How AI is reshaping emerging markets equities

One question we have been hearing consistently from clients is: How will AI developments affect investments in emerging markets (EM)? While China’s AI story has been much discussed, the impacts on other emerging economies remain less well known. So, we thought it would be an excellent time to take stock of the competitive advantages in the EM equity space, identify some of the challenges, and highlight where additional strategic focus is needed.

The US dollar is not the only driver of EM returns this year

One of the cleanest explanations of the EM resurgence this year has been the US dollar, or more precisely, its weakness. Dollar weakness helps international liquidity, promotes risk-seeking behavior among non-US investors, and gives space to EM central banks space to loosen monetary conditions. What’s more, it is helpful for corporates that may have picked up US dollar debt when rates were low. This is all undoubtedly helpful, but it doesn't paint the full picture: More than half of the year-to-date return for EM equities has come from AI and related technology themes.

So much of the focus in AI and tech has been on US dominance—which, to be fair, is the epicenter—but emerging market companies are surely in the game. With that in mind, we have taken a deeper dive to uncover the competitive advantages that various EM countries and regions have in AI research, adoption, and delivery.

Let’s start with China

Chinese equities began 2025 as one of the worst-performing markets in the post-Covid world, plagued by a softening economy, a roiling property crisis, and foreign outflows. But we saw how quickly things can change in emerging markets when news broke in January that the Chinese start-up DeepSeek had created a powerful AI model that was significantly cheaper and more efficient than US competitors. This proved to be a catalyst for the broader Chinese index (as well as a shift in policy support).

In truth, there were indicators of China’s AI resurgence that foreshadowed the DeepSeek news. Training large language models (LLM) is a highly energy-intensive area, prompting China to investigate a range of energy options in recent years, including alternative sources, nuclear, and cross-border supply from Russia. Additionally, Chinese authorities have poured resources into AI infrastructure. The net result of these efforts is a surging equity market with companies that are investing across the entire AI spectrum, from specialized AI chip manufacturers, machine learning agents, LLM generation, and AI data centers. Well-capitalized firms like Alibaba, Tencent, and Baidu have cemented themselves as global leaders across the AI tech stack.

It should be noted that US policy has not been constructive here. In what could be described as an “own goal,” controls over US semiconductor exports may have caused a quantum jump in local Chinese manufacturing capabilities.

We are optimistic that China is an “AI winner,” but we would temper that enthusiasm with a reminder that China’s problem may well be that … it’s China. As the AI story unfolds, how willing will the Western world be to set aside concerns surrounding security, surveillance, and governance? There will almost certainly be some limits on global adoption of Chinese AI models.

Taiwan

As the world’s leading producer of chips with unrivaled semiconductor manufacturing capabilities, Taiwan is a natural beneficiary of AI investment and advancements. Indeed, the broad IT sector in Taiwan has generated a return of close to 130% in the two-year period ending September 30, 2025.¹ While EM index behemoth Taiwan Semiconductor Manufacturing Co. has garnered most of the attention as the world’s largest semiconductor foundry, the entire IT ecosystem in Taiwan—both upstream and downstream—is central to the AI supply chain.

Taiwanese authorities have recognized their advantageous position as an AI manufacturing leader. They have recently launched an aggressive initiative that identified core technological priorities aimed at generating more than $500bn in economic value over the next 15 years, and potentially transforming the economy from supply chain manufacturer to indispensable AI superpower.

South Korea

South Korean’s footprint in the AI ecosystem to this point has been heavily concentrated in the production of high bandwidth memory (HBM) chips, which are key components along the AI supply chain. Index heavyweights Samsung Electronics and SK Hynix hold a dominant market share in this space, but there is recognition among leaders that diversification across the tech stack is necessary to remain a global leader.

To this end, the country is investing heavily in AI infrastructure, including construction of one of the largest data centers globally. Specific pockets of the market where we have seen advancements along the AI spectrum include: 1) telecommunications, where SK Telecom has transformed itself, moving from a traditional telecom to a provider of full-stack AI value chain services; 2) e-commerce, where Naver, once known primarily as a search engine service, has become a full-service provider of commerce-centric AI tools, as a result of strategic acquisitions.

India

India’s IT exposure lies primarily in the software and services realm, an area that thrived as demand for digital services surged during Covid, but which has limited linkage to AI— meaning India has thus far missed the AI rally. Simply put, whereas South Korea and Taiwan used their hardware infrastructure as a natural foray into AI, India has not sufficiently invested in AI expertise or foundational capabilities.

The good news for Indian investors, however, is that end-user AI adoption levels in India have been among the highest worldwide, and that usage has garnered the attention of industry leaders. Microsoft, OpenAI, and Google have all recently announced plans to ramp up investments in India. While gaining ground with their Asian peers on chip fabrication appears to be difficult, these types of investments provide India an opportunity to establish itself as a host for AI infrastructure. To this end, India does have building blocks in place to find a niche position along the AI tech stack—namely robust data infrastructure, a vast pool of engineers and data scientists, and historically strong government and digital support that has promoted start-ups. To achieve an end-goal of AI autonomy, Indian leaders will need to continue to capitalize on their structural advantages, closing the gap on AI funding relative to peers, and overcome natural challenges such as poor access to energy sources. We continue to believe that AI deployment will likely be a natural next step for the main players. The risk here is that base-level IT support functions may be at risk from innovation.

GCC (Gulf Co-operation Council)

The countries in the Middle East have some interesting advantages in the AI value chain. Their primary advantage is clearly financial resources, as energy revenues and sovereign wealth funds enable governments to fund strategic development initiatives. For example, national programs like Saudi Vision 2030 and UAE AI Strategy 2031 outline clear plans for those nations to become integrated parts of the new global technology ecosystem. Through substantial investments in research and infrastructure, the GCC is cultivating a still-emerging, but increasingly credible, innovation economy. Nonetheless, while strategic plans are important, execution risks remain and the sector is still heavily reliant on foreign firms and foreign talent. What’s more, if oil prices were to dip into the $50-$55 range, the GCC countries could be forced to reassess their investment priorities as energy revenue would come under pressure.

Other emerging markets

As in much of the global business landscape, AI in many emerging markets remains in its infancy. These nations often lack key enablers of AI development—such as abundant STEM talent, affordable energy, and a robust pipeline of tech firms to drive adoption. It is worth remembering that the IT sector weight for both Latin America and EMEA is less than 1%. This is not a great starting point for some emerging economies, especially when developments in the rest of the world are running at a fast pace.

AI’s momentum in EM – and the road ahead

So far in 2025, exposure to AI has quietly strengthened EM returns. But the outlook remains uneven, as countries lacking key labor or infrastructure components may struggle to level the playing field. Still, for investors in the high-dispersion world of EM, these disparities can help create new opportunities, whether because of valuation or through a general desire to diversify (rebalance away) from the US technology mega caps in search of strategic areas outside the US that may have not gotten sufficient attention.