2026 U.S. Equity Outlook
Second Quarter
Key Takeaways
Growth Stocks: Uncertainty has rarely been higher — monetary policy, the global geopolitical landscape and trade policies are all in flux. To top it off, the ultimate economic impacts of artificial intelligence (AI) are uncertain.
Value Stocks: From software to retail, investors grapple with how quickly AI threats will materialize and where they may be overstated.
Growth Stocks
Investing in a Time of Heightened Uncertainty
As 2026 unfolds, we’re closely monitoring several key economic and market risks. While we’re emphatically fundamental, bottom-up investors, we still believe it’s important to understand the environment in which our companies operate. We believe these volatile economic conditions present an excellent opportunity to demonstrate the value of our long-term focus on high-quality, growing companies.
We see numerous tensions in the markets, indicating that this will likely be a significant and volatile year for financial markets.
The fog of war. Beyond the human tragedy, a widening conflict in the Middle East poses risks to global energy markets. A prolonged conflict, disruptions to global shipping and sustained higher energy prices could lead to higher inflation, complicating the outlook for growth and interest rates.
Uncertain U.S. monetary policy. Relatively weak job conditions argue for lower rates, while above-target inflation suggests little or no further cuts. President Donald Trump’s attacks on the Federal Reserve's (Fed’s) independence and the nomination of a new Fed chair introduce additional uncertainty into the interest rate outlook.
U.S. fiscal policy creates additional hurdles. Tariffs, trade wars and a shock to labor supply from immigration policy all have potentially inflationary effects. High and rising national debt implies a greater government interest expense burden, pushing up rates and crowding out private investment.
Market concentration and fundamentals exacerbate risks. Big U.S. stock indexes, such as the S&P 500® Index and Russell 1000® Growth Index, are remarkably concentrated in the 10 largest companies. Valuations of large-cap stock indexes are also high compared to historical averages. Growth stocks are similarly expensive relative to value stocks.
The implication is that heavily relying on a handful of companies increases the risk to the entire market of poor results or forecasts from one or a few firms. And if growth expectations turn out to be unrealistic, corrections could be sharp.The falling dollar suggests U.S. assets are less appealing than in the past. First, a weaker U.S. dollar means higher prices for imports (higher inflation). But take a step back and realize that the weaker the dollar, the lower the returns on dollar-denominated assets, such as U.S. stocks and bonds, for foreign investors.
Essentially, since the 2008 Great Financial Crisis, U.S. assets have enjoyed a tailwind from a strengthening dollar. Overseas investors received the double benefit of currency gains alongside rising U.S. asset prices.
This tide may finally be going out, as the greenback has fallen about 10% since January 2025. One implication for financial markets and the economy is that less foreign demand for U.S. Treasuries means higher rates here at home, all else equal.
These economic and policy uncertainties go a long way to explaining why we expect market volatility to continue in 2026. However, one source of uncertainty warrants a more detailed discussion.
Is AI a Bubble or a Breakthrough for Markets in 2026?
On the one hand, investors appear to be saying that the big corporate spenders on AI are unlikely to generate an economic return sufficient to justify massive capital spending. This is the argument of those who see an “AI bubble.”
On the other hand, the stocks of entire industries — including software, many financial services segments, and even real estate property managers — are being hammered on the premise that AI threatens their very existence.
So, which is it? Is AI massively overhyped, or is it an economic superpower about to make entire segments of the economy obsolete?
We believe the truth probably lies somewhere in the middle.
In our conversations with companies, we observe clear signs of progress in implementing AI in software coding and digital advertising. However, the broader promise of productivity from “agentic AI” has so far remained unfulfilled.
Physical AI provides another way for this technology to boost productivity. Examples include autonomous vehicles or robots, which can “reason” and interact with their physical surroundings. However, we’re still in the early stages of development and deployment.
And while there are signs of frothiness in speculative capital chasing early-stage AI startups, the most profitable and largest cash-generating companies in the world are fueling much of the AI investment. These big spenders include Alphabet, Amazon.com, Meta Platforms and Microsoft. So far, Alphabet and Meta have reported some of the clearest signs of AI contributing meaningfully to their bottom lines.
What we’re looking for are broader signs of success and AI adoption resulting from this spending on model training and data centers/cloud computing. Such signs would help sustain investment in AI and ease investor worries about overspending. Identifying and validating these successes is a top priority for all our investment teams.
Finding Opportunities During AI-Driven Market Dislocations
In our view, the dislocations and market upheaval surrounding AI present a tremendous opportunity to add value through individual security selection. That’s because the AI-related sell-off across entire industries overlooks the differing fundamentals of the underlying companies.
For example, we’re seeing high-quality software companies with accelerating growth selling off right alongside those with slowing growth. We see these fast-growing companies as potential opportunities at what we think are attractive valuations, given our view of their likely long-term success.
What’s more, opportunities aren’t limited to AI and its related fields. For instance, we continue to see significant potential in companies that benefit from long-term, secular trends such as space commercialization, high-quality industrials, cybersecurity and drug discovery.
Finally, uncertainty around interest rates and financing costs underscores the attractiveness of companies that can finance growth from their own cash flows. This explains, in part, why we’re so focused on the sustainability and trajectory of corporate profitability, viewed in the context of a company’s stage of development.
Value Stocks
How to Find Value Amid AI Disruption
Dario Amodei, the co-founder of AI company Anthropic, wrote an essay in October 2024 that struck an upbeat tone about this emerging technology.1
Titled “Machines of Loving Grace,” his essay acknowledges AI’s risks but mostly extols how its transformative power could be harnessed to improve the world.
In January 2026, Amodei published another essay with a decidedly different theme.2 “The Adolescence of Technology” is a warning to a world that he seems to think is sleepwalking into a “serious civilizational challenge” as AI’s capabilities rapidly advance and potentially change how, or if, humans work.
“Humanity needs to wake up, and this essay is an attempt — possibly a futile one, but it’s worth trying — to jolt people awake,” Amodei wrote.
How AI May Reshape Sector Expectations in 2026
Amodei’s latest essay seems to have sparked some serious thinking among investors about how AI could fundamentally alter the businesses they invest in.
One by one this year, stocks of entire industries have tumbled as new applications and advances in AI appear to threaten broad business models. Software stocks fell sharply as investors considered whether AI could quickly and cheaply replicate the functions of software-as-a-service (SaaS) firms like Salesforce.
Others followed. Insurance brokers sold off due to fears that businesses could use an AI model to analyze their risks and pair them with appropriate insurance policies, eliminating the need for a middleman. Real estate brokers fell on similar logic.
Investors are left facing a confounding landscape. How real are these threats? How soon could they materialize? What if these tools actually improve the businesses they’re supposed to supplant?
As we examine the situation, we find that the reality is more complex than these stock movements indicate. For instance, the doomsday predictions about software companies aren’t so straightforward.
Businesses storing their data on on-premises mainframes rather than in the cloud will probably face significant challenges, or even find it impossible, to substitute their existing software with an AI application.
Companies that handle particularly sensitive data — hospitals, law firms, banks and so on — would be reluctant to transfer their data to an AI-compatible cloud, not to mention the regulatory hurdles they might encounter when implementing AI.
Wealth managers have been in the AI crosshairs recently, too. Couldn’t AI advise people how to manage their money, taxes and estates?
Perhaps, but roboadvisors have existed for years. Consumers tend to value human interactions. They want someone to pick up the phone, answer their questions, guide them and provide reassurance. They also want, if necessary, someone to blame.
How AI Tools May Change How Consumers Discover Products
Even sectors and businesses that one might assume are relatively safe from AI might not be, depending on how certain variables unfold.
Take online retail, for example. Some AI firms are developing a shopping agent, an AI application that will scour the web and fetch items for purchase that match a consumer’s prompts.
Let’s say you’re a long-distance runner; you could get on an AI shopping agent and place the following prompt: “Find me a pair of Bluetooth-enabled, sweat-resistant earbuds that are gray or black — certainly not red — and are also on sale for less than $60 and can be delivered to me today by 5 p.m.” Rather than rifling through several websites yourself to find a product that meets all your specific needs, the AI agent does it for you in mere seconds.
In such a scenario, consumer convenience could pose trouble for seemingly entrenched online retail giants like Walmart or Amazon. Those companies would be cut off from consumers and the valuable data they currently collect from them for advertising purposes.
Morgan Stanley reports that just 1% of current e-commerce transactions are handled by AI shopping agents. It projects this will increase significantly to 20% by 2030.
Value Investing in the AI Era
As value investors, we continue to favor stocks of companies we deem as high-quality with durable business models and relatively narrow outcomes, even amid current AI disruptions.
We continue to like medical device companies because AI can’t make a hip replacement. Hospitals could benefit from AI by improving billing efficiency or assisting physicians in evaluating patient scans. AI could help pharmaceutical companies better identify which drugs under development have promise and which ones don’t.
We like sectors that, for now, still meet our criteria. We think consumer staples, for the most part, are relatively insulated from AI. Packaged foods and food distributors don’t appear to face direct AI headwinds while they deal with other challenges, like weight-loss drugs. But this thinking could change if AI results in higher unemployment and fewer people go to restaurants or cut back on overall spending.
Similarly, banks broadly have neutral AI exposure today, but credit risk would go up if job losses increased.
How Investors Can Adapt as AI Reshapes Business Models
New technologies have always posed challenges to investors. Some predictions about how the internet would affect companies came true almost immediately, while others never materialized. Most took years to play out.
AI seems similar. Markets often see it as pure disruption, but its earliest effects might be more incremental — appearing first as cost savings, increased efficiency, and better execution rather than a complete overhaul of business models. Over time, these improvements can significantly boost margins, productivity, and returns on capital, especially for established firms with scale.
AI will likely follow a similar path, though the changes could occur more quickly. Still, it doesn’t mean AI’s progress will advance steadily or evenly. A January 2026 study found that despite the impressive capabilities of large language models, the technology still showed a propensity to fail at reasoning, even in simple cases.3
In either case, it will mean investors should be vigilant, ready to adapt to changing circumstances, and also be prepared to examine and question the prevailing wisdom.
¹Dario Amodei, “Machines of Loving Grace,” available at https://darioamodei.com/essay/machines-of-loving-grace.
²Dario Amodei, “The Adolescence of Technology,” available at https://www.darioamodei.com/essay/the-adolescence-of-technology.
³Peiyang Song, Pengrui Han, and Noah Goodman, “Large Language Model Reasoning Failures,” Transactions on Machine Learning Research, January 2026.
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