Is Artificial Intelligence in a Bubble? Earnings, Market Valuations and the Hidden Risk of Leverage

AI Market Commentary

Artificial intelligence has rapidly become one of the most powerful forces shaping financial markets. Billions of dollars are being invested in data centers, advanced semiconductors, cloud computing and AI software. Some of the world’s largest companies are reporting impressive growth, and investors are betting that artificial intelligence will fundamentally change the global economy.

But an important question remains: Are investors appropriately valuing the AI revolution, or has enthusiasm for the technology pushed parts of the stock market into bubble territory?

The answer may be more complicated than a simple yes or no. AI is already producing meaningful business results, but the scale of investment, expectations embedded in stock prices and growing use of borrowed money to purchase securities warrant careful attention.

1. The earnings are real. Are the valuations justified?

One of the strongest arguments against comparing today’s AI boom directly with the dot-com bubble of the late 1990s is that many of today’s leading technology companies have substantial revenue, established customer relationships and significant cash-generating businesses.

Consider several of the latest reported quarterly results, covering the quarter ended June 30, 2026:

• Microsoft: Revenue reached $90.0 billion, an increase of 18% year over year. Operating income rose 18% to $40.6 billion, reflecting continued strength in Microsoft’s cloud and AI businesses.
• Amazon: Net sales increased 20% to $200.6 billion. Amazon Web Services revenue grew 37% to $42.2 billion, its fastest growth in 18 quarters, demonstrating the strength of demand for cloud infrastructure.
• Alphabet, Google’s parent company: Revenue increased 24% to $119.8 billion. Google Cloud revenue surged 82% to $24.8 billion, driven in part by demand for enterprise AI solutions and infrastructure.

These results demonstrate that AI-related demand is not simply a story about investor enthusiasm. Businesses are purchasing computing capacity, cloud services and AI capabilities, and some of the industry’s largest participants are converting that demand into substantial revenue growth.

Sources: Microsoft’s Q4 FY2026 results, Amazon’s Q2 2026 results and Alphabet’s Q2 2026 results.

However, strong earnings alone do not establish that a stock is attractively valued. Investors must also consider how much they are paying for those earnings and how much future growth is already reflected in the share price.

A company can report excellent results and still experience a significant decline in its stock price if those results fall short of expectations, growth slows or investors become less willing to pay a premium valuation.

That distinction is central to evaluating today’s AI market.

2. The next phase: Turning massive AI investment into profits

The AI industry faces an increasingly important financial test. Companies have committed enormous sums to infrastructure, but the ultimate return on those investments remains uncertain.

Building data centers, purchasing advanced chips, securing electricity and developing AI models require substantial upfront capital. Those investments can create significant long-term value, but the financial returns must eventually justify the expense.

The challenge is that spending on AI infrastructure and revenue generated directly from AI are not necessarily growing at the same pace.

Some AI investment produces immediate revenue through cloud subscriptions, computing services and enterprise contracts. Other investments are intended to support products that may not generate meaningful profits for years.

Meanwhile, competition could place pressure on pricing, technology could advance faster than existing equipment depreciates, and customers may ultimately spend less than providers currently anticipate.

Investors should also distinguish between revenue generated by the broader AI ecosystem and revenue that can be attributed directly to AI products. A cloud provider may benefit from AI demand while continuing to generate much of its revenue from traditional computing services.

The question is not simply whether companies are investing in AI. It is whether the cash flows and profits ultimately generated will justify the capital being deployed.

3. What happens if expectations become too optimistic?

Financial bubbles do not necessarily develop around technologies that lack value. Some of the most significant market bubbles in history have involved technologies or industries that eventually transformed the economy.

The danger arises when investors extrapolate extraordinary growth too far into the future, underestimate risks or assume that current market leaders will capture a disproportionate share of the economic benefits.

The internet transformed commerce, communication and business productivity. Yet many internet-related stocks collapsed during the early 2000s because their valuations had exceeded what their businesses could reasonably support at the time.

The technology was transformative. The investment prices were not always justified.

AI could follow a similar pattern in some parts of the market without repeating the entire dot-com experience. Some companies may emerge as enormous long-term winners, while others struggle to recover the cost of their investments.

A market correction would not necessarily mean that AI had failed. It could simply mean that investors had paid too much, too early, for the expected benefits.

4. The overlooked warning sign: Margin debt and investor leverage

Earnings and valuations tell only part of the story. Another important indicator is the amount of money investors are borrowing to purchase securities.

According to data published by the Financial Industry Regulatory Authority (FINRA), U.S. margin debt reached approximately $1.454 trillion in August 2026, up approximately 37% from $1.060 trillion in August 2025. Margin debt also reached approximately $1.502 trillion in June 2026.

Source: FINRA margin statistics, as reported by YCharts.

Margin debt represents money borrowed by investors from brokerage firms, typically using securities in their accounts as collateral. Rather than paying the full purchase price of an investment with their own capital, investors use borrowed funds to increase their market exposure.

This is known as leverage.

Leverage can amplify returns when stock prices rise. However, it also magnifies losses when prices fall, and it can create additional selling pressure during market declines.

The scale and growth of margin borrowing deserve attention because they can influence how the market behaves when investor sentiment changes.

How leverage can amplify a market rally

Suppose an investor has $100,000 in cash and borrows another $100,000 to purchase $200,000 of stock.

If the investment increases by 20%, its value rises to $240,000. After repaying the $100,000 loan, the investor has $140,000 before interest and other costs. That represents a 40% gain on the original $100,000 of equity, rather than the 20% gain that would have resulted without borrowing.

This mechanism can increase purchasing power and contribute to demand for stocks during a rising market.

However, the same mechanism works in reverse.

If the $200,000 portfolio declines by 20%, its value falls to $160,000. After subtracting the outstanding $100,000 loan, the investor has only $60,000 in equity—a 40% loss on the original capital.

The investor’s underlying securities have declined by 20%, but the investor’s equity has declined by 40%.

Interest expenses can make the outcome worse.

What happens when markets fall?

The more consequential risk emerges when falling prices reduce the equity supporting borrowed investments.

Brokerage firms impose maintenance-margin requirements, and they can impose stricter requirements of their own. When an account no longer meets the applicable requirements, the investor may need to deposit additional cash or securities.

If the investor cannot meet the requirement, the brokerage firm may liquidate securities to protect its loan.

When many leveraged investors face these circumstances simultaneously, a potentially self-reinforcing cycle can develop:

1. Stock prices decline.
2. The value of collateral supporting margin loans falls.
3. Investors face margin calls or tighter borrowing limits.
4. Some investors must sell securities to raise cash or reduce their debt.
5. Additional selling puts further downward pressure on prices.

This process can accelerate a correction beyond what would otherwise be expected from a change in corporate earnings or economic conditions alone.

It is especially concerning when leverage is concentrated in popular, highly valued or volatile investments.

FINRA explains the risks of margin investing in its investor guidance, including the possibility that brokerage firms may sell securities in an account to satisfy margin requirements, potentially without advance notice.

Source: FINRA — Margin Debt at Record Levels: Know the Risks.

5. FINRA’s role: Monitoring margin activity, not setting stock prices

FINRA is the Financial Industry Regulatory Authority, a self-regulatory organization that oversees U.S. broker-dealers and enforces rules governing their activities. It also publishes monthly margin statistics that allow investors to monitor borrowing within the securities industry.

Its role in this discussion is important, but it is worth making a distinction.

FINRA does not determine where stock prices should trade, nor does its margin-debt data prove that the market is in a bubble. Rather, the data provides a useful measure of investor borrowing and leverage.

Margin debt can increase for several reasons, including rising stock prices, greater trading activity, increased demand for leveraged strategies and changing collateral requirements. The data alone does not reveal exactly who is borrowing, which securities they are buying or whether those positions are speculative.

Nevertheless, a rapid increase in margin debt can be an important warning sign when it coincides with elevated valuations, concentrated market leadership and unusually optimistic expectations.

The relationship between leverage and stock prices is also more complicated than it may initially appear.

Rising prices can encourage investors to borrow more, creating additional buying power. At the same time, rising prices increase the value of securities used as collateral, which can permit further borrowing. When conditions reverse, that process can work in the opposite direction.

Margin debt is therefore both a potential contributor to market movements and a reflection of investor behavior. It should be interpreted alongside valuations, earnings, market concentration, interest rates and other measures of financial risk.

High margin debt does not reliably identify the precise timing of a market peak. But it can help investors assess how vulnerable markets might be if a correction begins.

6. Is today’s AI boom comparable to the dot-com bubble?

There are meaningful similarities, but there are also important differences.

Similarities include:

• High expectations for a transformative technology.
• Investors placing substantial premiums on companies expected to benefit from future growth.
• Heavy investment in infrastructure intended to support that growth.
• The possibility that competition and capital costs could prevent some businesses from earning their anticipated returns.
• Elevated borrowing that could amplify market movements if sentiment changes.

Important differences include:

• Many of today’s leading AI companies already have large, profitable businesses and established revenue streams.
• The largest technology companies possess substantial financial resources to fund investment internally.
• AI is already being integrated into existing products and services, rather than depending entirely on an unproven future business model.
• The economic benefits of AI may extend across numerous industries, not just companies directly involved in developing the technology.

These differences make a repeat of the dot-com collapse far from inevitable.

However, the fact that the underlying technology is real does not eliminate the risk of excessive valuations. Investors can correctly identify a major technological shift and still overestimate how quickly it will produce profits or how much of those profits will accrue to particular companies.

The more useful question is not whether AI is a bubble in its entirety. It is whether the prices investors are paying for individual businesses adequately reflect their growth prospects, capital requirements and risks.

7. What should investors watch next?

Several developments will help determine whether the AI investment cycle can sustain its momentum.

Corporate earnings and guidance. Revenue growth is important, but investors should also monitor operating margins, free cash flow and management’s expectations for future demand.

Capital expenditures. Continued increases in spending on data centers, chips and computing infrastructure may be justified if they produce attractive long-term returns. The risk increases if spending continues to accelerate without corresponding improvements in revenue and cash flow.

AI monetization. Companies must demonstrate that AI products can generate durable economic value. User adoption and impressive demonstrations are encouraging, but they are not substitutes for sustainable profits.

Valuations. Even strong companies can be vulnerable when their stock prices assume years of exceptional growth with little room for disappointment.

Margin debt and other leverage indicators. FINRA’s monthly data can help identify periods when borrowing is expanding rapidly. Investors should also consider the use of leveraged exchange-traded funds and other strategies that can amplify market movements.

Market concentration. When a relatively small number of large companies account for a substantial portion of market performance, disappointing results from those companies can have an outsized effect on major indexes and diversified portfolios.

No single indicator can reliably predict when a market correction will begin. Taken together, however, these measures can provide a more complete picture of the risks facing investors.

Conclusion: A real revolution can still produce an investment bubble

Artificial intelligence may ultimately prove to be one of the most consequential technologies of this generation. The latest earnings from Microsoft, Amazon and Alphabet demonstrate that substantial demand already exists, and the opportunity for further innovation remains significant.

At the same time, the amount of capital being committed to AI infrastructure, the expectations embedded in technology stock valuations and the rapid growth in margin debt warrant caution.

The risk is not necessarily that AI will fail. It is that investors may become too optimistic about how quickly its benefits will materialize, how much profit companies will ultimately earn and what those future profits are worth today.

The growth in margin debt adds another dimension to the analysis. When investors increasingly rely on borrowed money, rising markets can become more powerful, but falling markets can become more disruptive as investors are forced to reduce exposure.

For long-term investors, the appropriate response is not necessarily to abandon technology stocks or attempt to predict the exact top of the market. It is to remain disciplined about valuation, diversification, risk tolerance and the role individual investments play within a broader financial plan.

At HWC Financial, we believe that distinguishing between a promising technology and an appropriately priced investment is essential to long-term financial decision-making. AI may create extraordinary opportunities, but sound investment decisions still require an understanding of both the potential rewards and the risks that accompany them.

This material is for informational and educational purposes only and should not be construed as individualized investment, tax or legal advice. All investing involves risk, including the potential loss of principal. Past performance does not guarantee future results. Investors should consider their individual circumstances and consult their financial professional before making investment decisions.