AI fever seems to have taken over the world. Silicon Valley giants and tiny startups alike have raced to capitalize on the transformative technology, causing a wave of innovation, investment and adoption across several industries.
But not everyone is buying the hype. As billions of dollars pour in and valuations skyrocket, some skeptics wonder whether all of this will last — or if the AI industry is simply a bubble about to burst.
Is There an AI Bubble?
AI startups are hitting valuations that far exceed their actual earnings, while tech giants are investing billions into AI innovation, despite limited profits from their AI products. Together, these trends suggest that AI could be the next bubble to burst.
What’s a Bubble, Again?
In economics, a bubble refers to a situation where the price of an asset rises way too high (usually because of hype and excessive buying) and eventually crashes, causing financial losses and business failures. Two notable examples: the dot-com bubble of the 1990s, where the overvaluation of internet startups led to the 2000 stock market crash; and the housing bubble of the mid-2000s, where risky lending blew up the housing market in 2007, setting off the Great Recession.
Is There an AI Bubble?
Bubbles can only be conclusively identified after they’ve popped. That said, the AI industry does appear to be in the midst of one, insofar as widespread hype and an influx in speculative investments are driving much of its current growth.
As public interest and media coverage has grown, companies eager to capitalize on AI’s perceived opportunities have poured billions of dollars into the technology. This is occuring in spite of the AI’s many fundamental challenges — and the difficulty of finding ways to make money off it.
“The expectations of [AI] are far beyond what the technology can deliver,” Xun Wang, chief technology officer at marketing automation company Bloomreach, told Built In. “There’s a whole bunch of people who think that they can deploy this technology to solve everything and replace everything. But that’s just not going to happen.”
Still, tech companies continue to promote ambitious AI visions, hoping they can figure out the revenue part later. And so the bubble keeps getting bigger.
When Did the AI Bubble Begin?
After decades of sporadic growth and decline, the artificial intelligence industry hit its stride in November of 2022, when OpenAI released ChatGPT. Built on a transformer architecture (a type of neural network originally introduced by Google in 2017), the chatbot could understand and generate natural language in coherent, human-like text responses, showcasing the powerful potential of generative AI to the world for the first time.
“It grew the visibility of what AI could do,” Erik Brown, senior partner of AI and product engineering at West Monroe Partners, told Built In. “That drove this hype cycle.”
Excitement escalated into full-blown hysteria. Venture capitalists invested billions into AI startups, including everything from AI-powered lawyers and therapists to image and music generators. Suddenly, every company was an “AI company.”
“We’re kind of doing a spray and pray, where we’re investing in all of these companies and hoping one or two of them do well,” Gayle Jennings-O’Byrne, a venture capitalist and CEO of Wocstar Capital, told Built In.
“Everyone’s rushing in because they don’t want to miss out on ‘the next big thing.’”
“I’ve seen deals where there’s no revenue, there’s no customers. We don’t know if the market is going to want this, if people are going to want this. And yet they’re able to raise millions of dollars,” she continued. “Everyone’s rushing in because they don’t want to miss out on ‘the next big thing.’”
Legacy tech giants like Google, Amazon and Meta raced to keep up, building their own AI products. Nvidia, the main supplier of the computer chips needed to train AI models, is now among the most valuable companies listed on the public stock exchange.
Long-term, many experts see AI as a generation-defining technology, claiming it will revolutionize modern life in the same way mobile phones, the internet and electricity did. In some ways, it already is.
But some doubts are starting to overshadow the initial excitement around AI, as concerns mount over whether these companies will ever recoup the billions invested in its development — or if those returns will materialize anytime soon.
Signs the AI Bubble May Be Bursting
Although artificial intelligence is still receiving a significant amount of money and attention, the industry appears to be cooling off a bit — perhaps indicating that the AI bubble is bursting.
Hype Is Waning
Despite the massive investments and high expectations, the AI hype machine appears to be slowing down. New scientific papers have come out undermining some of the flashier claims about the technology. And drastic warnings about AI posing an existential threat to humanity or taking everyone’s jobs have largely subsided, replaced by more technical conversations around accuracy and explainability.
“We’ve gone along this hype cycle and are now in the trough of disillusionment so to speak, where people are realizing that [AI] is not all magic and fairy dust,” Brown said. “We’re seeing a more practical approach to it now.”
Profits Are Lacking
Although some tech companies have spent a lot of money on building out their data centers and computing infrastructure, their AI products lack clear paths to monetization. Aside from the actual hardware makers, few are seeing real returns, raising concerns about whether they’ll be able to recoup the billions of dollars they’ve invested in AI.
Major AI investors like Goldman Sachs and Sequoia Capital have issued reports expressing doubts about the sustainability of AI, arguing the technology may not be able to generate the level of profits needed to justify the billions of dollars being funneled into its development. David Cahn, a partner at Sequoia, estimates that the tech companies will need to generate about $600 billion in revenue to make up for all the money it’s spending on AI — a number they are nowhere close to right now.
“Those who remain level-headed through this moment have a chance to build extremely important companies,” Cahn wrote in his blog post. “But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. That delusion says that we’re all going to get rich quick.”
Success Is Lagging
Many of the top tech companies remain committed to AI, telling investors that they actually plan to ramp up spending in hopes of future financial success. For instance, Microsoft’s CFO, Amy Hood, noted in an earnings call that the company’s investments in data centers are expected to support monetization of its AI technology “over the next 15 years and beyond.” Similarly, Meta’s CFO, Susan Li, stated that, while the company doesn’t expect its AI products to be a meaningful driver of revenue in 2024, it believes these investments are going to “open up new revenue opportunities over time” that will lead to “solid” returns.
That time horizon is unconventional for many investors, who are more accustomed to the regular quarterly sales and profit growth typical of Silicon Valley software companies, according to Jennings-O’Byrne.
“[AI] is very capital intensive, between the databases you need to build and the computational power that’s needed,” Jennings-O’Byrne explained. “We’re not going to see the profits in the same way and with the same speed that we’re used to.”
AI may not be the best at driving revenue yet, but its ability to “drive efficiency” is already clear, Ricardo Madan, senior vice president at tech services company TEKsystems, told Built In. Companies that are able to leverage that efficiency into commercially successful, enduring AI products stand to win big.
Will the AI Industry Last?
None of this is to say that AI itself doesn’t have revolutionary potential, nor that the industry won’t see big profits eventually. The dot-com bubble of the 1990s saw much higher over-investment and overvaluation than what the AI industry is experiencing today, yet its collapse paved the way for giants like Google and Amazon. The same will likely be true for a select few AI companies.
“That’s how the economy readjusts itself to be efficient, it’s a natural part of things,” Wang said. “There will be companies that go out of business, there will be layoffs. And then it will readjust and we will continue to refine the technology.”
And while the current AI landscape may appear bubble-like, the underlying technology and long-term potential of the industry indicate it will have a lasting impact — even after it initially bursts. Built on decades of research and technological advancements, AI’s core value lies in its ability to process massive amounts of data, which makes it inherently good at recognizing patterns and making complex decisions. So, despite this short-term volatility, many believe the next wave of AI giants is right around the corner.
“At the end of the day, we will come up with another five, 10, 20 AI-native, trillion dollar companies that will change our lives,” Wang said. “We will all be using AI in some way.”
Frequently Asked Questions
Is there an AI bubble?
Bubbles can only be conclusively identified after they’ve popped. That said, the artificial intelligence industry does appear to be in the midst of an economic bubble, insofar as high expectations and massive investments have yet to yield significant profits for companies. But the underlying technology and long-term potential of AI indicate it will have a lasting impact — even if some overvalued companies ultimately fail.
What are the consequences of the AI bubble?
If the AI bubble bursts, companies heavily invested in the technology will likely face significant financial losses, leading to layoffs and a decrease in innovation. A crash may also result in a loss of trust in AI, which could hinder future investments and development down the line.
