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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →William Blair’s August 2026 view is that AI-related technology and infrastructure were losing market momentum while more industries and countries began contributing to returns. The firm calls this a stockpickers’ market: a shift in leadership beneath resilient indexes, not proof that AI is finished or that the market has entered a downturn.
What William Blair means by a narrower AI trade
In its August 27, 2026 commentary, “A Market in Transition”, partner Olga Bitel and strategy analyst Alexa Davis describe a market in which index-level resilience concealed a change in what was driving performance. AI-related technology and infrastructure had been important sources of gains, but their momentum weakened as participation spread across more industries and countries.
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The authors’ point is about market leadership and dispersion—not a claim that every AI-linked company fell, that AI investment stopped, or that a broad downturn began. They describe the environment as “a classic stockpickers’ market,” where company-level differences matter more when no single sector clearly leads.
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What the reported returns show—and when
William Blair’s figures below are historical returns for the stated benchmarks and periods, not current returns as of October 2026. The firm cites FactSet and its own analysis. These are different exposures, so the table is a comparison of reported performance rather than a claim that every measure represents the same market segment.
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| Exposure | Q2 2026 return | Q3 2026 through August 19 |
|---|---|---|
| U.S. all-cap equities | 15.7% | 2.6% |
| Developed-market equities outside the U.S. | 14.0% | 2.0% |
| Emerging-market equities | 22.8% | -2.5% |
| Global small-cap equities | 15.1% | Not stated for this period by William Blair |
| U.S. value equities | Not stated in this comparison | 5.8% |
The Q2 figures show emerging markets and global small caps ahead of U.S. all-cap equities during that quarter. The partial Q3 figures tell a different story: emerging markets were down through August 19 while U.S. all-cap, developed markets outside the U.S., and U.S. value were positive. The windows should not be combined into a single claim about who was “winning” in 2026.
William Blair says the emerging-market Q3 decline was affected by rotation in South Korean and Taiwanese companies connected to the AI technology and infrastructure buildout. It also says technology drove most aggregate S&P 500 returns in April and May, then detracted materially in June and July, with other sectors partly offsetting that weakness. Neither observation means the entire S&P 500 was flat or that all AI companies declined.
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Why the authors think leadership is changing
Bitel and Davis frame the rotation as taking place within an expanding economy, rather than as clear evidence that investors were anticipating a downturn. Their August assessment pointed to improving supply- and demand-side indicators, including manufacturing purchasing managers’ indexes, auto sales, and inflation-adjusted retail sales. They said economic data generally surprised to the upside in the United States, euro area, and Japan, while China and Latin America disappointed relative to expectations and emerging-market Asia lost some momentum. These are the authors’ interpretations of conditions at that time.
Their outlook also identified sources of uncertainty that could affect inflation and the durability of the rotation:
- Energy prices: Changes in energy costs can affect inflation and the outlook for businesses and consumers.
- Semiconductor prices: Memory-chip supply constraints were adding pressure to goods costs, although the authors said some South Korean memory-chip export-price pressure might be easing.
- Tariffs: The authors expected changes in U.S. tariff policy to continue, including through mechanisms such as Section 301. That was an August 2026 policy outlook, not a statement that tariff conditions remain unchanged.
William Blair also linked higher government-bond yields to demand for capital as investment grows in physical infrastructure, manufacturing, energy, defense, and other tangible assets. Its argument was that higher rates do not necessarily imply worsening debt dynamics if nominal GDP grows faster than nominal borrowing costs. As a historical illustration, the article said Japan’s government debt-to-GDP ratio fell 10% after peaking in 2022 while 10-year yields rose nearly 200 basis points from 2022 through 2025. That example is the authors’ argument, not a general assurance about debt sustainability.
How the AI investment thesis separates near-term activity from eventual winners
In a July 15, 2026 article, “Waiting for AI Winners to Emerge”, Bitel distinguished spending on AI infrastructure from the harder, longer-term question of which businesses will turn AI into useful products and durable revenue. She said infrastructure had driven equity-market gains for more than a year, while rising chip prices and capacity expansion were shifting near-term leadership toward semiconductor-equipment companies.
That near-term supplier activity does not establish which application-layer businesses will succeed. Bitel’s longer-term test was whether companies use AI to improve efficiency or generate revenue. The July article described leading language models as becoming “good enough” for some applications and noted declining token prices in its July 2026 discussion; those observations were time-bound, not a guarantee about future adoption or profits.
An earlier William Blair article, “A Broader Market Awakening”, published March 3, 2026, placed the shift in a wider capital-expenditure thesis. It described investment in data centers, semiconductors, cooling, power, defense, energy, and supply chains as a potential source of growth across more sectors and regions. That earlier framing offers context for the structural argument, but it should not replace the August article’s more recent and specifically dated performance figures.
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Does a broader market mean investors should sell AI stocks?
No such instruction follows from William Blair’s commentary. The authors describe a change in market leadership and argue that selection among companies may matter more; they do not say every investor should sell AI holdings or that one allocation will outperform. The August article says its information is not a recommendation to buy or sell shares, and that investment strategies may not suit every investor.
For readers assessing the argument, keep three distinctions in view:
- Historical returns versus forecasts: The reported Q2 and Q3-to-date returns describe past periods. They do not predict what will lead next.
- Market theme versus individual business: A slowdown in AI-related technology and infrastructure leadership does not establish that every company connected to AI weakened, or whether a specific firm can earn durable returns from AI.
- Broadening versus guaranteed rotation: Wider participation can coexist with losses in some regions or sectors, as the Q3-to-date emerging-market figure illustrates. It does not prove that leadership will continue to broaden.
William Blair notes that the indexes discussed are unmanaged and cannot be invested in directly, and that past performance does not indicate future returns. Portfolio decisions require an investor’s own goals, time horizon, and risk tolerance; these market observations alone cannot determine an appropriate holding.
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