KOHb - Getty Images

Feature

An AI bubble burst? Early warning signs and how to prepare

AI is nearing a reset, shifting focus from hype to measurable value. CIOs must reassess investments, prioritize ROI and guide their organizations toward a sustainable AI strategy.

Julie Hanson
By
Published: 10 Dec 2025

The impending end of an AI bubble could signal a fresh start for some AI technology companies.

AI technology has captured the attention of consumers and investors alike due to its rapid innovation and potential for profit, resulting in a surge of AI tools flooding the market. But, despite a wave of innovation, few initiatives made it past the development phase. This was because they were built on fragmented tools and were too disconnected from business goals, according to Juan Jose Lopez Murphy, head of data science at Globant.

The situation made some investors uncomfortable.

"The frustration we experience, which some call deflation, is fatigue from too many models and too little strategy," Lopez Murphy said. "Instead of investors and executives pulling back completely, we are starting to see a shift of focus from volume to value."

Investors are now looking for projects that deliver measurable outcomes that are sustainable across teams and systems, resulting in a more disciplined market, he said.

The big difference between what's happening now and previous investment bubbles is that AI technology is real in terms of actual value that it brings, said Matt Hasan, PhD and CEO of aiRESULTS Inc. As an AI strategist and an economist, Hasan said he looks at the market through two lenses -- the technology and the money chasing it.

Unrealistic expectations have led to overinvestment in generative AI, and according to an MIT report, 95% of organizations are experiencing zero return. Investment is currently outpacing value.

"The risk comes from how fast investors have piled in," Hasan said. "Money is flowing into data centers, chips and startups a lot faster than real adoption can keep up. The hype is moving ahead of actual business value."

Three critical factors differentiate this bubble from others, according to Jonathan Bittner, CEO of Dimensional Analytics. Those ways include the following:

  • Circular financing. Major players in the AI industry are investing in each other, creating the illusion of economic activity. Bittner cites the example of Nvidia investing $100 billion in OpenAI, which buys Nvidia chips, while Oracle buys Nvidia chips for OpenAI centers.
  • Profitability timeline. Many startups lose money initially, but they have a plan for achieving profitability. OpenAI is losing $12 billion per quarter and expects $44 billion more in losses through 2029. Bittner said. "They're spending $2.25 to make $1. No dot-com company survived with that kind of burn rate."
  • National security framing. AI companies are embedding themselves in defense contracts, which could potentially lead to a bailout request, Bittner said.

Early indicators of a bubble deflation

Forrester predicted an AI market correction in 2026 as organizations grapple with the ever-widening gap between inflated vendor promises and actual value delivered. With fewer than one-third of decision-makers able to tie the value of AI to their organization's financial growth, CEOs will rely on CFOs to approve AI investments based on ROI in 2026, according to the report.

"In 2026, the AI hype period ends as the pressure to deliver real, measurable results from secure AI initiative intensifies," Sharyn Leaver, chief research officer at Forrester, said in a report. "As the era of volatility continues, tech and security leaders will be called upon to recalibrate investments under tighter financial scrutiny and governance while navigating increasingly complex geopolitical and economic risks."

Hasan has seen some deflation as venture funding cools off, valuations level out and companies realize that promised gains are taking longer to show up.

"That's not collapse -- that's a pause to catch our breath," Hasan said.

More red flags are visible if you look deeper, Bittner said, including the following:

  • Economic dependency. Without AI investment, economists suggest we may already be in a recession, Bittner said. Manufacturing has contracted for seven straight months.
  • Infrastructure bottlenecks. The country is projected to face a 35 GW electricity shortfall by 2028, Bittner said. Data centers need 57 GW but only 21 GW will be available. "Most new data centers in the internet hub of Ashburn, Va., are being powered by natural gas generators because the electricity supply doesn't even have a date to catch up," Bittner said. "This isn't a temporary bottleneck. It's physics."
  • Public sentiment shifts. Consumer confidence has reached its lowest point since 1997, and AI is not showing the promised ROI returns. "Public perception matters a lot," Hasan said. "When excitement outpaces results, people start to question whether AI is really improving their work or their lives. Once that doubt creeps in, the emotional fuel behind the boom starts to fade."

What a burst could mean for businesses

A bubble burst won't kill AI, just the unrealistic expectations surrounding it, Hasan said. He believes that companies focused on solving real problems will emerge stronger.

Bittner shares Hasan's optimistic outlook. He said the burst itself would hit organizations in three waves, including the following:

  • Wave 1. There will be layoffs at AI companies, including many AI startups. "We're talking tens of thousands of highly paid engineers suddenly on the market," Bittner said.
  • Wave 2. Bittner said 56% of companies are missing AI cost projections by 11% to 25% and one in four are missing by more than 50%. When CFOs demand results, entire AI divisions will get cut, Bittner said.
  • Wave 3. Real innovation accelerates. True builders will survive the crash and start solving actual problems with appropriate technology, Bittner said. He points to companies such as Google, Amazon, and PayPal, which strengthened after the dot-com crash because they had solid business models. He believes the same will happen with AI.

"The AI bubble burst could mark the beginning of a healthier, more focused innovation cycle for AI. Enterprises may start consolidating budgets for projects or slow down hypothetical projects," Lopez Murphy said. "This period doesn't mean that innovation is stopping altogether but rather showing maturity in prioritizing projects."

He believes that emphasis will shift to building frameworks that will last in the long term.

How CIOs can adapt and protect their organization

As the threat of an AI bubble burst looms closer, industry leaders will have to see through the hype and focus on AI technology that solves tangible business problems. Hasan advises leaders to stay grounded, tie AI projects to clear results and track costs.

"If businesses keep their heads and focus on real impact, a correction won't be a disaster. It'll be a reset, and a healthy one," he said.

Bittner added his own recommendations, including the following:

  • Demand measurable ROI up front. If an AI vendor can't show you hours saved, errors prevented or revenue generated within 90 days, walk away.
  • Favor narrow, focused solutions over general AI. A tool that does one thing exceptionally well beats a general-purpose tool that does everything poorly, he said.
  • Don't assume you need state-of-the-art models. This is where most organizations waste money, Bittner said. Many production AI applications work fine with smaller, open source models that can run at the edge.
  • Look at who's profitable. An AI company losing billions quarterly is not building sustainable technology. Partner with companies that have actual business models, he said.
  • Audit your AI spending. Most organizations find that 80% of AI spending is on experiments that never ship. Invest in the 20% that works.

For Hasan and Bittner a bubble burst would signal a new, more efficient approach to AI technology investments.

"The bubble pop won't be a disaster. It will be a reset. And America's hard-working, smart people will use that reset to revolutionize the economy with AI -- the right way," Bittner said. "It will always be about the people. Not the algorithms."

Julie Hanson is a freelance writer who has reported on local news across Massachusetts and New Hampshire.

Dig Deeper on CIO strategy