Have you ever used Generative AI to do your work before? Maybe you even feel a bit reliant on it, like you have to run every piece of writing youâve done through it, just in case. If so, you might not want to get too attached to it just yet. You might have heard the term âthe AI bubbleâ on the news or social media lately, with warnings of catastrophe not unlike the Dotcom bubble in 2000, but what does that really mean? Most of us individually might not be able to do anything about the AI bubble, but learning more about it can help us understand what might happen to the economy, AI technology and government policy when it does burst.
To start, letâs talk about the Dotcom bubble to understand the comparison. In the late 1990s, Internet-based company stocks skyrocketed. Their price increased because of swarms of investors chasing growth and profit, often ignoring whether these businesses were making any real money. Investors, afraid of missing out, ignored traditional investing philosophy and poured funding into internet start-ups that had no plan for how to make money. Other weak points that started to crack include $500 billion of debt borrowed to build fiber optic networks that could never be repaid, and circular financing, where Lucent Technologies, a telecommunications manufacturer, famously lent money to other companies for them to buy its equipment.
However, in 2000, the bubble started to burst. Start-ups that were valued at hundreds of millions of dollars blew through the money they were given and generated none back for the shareholders, turning them worthless in a matter of months. A well-known example is Pets.com, an online pet supply delivery business that raised $82 million as soon as it went public but went bankrupt months later due to the ownerâs lack of expertise and a lack of general demand at the time. While a few like Amazon and eBay famously survived the bubble and are still well-known today, hundreds more folded like Pets.com, taking the fortunes that investors poured into them with them.
Thereâs some scary similarities between the financial markets in the late â90s and today. Everywhere I look, from Microsoft pushing AI in its every service to Instagram reels advertising products that can complete any assignment, companies are justifying billion-dollar investments into AI and start-ups are creating GPT wrappers for any niche function imaginable, trying to get a slice of the pie before the market is saturated. Credit markets are financing $1.5 trillion of spending on data centres and other hardware, not even including whatâs being spent internally. Weâre even seeing repeats of circular financing, such as Nvidia investing billions in OpenAI, which then uses that money to purchase Nvidia chips.
However, there are some key differing factors this time. The difference maker is whether generative AI demand truly exists and whether its monetizable. For all the companies trying to create AI integration, how many users are really jumping at the chance to use Co-Pilot in their Excel? How many users are willing to pay for AI services? Without an end goal of how these trillion dollar investments are going to be paid off, the cracks are soon going to start showing. I, personally, am pretty skeptical. One MIT study finds a 95% failure rate for AI solutions, attributed to integration and usage, rather than the models themselves. Companies are trying to hide the lack of impact their AI models are having to appease shareholders.
While Forbesâ Peter Cohan believes a continued boom is still the likeliest outcome, Iâm not as optimistic. While innovation is still ongoing, I canât see how profits can outweigh the insane investments being poured in with AIâs current development. On the other hand, the worst case scenario would be one where OpenAI, the keystone piece keeping this whole AI structure from collapsing, goes bankrupt, dragging other players like CoreWeave and Nvidia with it. Given seven tech companies currently make up over a third of the entire market, this kind of decline could wipe out trillions of dollars and cause some serious distress to the economy. So, even if we canât stop the AI bubble from ever bursting, staying curious and financially aware helps us avoid the biggest pitfallsâwhether or not the hype lives up to reality.