The question of whether artificial intelligence is racing toward a bubble has become one of the most persistent debates in tech. After dominating industry conversations throughout 2025, the topic has only grown louder as record investments, soaring valuations, and massive infrastructure deals continue to pile up.
The surge in AI spending has been fueled by unprecedented enthusiasm from investors and corporations alike. Multi-billion-dollar commitments to artificial intelligence platforms, cloud infrastructure, and advanced chips have pushed the market to historic highs, prompting some observers to warn that the pace may be unsustainable.
Others argue the opposite. They say the scale of investment is not excessive but necessary, especially as demand for computing power, data centers, and specialized processors continues to accelerate at a speed few industries have ever experienced.
To better understand where sentiment truly stands, CNBC gathered perspectives from 40 tech executives, analysts, and industry insiders, asking a simple but loaded question: Are we in an AI bubble, and if so, how worried should we be?
A boom powered by record spending
Much of today’s AI momentum can be traced to aggressive capital deployment by major players across the tech ecosystem. Companies such as OpenAI and Nvidia have been central to some of the largest AI-related deals on record, working closely with cloud providers to expand capacity and meet rising demand.
At the same time, hyperscalers including Amazon, Microsoft, and Google have continued to pour billions into data center construction and cloud expansion. These investments are designed to support the explosion of AI workloads, from large language models to enterprise automation and consumer applications.
According to analysts, this combination of rapid innovation and near-limitless funding has created an environment where valuations can climb faster than fundamentals, a classic warning sign often associated with speculative bubbles. A closer look at recent data center deals, detailed in CNBC’s reporting on the surge in AI-driven infrastructure spending, shows just how quickly commitments have escalated.
Debt, scale, and growing unease
While demand for AI services shows no signs of slowing, the financial structures behind many of these projects are raising eyebrows. The enormous levels of debt used to finance data center construction and hardware procurement have sparked concern among economists and investors.
CNBC previously reported on the growing debt loads tied to AI expansion, highlighting fears that even a modest slowdown in demand could leave companies overextended. In past market cycles, similar dynamics have preceded sharp corrections, particularly when expectations outpaced real-world returns.
Economic bubbles typically form when asset prices rise rapidly due to optimism or speculation, followed by a sudden pullback once confidence weakens. For some skeptics, the current AI landscape looks uncomfortably familiar.
Industry leaders push back on bubble fears
Not everyone agrees that artificial intelligence is headed for trouble. Nvidia CEO Jensen Huang publicly dismissed bubble concerns during a recent earnings call, stating that from his company’s vantage point, demand remains exceptionally strong.
“There’s been a lot of talk about an AI bubble,” Huang said. “From our perspective, we’re seeing something very different.”
Supporters of this view argue that unlike the dot-com era, today’s AI boom is underpinned by real usage, measurable productivity gains, and widespread adoption across industries. They point to enterprise demand, government contracts, and consumer tools as evidence that AI is already delivering tangible value.
Skeptics draw parallels to past manias
Others are less convinced. Michael Burry, the investor famously portrayed in The Big Short, has warned that the current enthusiasm surrounding AI mirrors the speculative excesses of the late 1990s. In a detailed essay published on his Substack and echoed in a post on X, Burry compared today’s spending frenzy to the dot-com bubble, cautioning that not every winner will survive once the market matures.
“Sometimes, we see bubbles,” Burry wrote. “Sometimes, there is something to do about it. Sometimes, the only winning move is not to play.”
His comments have resonated with investors who remember how quickly sentiment shifted during previous tech downturns.
Even AI insiders see signs of overexcitement
Interestingly, some of the most nuanced takes come from within the AI industry itself. OpenAI CEO Sam Altman acknowledged last year that while artificial intelligence may be the most transformative technology in decades, investor enthusiasm may have run ahead of reality.
During a dinner with reporters, Altman openly admitted that the market as a whole could be overexcited about AI, even as he reaffirmed his belief in its long-term impact. His remarks reflected a broader sentiment shared by several executives who believe AI’s future is enormous but uneven.
Measuring belief and concern
Rather than framing the issue as a simple yes or no question, CNBC evaluated responses along two dimensions. Participants were asked to assess how strongly they believe AI is currently in a bubble and how concerned they are about the implications.
Each response was scored on a scale from zero to ten for both belief and concern. Zero represented no belief that a bubble exists or no concern, while ten indicated strong conviction and high anxiety. The results showed a wide distribution, with many answers landing somewhere in the middle.
This spread highlights the complexity of the current moment. Some see inflated expectations and financial risk, others see necessary investment in foundational technology, and many see elements of both unfolding at the same time.
As artificial intelligence continues to reshape industries, the debate over whether today’s boom represents a healthy expansion or an overheated market remains unresolved. What is clear is that the conversation is far from over, and the stakes continue to rise alongside the investments fueling the AI revolution.
