AI has been the predominant force driving markets this year. How is the theme playing out in the U.S. small-cap market?

Mick Rasmussen: This market is as narrow as any we’ve witnessed, with AI serving as the clear, dominant driver of index returns. Within U.S. small caps, the companies most closely tied to the theme are the ones benefiting from the AI infrastructure buildout—semiconductor companies, firms manufacturing semiconductor production equipment, and providers of the hardware, networking components, and technologies that support data centers. Additionally, there is a long tail of companies tied to construction and energy infrastructure that are benefiting from AI-related demand. These companies have also experienced strong stock performance.

Kipling Weisel: The other side of the AI trade is comprised of companies that investors perceive as vulnerable to AI disruption. Software companies, payments firms and businesses whose value is tied primarily to intangible assets have sold off significantly. In our view, the market has been indiscriminate in assigning winners and losers within that group, effectively selling everything at once.

After the significant run-up in AI-related stocks over the past two years, how are you thinking about valuations today?

Ryan Snow: Growth has been very strong for some of these companies, but there are clearly areas where valuations have become disconnected from fundamentals. For a meaningful portion of the market, it’s difficult to justify valuations using traditional measures tied to revenue, earnings or cash-flow generation.

Can you provide examples of areas where AI-related enthusiasm appears excessive?

Ryan Snow: One of the clearest examples is quantum-computing companies. Quantum processors could ultimately accelerate the training of machine learning models, and recently the U.S. government announced plans to provide grants to select quantum computing firms and acquire equity stakes in some of them. That announcement further fueled enthusiasm across the group.

But if you step back and look at the underlying businesses, many have little to no commercialized product revenue today. Despite that, some command market capitalizations exceeding $20 billion. Without traditional revenue streams or operating fundamentals, it becomes nearly impossible to perform conventional fundamental analysis or determine what these businesses should be worth.

Mick Rasmussen: There’s also another category of companies currently experiencing a sharp acceleration in revenue tied to AI demand, but the durability of their growth is less certain. One example is an energy company positioned to help alleviate near-term power bottlenecks associated with the AI buildout. The stock more than doubled over the two-month period ending in May following strong operating results. Because data centers currently face limited access to new power capacity, the company is well positioned today. However, if the pace of AI infrastructure spending slows or if lower-cost energy sources become available to data centers through expanded transmission and grid connectivity, the company could see a meaningful decline in demand and revenue.

Another example is a construction services company whose stock also doubled over the two months ending in May. The business performs site preparation and concrete work for new data centers. While growth has been strong, this is ultimately a low-margin business with relatively low barriers to entry. Yet the stock is being valued as though it were a high-quality compounder capable of generating outsized earnings growth indefinitely. Some of these valuation moves are difficult to reconcile with the underlying business fundamentals.

Given AI’s long-term promise, how is Wasatch investing in the theme?

Kipling Weisel: We’re constructive on AI and are being proactive in identifying investment opportunities. From a stock-picking perspective, it’s an exciting environment because substantial capital is flowing into the space and there are real secular growth drivers emerging from AI adoption. That said, we want to be selective and focus on businesses with durable competitive advantages and long-term growth drivers that extend beyond the current AI cycle.

For example, we own several capital equipment companies tied to semiconductor manufacturing. They benefit from AI-driven semiconductor demand, but even before AI, they were already benefiting from increasing chip complexity. Their tools are mission-critical to customers, and many operate as monopolies or duopolies within highly specialized niches. We believe those characteristics make their growth more durable, even absent an elevated AI spending cycle.

Mick Rasmussen: We also own a company that helps utilities upgrade electrical grids, which is increasingly important as AI drives higher power consumption. We believe there is strong visibility into the durability of the company’s earnings growth. The stock has performed well for us, although it has not participated in the AI rally to the extent that some of the more speculative areas of the market have.

Do Wasatch portfolios have more or less exposure to AI-related companies than small-cap indices?

Mick Rasmussen: On an earnings-sensitivity basis, our exposure is roughly in line with the benchmark. In other words, if AI-related spending were to accelerate meaningfully from here, the earnings growth of AI-related holdings within our portfolios would likely be comparable to that of AI-related companies in the index.

However, because we avoid many of the more speculative names tied to the theme, we are underweight from a market beta perspective. As a result, during periods when AI enthusiasm drives strong index performance—as has often been the case recently—we have tended to underperform. Conversely, when concerns emerge around the AI buildout, such as negative headlines involving hyperscalers or large AI companies, our portfolios have generally outperformed.

We see considerable risk in many of the speculative stocks that have surged in recent months, and we are comfortable with our positioning even if it results in periods of relative underperformance during the most euphoric phases of the market.

Companies perceived to be at risk of AI disruption have sold off sharply in 2026. Is the selloff justified?

Kipling Weisel: In some cases, yes. As AI continues to improve, particularly in areas such as coding, barriers to entry are changing for certain software businesses and other companies whose value is tied to intellectual property or intangible assets.

At the same time, we believe the selloff has been overly broad. We see examples of software companies whose shares have declined despite the fact that their businesses are likely to benefit from AI rather than be disrupted by it.

How are you evaluating AI disruption risk within U.S. small-cap portfolios?

Kipling Weisel: We are not making broad, industry-level bets on software companies. Over the past two years, we’ve exited several positions where we believed AI disruption risk was elevated.

For the software companies and other businesses we continue to own, we believe their competitive advantages extend well beyond the underlying technology itself. Many possess proprietary data, network effects, scale advantages or deeply embedded customer relationships that we believe provide meaningful insulation from AI disruption.

Ryan Snow: One example is a large health savings account (HSA) administrator that we own. The company’s fundamentals have remained strong, yet the stock has declined. We believe the market has taken an overly simplistic view that because the company offers a software-based interface connecting customers and health-care providers, it could be displaced in an AI-native environment.

In our view, the company’s long-term value has very little to do with the interface itself. It manages HSA information for more than 10 million members and connects them with hundreds of network partners. We believe that network and ecosystem would be extremely difficult to replicate.

What has happened to the rest of the U.S. small-cap market—companies neither directly tied to AI nor perceived to be vulnerable to disruption?

Ryan Snow: A large number of companies fall into this category, both within our portfolios and across the broader index. Many of the companies we own have continued to compound earnings growth, yet their stock prices have largely stagnated. In some cases, valuations are as low as we’ve seen in their histories as public companies. Fundamentals remain strong, but in a market almost entirely focused on AI, that has mattered very little.

What are the similarities and differences between the current environment and the Dot-Com bubble?

Ryan Snow: The market enthusiasm surrounding AI certainly has echoes of the dot-com bubble. We are again seeing an environment where fundamentals appear less important and investor euphoria has driven sharp appreciation in the stocks of many lower-quality companies with limited earnings or measurable fundamentals.

The last period where low-quality stocks outperformed high-quality businesses to this extent was during the dot-com era. We continue to believe that, over the long term, earnings growth ultimately drives stock prices and that fundamentals will eventually reassert themselves.

That said, there are important differences between today and the dot-com period. AI may ultimately prove more transformational and far-reaching than prior technological innovations. In addition, many of the companies driving and enabling the AI boom—such as Amazon, Google and Meta—are highly profitable businesses with substantial cash flows. Many of the companies building out internet infrastructure during the dot-com era were not in a comparable financial position.

Risks and Disclosures

The views and opinions expressed herein are those of Wasatch Global Investors as of the date of publication, are subject to change without notice, and are provided for informational purposes only. Discussion of market, economic, industry, or company trends, portfolio positioning, and factors influencing performance reflects current views and should not be relied upon as investment advice. Investing involves risk, including the potential loss of principal. Past performance is no guarantee of future results, and there is no guarantee that the market forecasts discussed will be realized.

Statements regarding future market conditions, AI adoption, company prospects, earnings growth, disruption risk, valuation, portfolio positioning, or other future events are based on current expectations and assumptions and are subject to change. Actual results may differ materially from those expressed or implied, and there can be no assurance that any forecasts, expectations, or opinions will be realized.

Discussion of the long/short strategy is provided for informational purposes only. Long/short investing involves additional risks, including risks associated with short positions and the potential for increased volatility relative to traditional long-only strategies.