A structural shift is redrawing the revenue map of global equity markets, and the primary author of that shift is artificial intelligence. Morningstar Indexes' 2026 global revenue study, written by Dan Lefkovitz, finds that the majority of the world's national stock markets now derive a larger share of revenues from abroad than they did a year ago. The mechanism driving that change is not trade policy or macroeconomic convergence. It is the rise of AI.
Lefkovitz is direct about the pattern: markets that have grown more internationally oriented in their revenues are "all home to important artificial intelligence stocks." Broadcom, Taiwan Semiconductor Manufacturing, Samsung Electronics, Tokyo Electron, ASML, and Alibaba are named explicitly. As those companies have grown in market value, they have pulled their home markets, the US, South Korea, Taiwan, Japan, the Netherlands, and China, into a more global revenue orientation. The US itself now sources just 59% of its stock market revenues domestically, down from 61% a year ago.
The investment implication is immediate. A position in a Korean or Taiwanese equity index is no longer primarily a bet on domestic economic conditions. It is increasingly an expression of exposure to the global AI supply chain.
Natural Resources: The Second Globalizing Force
AI is not working alone. Lefkovitz notes that "AI, clean energy, and geopolitics have driven a global mining boom," with gold and oil prices also rising between mid-2025 and mid-2026. Natural resources-driven markets, including Brazil, Chile, Australia, South Africa, and much of the Persian Gulf, have each become more globally oriented in their revenue mix. Vale, Petrobras, SQM, BHP, and Gold Fields are among the companies that have grown in relative market prominence. The UK, likewise, has globalized further through Shell, BP, Rio Tinto, and Glencore.
The resource globalization story is directionally similar to the AI story but structurally different. These markets are tied to commodity cycles and industrial demand, not to technology infrastructure spending, and they carry a meaningfully different correlation profile as a result.
Correlation Is Where the Diversification Argument Gets Tested
The study's most actionable finding concerns portfolio correlation. Lefkovitz states plainly that "stock markets reliant on AI are more correlated than those with no exposure." Taiwan, Korea, and the Netherlands have been tightly tied to the US over the past three years, because companies like TSMC, SK Hynix, and ASML are "dependent on the same factors as US mega-caps Nvidia and Broadcom." Owning those markets alongside a heavy US technology allocation provides less diversification than the geographic labels suggest.
The clearer diversification benefit lies elsewhere. Brazil, Indonesia, and India register lower correlations with the US, anchored by domestic revenues or commodity exposure. The most domestically oriented markets globally tend to be emerging, countries like Egypt, Indonesia, Pakistan, Turkey, and India, with little AI or natural resources weighting. As Lefkovitz concludes, "some national equity markets are more national than others."
Five Key Takeaways for Advisors and Investors
1 Geographic label does not equal geographic revenue exposure. Revenue source data, not country of listing, should anchor allocation decisions.
2 AI-driven markets move together. Taiwan, Korea, and the Netherlands now correlate tightly with the US. Owning all of them alongside US technology does not diversify AI risk.
3 Natural resources offer a structurally different global exposure. Brazil, Chile, and Australia have globalized through commodity cycles, not technology, and carry a different correlation profile.
4 Domestically anchored emerging markets are the clearest diversifiers. India, Indonesia, and Egypt remain less correlated to US equity cycles and merit reconsideration on that basis.
5 Revenue geography is a standard portfolio construction input, not a secondary consideration. Where a market's companies actually earn their revenues defines the true risk exposure, regardless of where they are listed.
Footnote:
1 Lefkovitz, Dan. "AI Is Globalizing Many of the World's Stock Markets. Here's What That Means for Investors." Morningstar Indexes, 8 July 2026, indexes.morningstar.com/insights/perspective/bltd965372079d6c778/ai-is-globalizing-many-of-the-worlds-stock-markets-heres-what-that-means-for-investors.
