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. In fact, AI contributed to as much as 20 percent of real gross domestic product growth in just the third quarter of 2024 in the United States and is poised to remain a pivotal part of the country’s economy.
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 artificial intelligence 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 we could be living through an AI bubble.
What Is a Bubble in Economics?
In economics, a bubble refers to a situation where the price of an asset rises way too high (usually because of hype and excessive demand) and eventually crashes — known as the bubble “popping” or “bursting” — causing rapid valuation decreases, financial losses and business failures.
Notable examples of bubbles include 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 have several characteristics of a bubble, 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. According to PitchBook, deals involving AI leaders OpenAI, xAI, Anthropic, Waymo and Databricks made up over 43 percent of the $74.6 billion in venture capital funding in the fourth quarter of 2024.
The uncertainty around AI grows when considering that the technology already comes with many fundamental challenges, including the difficulty of finding ways to make money off of it, and how impactful it will really be for automating work and changing the future of the job market.
“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. In 2025, Microsoft, Meta, Alphabet and Amazon plan to spend a combined $320 billion on AI and the data centers needed to power this technology as the competition heats up. And so, the bubble keeps getting bigger.
When Did the AI Bubble Begin?
After decades of sporadic growth and decline, the AI 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.”
Legacy tech giants like Google, Amazon, Meta and Nvidia raced to keep up, building their own AI products. Meta in particular, which is going all-in on AI development with its Meta Superintelligence Labs division, exceeded Q2 2025 revenue estimates and surpassed profit projections for the 10th quarter in a row. As for Nvidia — the main supplier of the computer chips needed to train AI models — it is now among the most valuable companies listed on the public stock exchange and became the first publicly traded firm to reach $4 trillion in market capitalization, all thanks to the growing AI space.
“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,” 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.’”
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. 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 have largely subsided, replaced by more technical conversations around accuracy and explainability. Plus, with the release of OpenAI’s highly-anticipated GPT-5 model, it failed to meet hyped expectations as a revolutionary step toward artificial general intelligence.
“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.
For example, Alphabet plans to spend 29 percent more on AI than expected in 2025, frustrating investors who are concerned about the company’s faltering cloud revenue. And while OpenAI reached a $500 billion valuation, the company has not disclosed whether it is actually close to profitability. Additionally, in an August 2025 report by MIT’s NANDA initiative, it was found that 95 percent of generative AI pilot programs at companies are failing, while only five percent are achieving rapid revenue acceleration for companies.
Major AI investors like Goldman Sachs and Sequoia Capital have also 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 were nowhere close to as of 2024.
“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, with Amazon, Microsoft and Meta planning 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. With this in mind, Meta invested billions of dollars in recruitment for its Meta Superintelligence Labs division, though has frozen AI hiring indefinitely following this rapid spree.
The time horizon for AI’s success 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.
What Does the Future of AI Look Like?
The future of AI has reached a crossroads, offering both persistent optimism and lingering unease. While it’s impossible to foresee which direction the industry will take, here are a few possible paths for AI.
AI Progress Continues to Accelerate
While the current AI landscape may appear bubble-like, the underlying technology and long-term potential of the industry could have a lasting impact. 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. This can be a major boon for businesses that are looking to establish more efficient data analysis processes.
And enhanced capabilities could be right around the corner with the push to develop and deploy agentic AI — the use of AI agents to complete a broader set of complex tasks without any human assistance. The Trump administration may further accelerate AI’s progression, promising to expedite the development of U.S. AI data centers, export American-made AI hardware, deregulate the industry and invest $500 billion through 2028 to reinforce the United States’ AI infrastructure through its Stargate Project.
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.”
AI Technology Stagnates and a Few AI Companies Remain
There is a real possibility that AI fails to live up to the hype. Even then, an increasing number of businesses will rely on it as an essential tool to get ahead. According to an Ernst & Young survey, 95 percent of organizations are investing in AI and seeing improvements in areas like operational efficiencies, employee productivity and customer satisfaction. Likewise, a McKinsey report found that 92 percent of companies will ramp up their generative AI investments from 2025 to 2028.
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.”
The AI Bubble Bursts Like the Dot-com Bubble Did
Of course, the American AI industry could collapse. A Chinese chatbot known as DeepSeek-R1 was released in January 2025 and displayed much lower costs and energy usage than its U.S. competitors. The move sent investors into a panic, resulting in the U.S. tech index losing $1 trillion in value.
DeepSeek revealed that the biggest AI names are vulnerable, hinting at a future where open-source AI could upend the entire tech landscape. While this would democratize AI tools and make them more affordable, it could also undermine larger investments and expose organizations that practice AI washing — exaggerating or flat-out lying about a company’s AI offerings to generate hype. This could weaken trust in the AI industry as a whole.
Still, it’s hard to imagine these developments leading to the complete erasure of AI from society. The technology has become entrenched in key industries like healthcare, cybersecurity, logistics and manufacturing, forever changing how many businesses and organizations operate. And investments in AI startups have stayed strong in the face of DeepSeek’s arrival. While the industry may go through more ups and downs, AI will likely continue to play a meaningful role in everyday life for years to come.
Notable AI Funding and Investment Milestones
To understand the current state of the AI market bubble, it is important to track the flow of capital into AI and infrastructure companies. Below are some of the most significant AI investment milestones that have contributed to the growth of an alleged AI bubble.
OpenAI and Broadcom Collaboration Announcement (October 2025)
OpenAI and Broadcom announced a major, multi-year collaboration to co-develop and deploy custom AI accelerators designed by OpenAI. This move signaled OpenAI’s deep commitment to controlling its hardware pipeline, aiming to embed insights from frontier model development directly into the chips themselves. The goal of this collaboration is to develop and deploy 10 gigawatts-worth of these new accelerator systems, scaled using Broadcom’s Ethernet solutions, to meet the surging global demand for AI compute power through 2029.
Although no financial details were officially disclosed, sources told The Wall Street Journal that the deal is worth several billion dollars. Broadcom’s stock also rose about 10 percent following the announcement — a trend seen among several other partners who have partnered with OpenAI.
Reflection AI Raises $2 Billion in Funding (October 2025)
Reflection AI, a New York-based developer of large language model training systems, successfully raised a $2 billion funding round. The investment, backed by Nvidia and numerous venture capital firms, highlighted the continuing shift in focus toward “open standards” models as a viable alternative to closed-source systems. Reflection AI’s October 2025 funding underscores investor confidence in the long-term profitability of developing open-source AI infrastructure, signaling that competition is growing beyond the top foundational model labs.
OpenAI Reaches $500 Billion Valuation (October 2025)
OpenAI achieved a $500 billion valuation in October 2025 following a share tender offer that allowed employees and early investors to sell their Open AI stock. This milestone cemented OpenAI as one of the most highly-valued private technology entities in the world. It also underscored the market’s explosive confidence in the commercialization potential of artificial general intelligence (AGI) and the anticipation of its continued dominance in the global technology landscape.
Anthropic Raises $13 Billion in Series F Funding and Reaches $183 Billion Valuation (September 2025)
Anthropic raised $13 billion in Series F funding, resulting in a total $183 billion valuation for the company and solidifying its position as a major competitor in the generative AI space. The capital was raised by Anthropic to finance its aggressive research and development pipeline focused on safety and alignment. This funding round was a significant driver of 2025’s third quarter global venture funding surge, confirming that venture capitalists are concentrating capital on a small number of proven AI giants rather than distributing it widely across the ecosystem.
Meta Invests $14.3 Billion in Scale AI and Recruits Scale AI CEO at Meta (June 2025)
Meta invested $14.3 billion in data-labeling and evaluation firm Scale AI, acquiring a 49 percent non-voting stake in the company and recruiting Scale AI CEO Alexandr Wang in the process to lead the TBD Lab under Meta’s Superintelligence Labs. The deal emphasized that Big Tech companies are willing to deploy immense sums to secure proprietary AI talent and infrastructure resources, especially when regulatory barriers complicate outright mergers or acquisitions.
OpenAI Raises $40 Billion in Funding Round (March 2025)
OpenAI raised $40 billion in a March 2025 funding round led by SoftBank, pushing the company’s valuation to over $300 billion. This single investment was so large that it accounted for over 50 percent of all global venture funding in the first quarter of 2025, dramatically inflating the market’s overall figures. The scale of this fundraise demonstrated investors’ belief in OpenAI’s dominance in the technology space.
Databricks Raises $10 Billion in Series J Funding (December 2024)
Databricks raised $10 billion in a Series J funding round, increasing the company’s total valuation to $62 billion. Databricks, which provides a data and AI platform built on Apache Spark, leveraged the funding to scale its infrastructure and expand its market share in the enterprise data sector. This was one of the largest single venture funding deals of 2024, and showed that the AI funding boom extended beyond core foundation models into the platforms and infrastructure required for large companies to deploy machine learning at scale.
Frequently Asked Questions
Is there an AI bubble?
Financial bubbles can only be conclusively identified after they’ve popped. With 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.
Is the AI bubble going to burst?
The release of DeepSeek’s-R1 in January 2025 and doubts of AI’s revolutionary capabilities has sparked fears that the AI bubble may be about to burst. However, major tech companies aren’t slowing down, with plans to invest billions of dollars in AI infrastructure throughout 2025. It remains to be seen whether the so-called ‘AI bubble’ will actually burst or if continued investments will yield worthwhile returns.
