What If We're in an AI Bubble?
The “b” word is not one most investors like to talk about, but what began as a whisper has grown louder and more prominent in recent weeks. While stocks are up for the year, the word is starting to inject a note of uncertainty into the markets…and when uncertainty comes, volatility follows.
Many experts and market commentators have begun discussing the prospect of an “AI bubble” in the media. So, while the markets have performed well — with all three major indices recently setting new record highs1 — it’s time for us to examine the question, too. After all, there’s no better time to prepare for storms than when the sun is shining. In this piece, we’ll look at why the markets might be in an AI-driven bubble and what investors can do about it.
Before diving in, it’s important to make one thing clear: a bubble itself is not necessarily a problem. The concern is whether that bubble will burst. We are not predicting that will happen. The nature of bubbles makes them difficult, if not impossible, to size or time. Many commentators have predicted that an asset bubble would burst only to be proven wrong. But where prediction fails, preparation succeeds. Consider everything you’re about to read in that light: we are preparing for a possibility, not forecasting an inevitability.
What Exactly Is a Bubble?
A bubble occurs when the price of something rises unsustainably high above its actual value. A bubble can form across an entire economy, like the mid-2000s housing bubble. It can form within a particular market, like the late-1990s dot-com bubble. Even specific products can spark bubbles, such as the “beanie baby craze” of the mid-90s. (Perhaps the most famous example is the “tulip mania” bubble in the Netherlands during the 17th century.) In each case, unprecedented levels of hype — for easily financed homes, internet stocks, or even stuffed toys — drove demand far above supply and inflated prices far beyond true value.
Eventually, investors realized they were unlikely to receive returns high enough to justify the inflated prices. They rushed to sell. The sudden drop sparked panic, in which nearly everyone tried to exit simultaneously, often at bargain-bin prices. The bubble burst, and people lost money.
So why are some experts now speculating that we could be in a bubble today? And what does AI have to do with it? It’s a complex question — but we’ll distill it into something simple by the end.
Part 1: Concentration — What’s Really Driving Market Gains?
Let’s rewind to October 14, 2022. The S&P 500 closed at 3,583 that day.2 No one knew it then, but it marked the bottom of a 10-month bear market. Fast-forward to October 28 of this year: the S&P finished at 6,890, a record high.2 Between these two dates, the index rose over 90%, an impressive bull market by any measure.
But what has driven that bull market? This is where things get interesting.
When we talk about “the stock market,” we often imagine it moving up or down as a single entity. But that’s not how markets really work. At any given moment, some stocks rise while others fall. The overall direction reflects the balance between the two.
Sometimes, however, a handful of stocks move so dramatically that they drag the entire index with them. That’s exactly what has happened in this bull market. For several years now, the majority of market growth has come from a small group of companies: Alphabet (Google), Amazon, Apple, Meta (Facebook), Microsoft, Nvidia, and Tesla. Collectively known as the "Magnificent Seven," they represent roughly 35% of the S&P 500’s total value.3 Add the next three largest — Broadcom, Oracle, and Netflix — and that number jumps to 40%.3
Think about that: an index comprised of 500 companies, yet ten of them make up nearly half of its total worth.
On the surface, these companies may seem very different. But nearly all share one major commonality: they are investing billions of dollars into AI.
Part 2: Valuation — The Premium Investors Are Paying
Excitement about AI is the primary driver of the market’s performance. Other factors, like easing interest rates and lower inflation, play a role — but AI dominates. There are now over 1,300 AI startups valued at more than $100 million, and nearly 500 valued at $1 billion or more.4 Eight companies — the Mag 7 plus Broadcom — now exceed $1 trillion in market value.5
Investors are so eager to board the AI train that they’re willing to pay enormous premiums. Take NVIDIA, the largest of the Mag 7. Its share price trades at more than 50 times its earnings.6 In plain English, investors are paying $50 for every $1 of current earnings, expecting massive future profit growth.
In other words, valuations have soared far above revenue — a distinctive bubble characteristic.
So, we have a stock market being propelled by a small cluster of companies, all heavily focused on one technological theme. Understandably, many investors are asking: “So what? Doesn’t this just reflect how important AI is?” A fair question — which brings us to the next point.
Part 3: Expectation — The Profitability Challenge
The reason investors are willing to pay so much for AI-linked companies is the expectation that they will eventually deliver massive profits. But here’s the elephant in the room: the vast majority of AI companies are not profitable. In fact, many are nowhere close.
AI is incredibly expensive. The infrastructure alone costs billions to build and maintain. The tech sector is investing so heavily that total spending on AI actually outpaced consumer spending during the first half of the year.5
But eventually, revenue must matter.
Consider OpenAI — perhaps the world’s most recognizable AI brand. It makes significant revenue, yet nowhere near enough to cover its costs. Analysts estimate OpenAI recorded a net loss of $13 billion in Q3 alone.7 The company has stated it hopes to become profitable by 2030. Many other AI companies appear to be operating at similar levels of loss.
Now, to be fair, the Magnificent Seven are profitable — they’re mature companies, not startups. But even here, there’s reason for caution. Companies like Microsoft, Amazon, and NVIDIA generate revenue by supplying data centers, chips, and cloud capacity to the smaller AI firms. Many have also invested billions directly into AI startups. If those startups fail to become profitable and ultimately go under, major suppliers could face declining revenue and write-downs on their investments.
For AI to become a sustainably profitable industry, the technology must become essential in everyday life. Only then will enough people and businesses be willing to pay prices high enough to cover the staggering costs and justify current valuations.
But that’s not guaranteed. For example:
- MIT found that after spending $30–40 billion collectively on AI, 95% of large enterprises are “getting zero return.”8
- A Pew Research report found that 50% of Americans are more concerned than excited about increased AI adoption.9 Only 10% are more excited than concerned.
These numbers can shift over time, of course. But for now, they do not suggest that AI is on the cusp of becoming universally indispensable — a necessary condition for many companies’ valuations to make sense.
Which brings us to the final piece.
Part 4: Distillation — Why Some Believe We May Be in a Bubble
Let’s boil everything down to something simple.
Why might we be in an AI bubble?
Because:
- The market’s growth has been driven largely by a handful of companies.
- Those companies’ growth is largely driven by one technology.
- The hype surrounding that technology has pushed valuations far above actual revenue.
- Current data suggests that earning enough revenue to justify those valuations may prove challenging.
When the price of something rises unsustainably above what it is truly worth, you have the conditions for a bubble.
So, that leads to the logical next question: What should investors do?
Preparing for Any Scenario
One of the biggest mistakes investors can make is trying to time if or when a bubble might burst. There are several reasons:
- We might not be in a bubble at all. AI could mature, adoption could expand, and profits could accelerate.
- Even if there is a bubble, no one can predict when it will pop. It could be months or years. Waiting for a perfect exit point is unrealistic.
- AI might deflate rather than burst. Some companies may falter, others may rise, valuations may normalize, and the industry could ultimately settle into a stable, long-term growth driver.
We don’t know which scenario will unfold — no one does. But history offers a useful guide.
After the dot-com bubble burst, tech stocks crashed…but many other asset classes performed just fine.10 The crash also revealed which companies were truly strong and which were not. Many survivors went on to become today’s tech titans — including several members of the Magnificent Seven.
The lesson is clear:
By staying diversified, patient, and focused on the long term, investors remain prepared for any outcome — and well-positioned to benefit from each.
Final Thoughts
We hope you found this piece helpful as AI continues to dominate headlines and investor conversations. Readers interested in discussing these trends further or exploring how they fit into their long-term strategy are welcome to reach out to our team.
Whatever the future holds, staying grounded, diversified, and long-term focused remains the strategy that has consistently stood the test of time.
1 “All four U.S. stock market indexes just closed at record highs,” Morningstar, https://www.morningstar.com/news/marketwatch/2025102832/all-four-us-stock-market-indexes-just-closed-at-record-highs-heres-what-history-says-happens-next
2 “S&P 500 Historical Data,” Investing.com, https://www.investing.com/indices/us-spx-500-historical-data
3 “With the Magnificent Seven at 35% of the S&P 500 and the Ten Titans at 40%, are AI Growth Stocks Poised for a Sell-Off or Is There Still Room to Grow?” Yahoo Finance, https://finance.yahoo.com/news/magnificent-seven-35-p-500-114500263.html
4 “Are we in an AI bubble?” CNBC, https://www.cnbc.com/2025/10/21/are-we-in-an-ai-bubble.html
5 “AI spending is boosting the economy, but many businesses are in survival mode,” CNBC, https://www.cnbc.com/2025/10/21/are-we-in-an-ai-bubble.html
6 “NVIDIA P/E Ratio,” Public.com, https://public.com/stocks/nvda/pe-ratio
7 “Big Tech’s Soaring Profits Have an Ugly Underside: Open AI’s Losses,” The Wall Street Journal, https://www.wsj.com/tech/ai/big-techs-soaring-profits-have-an-ugly-underside-openais-losses-fe7e3184
8 “State of AI in Business 2025,” Massachusetts Institute of Technology, https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf
9 “How Americans View AI and Its Impact on People and Society,” Pew Research Center, https://www.pewresearch.org/science/2025/09/17/how-americans-view-ai-and-its-impact-on-people-and-society/
10 “Winners and Losers from the Dot Com Bubble Rate Hike Cycle,” YCharts, https://get.ycharts.com/resources/blog/winners-amp-losers-from-the-dot-com-bubble-rate-hike-cycle/
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