NOTE: This blog post is based on a chapter in my book, Beyond Wall Street: 7 Principles of Risk Management and Wealth Preservation. Written in 2023, this chapter has been slightly updated and published here to reflect the current market.
Over the course of my career, I’ve witnessed four major economic bubbles rise, grow, and then burst. I’ve learned important lessons from them—lessons I actively apply in my day-to-day interactions with clients and in my personal investing strategy.
Recognizing bubbles is a crucial part of risk management. The better you are at spotting a bubble bursting, the more likely you are to take profits off the table, protecting your finances and overall investing capacity.
BUBBLES IN NATURE
Markets move in cycles—periods of growth followed by contraction. Financial bubbles are a part of this cycle, much like hurricanes are part of the natural ecosystem and climate of Florida.
Bubbles are characterized as abnormal activity within a particular sector or asset class that disrupts the market’s typical or natural rhythm. This disruption often results in rapid, unsustainable price increases—when the bubble bursts, it can lead to a sharp, significant decline in the affected asset’s value. This sudden downturn contrasts with the stability that typically characterizes a healthy and well-functioning market environment.
Preeminent American economist Hyman Minsky theorized that “stability leads to instability, the more stable things become and the longer things are stable, the more unstable they will be when the crisis hits.” In other words, a strong, stable economy encourages riskier behavior and unrestrained monetary policy, making borrowing easier, which then can worsen crises if and when they occur.
Good risk management can’t eliminate market downturns, but it can help investors navigate them. You can control your own exposure—but not the crowd’s behavior. When collective euphoria gives way to panic, even the soundest portfolio can take a hit.
And that’s why spotting bubbles matters.
THE STATE OF TECH
To start, the tech sector is bursting with good ideas—great ideas, even—that never really get off the ground. For every Apple, there are about a thousand rotten ones. Even if they start to succeed, the likelihood of becoming the next Microsoft, Google, or Amazon is becoming increasingly complex as the field grows more crowded.
Truly novel ideas are rare—but when they emerge, excitement can quickly spiral into mania. The enthusiasm can grow out of control. Many economists now warn that we’re in the middle of an AI bubble reminiscent of the late-1990s dot-com frenzy.
After years of pandemic-fueled growth, tech stalled in 2022 as higher interest rates slowed the economy. Giants like Alphabet, Meta, Microsoft, and Amazon laid off thousands as revenues and stock prices fell. Then AI reignited the industry. Microsoft’s multibillion-dollar investment in OpenAI—creator of ChatGPT—triggered a race. Every major platform, from Google to LinkedIn, rushed to roll out AI tools. Startups followed in droves, and investors flooded the sector with cash.
On the surface, the NASDAQ looks just shy of its all-time high. But if you dig deeper, valuations are already well above dot-com levels.
THE DEEPER ISSUE
In the last decade, many renowned tech stocks have been reclassified into other categories. It’s not entirely clear why, but Meta (Facebook) and Alphabet (Google) were reclassified in 2018 from their original Information Technology classification to Communication Services. In March of 2023, PayPal, Visa, MasterCard, and Fiserv were moved over to the Financial sector. Amazon, Tesla, and Netflix have been forced into the Consumer Discretionary and Communication column, respectively. If the above companies had not been reclassified, the official IT sector weight, estimated in 2023, would be 37%.
In fact, if you add all the information technology companies back to their original place, the sector weight surpasses the dot-com bubble peak by leaps and bounds. Currently, we have the most significant tech consolidation in the history of the S&P 500, even without putting major tech companies back where they were initially.
With AI dominating headlines, valuations have soared well past dot-com-era levels, suggesting we may be nearing the peak of a new tech bubble. Since the tech sector accounts for a massive share of the S&P 500 (and other indexes), and power is concentrated among a few major players, the entire industry is in a highly precarious position.
2025 REFLECTIONS
Today, as more and more AI companies appear, “hundreds of billions of dollars get channeled into technology whose ability to generate sustained profits is still largely untested,” Financial Post reported.1 Meanwhile, people rush to invest, feeling the pressure. “[F]ear of missing out has fanned stunning valuation gains, prompting speculation that Nvidia Corp. alone might reach a market capitalization of $5 trillion.”2
Other consumer-forward tech—like social media companies—generates income from ads and data harvesting and has relatively low overhead due to cheap access to cloud storage and little need for physical real estate. Comparatively, AI is costly to develop and run, requires a massive amount of energy, and lacks easy income channels to push it mainstream in a stable way or to make it less of a financial burden on small start-ups.
Furthermore, enterprise-level investment remains limited. Many companies interested in contracting with an AI provider to deliver AI services to their clients ultimately decide not to participate, primarily due to the significant risks of data leaks and high costs.
The combination of high overhead costs, limited income, and difficulty attracting corporate investors makes AI a risky investment. Because AI technology has enormous revolutionary potential, it garners tremendous investor interest but creates a highly speculative environment. AI is still an immature, experimental asset that requires careful consideration rather than reckless enthusiasm.
Yet reckless enthusiasm persists, even with the echoes of the dot-com bubble still ringing in many ears.
For example, according to the Financial Times, at least 10 AI startups—all without profit—have reached valuations of over $1 trillion in the past year.3 Though many in the industry are sounding the alarm, feeling uneasy about the parallels to past bubbles, the AI industry seems unfazed. CNN reports that “the AI industry’s response has been to shrug and watch their valuations tick higher and higher…and even if there is a bubble, proponents say, the dot-com bubble gave us companies like Amazon, and the internet became, well, the internet.”4
Meta’s latest guidance from its Q2 2025 earnings call in late July projects capital expenditures of $66-72 billion for 2025, mainly driven by AI infrastructure. This is a significant rise from earlier estimates. Additionally, Microsoft’s fiscal year-end report for June 30, 2025, shows capital expenditures of over $80 billion, mostly spent on AI-enabled data centers and cloud infrastructure.
Costs are only set to rise. McKinsey found that “by 2030, data centers are projected to require $6.7 trillion worldwide to keep pace with the demand for compute power. Data centers equipped to handle AI processing loads are projected to require $5.2 trillion in capital expenditures, while those powering traditional IT applications are projected to require $1.5 trillion in capital expenditures…Overall, that’s nearly $7 trillion in capital outlays needed by 2030—a staggering number by any measure.”5
Even OpenAI, which is arguably the most famous and successful AI company to date, has yet to turn a profit. With an estimated 15.5 million paying subscribers and an estimated $11.6 billion in revenue in 2025, it is burning a total of $26 billion to keep the lights on, resulting in a loss of $14.4 billion.6
This, taken with the already heavy consolidation of tech on the S&P 500 and other indexes, paints a truly troubling picture. Can the market sustain another tech bubble? And if it bursts, what happens next?
INVESTOR TAKEAWAYS
AI’s potential is vast, but investing directly in it is risky. Investors seeking exposure to the boom might look to supporting industries—especially energy. The AI revolution runs on electricity, and demand for power generation, storage, and infrastructure is set to rise sharply. Unlike AI startups, energy producers serve a universal, time-tested need.
However, it’s important to remember that even financial bubbles have their positives. The dot-com bubble of 2001 caused a severe crash, but the companies that endured went on to achieve incredible success. The internet boom established the infrastructure that enabled its growth, resulting in the emergence of new industries such as Amazon. Those companies developed innovative, impactful technologies that were once hard to imagine prior to the bubble, such as mobile phones, online shopping, payments, and entertainment, which are now commonplace. Major technological breakthroughs—such as cryptocurrency and, yes, even AI—have come from innovations that now feel normal to us.
Ultimately, the key takeaway for investors is that even if the AI bubble bursts, history consistently shows that the investments that fuel it often lead to significant economic growth and groundbreaking innovation, which eventually revive the market and nourish the natural market cycle.
SOURCES:
- As AI-Bubble fears spread, a $35 billion fund manager positions for inflows. (2025, October 12). Financial Post. https://financialpost.com/pmn/business-pmn/as-ai-bubble-fears-spread-a-35-billion-fund-manager-positions-for-inflows
- Ibid.
- Conboye, J., & Hammond, G. (2025, October 16). ‘Of course it’s a bubble’: AI start-up valuations soar in investor frenzy. Financial Times. https://www.ft.com/content/59baba74-c039-4fa7-9d63-b14f8b2bb9e2
4. Morrow, A. (2025, October 18). Why this analyst says the AI bubble is 17 times bigger than the dot-com bust. CNN. https://www.cnn.com/2025/10/18/business/ai-bubble-analyst-nightcap - Noffsinger, J., Patel, M., & Sachdeva, P. (2025, April 28). The cost of compute: A $7 trillion race to scale data centers. McKinsey & Company. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-cost-of-compute-a-7-trillion-dollar-race-to-resultingscale-data-centers
- Isaac, M., & Griffith, E. (2024, September 28). OpenAI is growing fast and burning through piles of money. The New York Times. https://www.nytimes.com/2024/09/27/technology/openai-chatgpt-investors-funding.html?ref=wheresyoured.at
