The dot-com bubble began when the internet first became mainstream, sparking excitement in the stock market for nearly any company that had anything to do with online interests or business. By the late 1990s, investors had flooded these internet-based companies (dot-coms) with cash, driving up their stock prices.
It wasn’t until the early 2000s that people started to realize some companies were failing to meet expectations. In March 2000, the stock market started a sharp decline, which marked the burst of the dot-com bubble, and some internet companies folded. Many people lost their jobs, and some people who invested in these companies lost much of their savings.
Today, some companies that have invested in AI have not profited as much as they would have expected, drawing fears of a similar kind of tech bubble.
The Entrepreneur reported that 95% of companies investing in corporate AI projects have not seen any returns on their AI investments. A key issue was that companies were using AI for the wrong purposes — such as sales and marketing — instead of administrative and repetitive tasks that might have actually brought revenue.
A few fast food restaurants, for example, had tried to implement AI into their drive-thrus. Many of these attempts failed as the AI continued to misinterpret orders. McDonald’s ended the system in 2024 after too many frustrating malfunctions. Taco Bell faced similar problems.
Additionally, the public is not very excited about the new AI technology. In fact, most people have feelings of concern, compared to just 16% of people who are more excited than concerned.
“I can’t really remember a boom with such active hostility to it,” economist and financial historian William Quinn told The New York Times.
An economic bubble is characterized by a rapid surge in asset prices driven by largely speculative ideas and FOMO – fear of missing out. This characterization is apparent in some companies today.
Amazon’s CEO had disclosed that they plan to spend $200 billion on AI in 2026. Alphabet, Google’s parent company, predicted spending around $185 billion. TikTok has recently introduced its own AI chatbot, TikTok Tako.
Investors have expressed worry that the billions the tech giants are putting into AI could take years to pay off. According to The New York Times, both Amazon and Microsoft’s share prices fell 10% after their spending plans were disclosed.
An article in Fortune magazine raised concerns over OpenAI’s accumulating debt and worrying predictions. The company has stated that they predict significant losses throughout 2028 and then a rise starting in 2030.
However, the market is unpredictable. In 2024, investor anxiety spiked following the release of DeepSeek, a Chinese-developed generative AI model that demonstrated strong performance at reportedly lower cost. The announcement triggered a sharp sell-off in several U.S. AI-related stocks as investors worried about rising global competition and narrowing technological advantages.
OpenAI’s choice to accept losses for the next three years is risky. AI is constantly evolving; investors are constantly fickle. If they lose their innovative momentum during those three years, they could fall behind in the AI race. If they fall behind, there’s a chance they’ll never catch up.
“The low-hanging fruit is gone,” experienced asset manager George Noble said to Futurism. “Every incremental improvement now requires exponentially more compute, more data centers, more power.”
All of this reflects the classic signs of an economic bubble.
Right now, AI appears to be in a euphoric stage, with massive spending, high expectations, and companies rushing to adopt the technology out of fear of being left behind. Their expectations are starting to outweigh real returns, with many AI projects failing to generate profit despite enormous investments.
Like the dot-com era, AI itself may endure, but today’s stock prices may not – which would be bad news for people who invest in the market.
