Lucas Plé: Hello everyone, and welcome to this latest episode of MacroWaves, the podcast from BNP Paribas’ Economic Research department. Today, we’re going to look at the role of artificial intelligence in the economic development of emerging countries. Which emerging economies are best positioned within supply chains to capitalise on the rise of AI? What challenges will they face in rolling ou t AI on a large scale in the medium term? What productivity gains can be expected?
My name is Lucas Plé, and I am the economist specialising in sub-Saharan Africa. To answer these questions today, I am joined by Christine Peltier, head of the emerging economies team, and Hélène Drouot, our Latin America economist. Hello!
Christine Peltier and Hélène Drouot: Hello.
Lucas Plé: Let’s start with an overview. In 2025, economic growth in emerging economies is estimated at 4.3%. This figure is partly due to strong export performance, driven by global demand for electronic products and AI-related goods. Christine, can you tell us which countries are benefiting most from the surge in demand for AI-related goods?
Christine Peltier: According to the World Trade Organisation’s (WTO) classification, exports of AI-related goods reached 12% of total global merchandise exports in 2025, amounting to $3.3 trillion. Of this total, 65% is exported by industrialised Asian countries. The region therefore holds a dominant position in this sector, particularly in the semiconductor sector, as it accounts for 85% of global exports. The short-term outlook for these countries is very good: the semiconductor market is expected to grow by a further 26% in 2026, following an already exceptional year in 2025.
Lucas Plé: So, emerging Asia is in pole position to capitalise on the rise of AI, but are all countries equally prepared?
Christine Peltier: Well, no, not exactly. Taiwan stands out clearly, as it boasts the highest specialisation rate in the world: 61% of its exports are AI-related goods. The country’s strategic position is significant because it manufactures almost all of the most advanced chips used by AI. The country therefore holds a strategic advantage in its negotiations with trading partners, especially the United States.
Lucas Plé: You’re suggesting that Taiwan holds a monopoly on the production of the most sophisticated chips; does that mean other countries are positioning themselves in other segments of the production chain?
Christine Peltier: That’s right. We see specialisation across the various stages of production. Taiwan, South Korea and Japan have specialised in the manufacture of silicon wafers onto which integrated circuits are etched. Together with China, these four countries accounted for 80% of wafer production capacity in 2025. Further along the supply chain, we find Malaysia, Vietnam and the Philippines, which have specialised in the assembly, testing and packaging of chips. For these countries, although the contribution to GDP is more modest compared to advanced etching, the rise of AI also served as a catalyst for economic expansion in 2025.
Christine Peltier: By specialising in the manufacture of microchips, emerging Asia has successfully captured a large share of the global market for AI-related exports. But the manufacture of chips and semiconductors relies heavily on metals and minerals. Can emerging countries that produce commodities also thrive on the expansion of IA?
Hélène Drouot: Indeed, Christine, several emerging countries have a strategic advantage thanks to their natural resources. We might be tempted to overlook this, as raw materials account for only 2% of the total export value of AI-related goods, according to WTO classification. However, while AI uses relatively few metals and minerals in proportion to the added value of finished products, these raw materials are essential and, above all, difficult to substitute. This gives producers of critical metals a strong strategic advantage. This is exemplified by China, which controls a significant portion of the global supply of rare earths and refined minerals. China also imposes export restrictions, which it uses as a tool for exerting diplomatic pressure.
Christine Peltier: Global demand for raw materials essential to AI is set to rise sharply in the coming years, particularly for copper, where demand is expected to surge due to the expansion of data centres. How can emerging economies make the most of this?
Hélène Drouot: Exporters of critical metals and minerals, such as Latin American countries and Indonesia, will need to attract foreign investment and forge new trade partnerships. This appeal is primarily achieved through a favourable business environment and strong, stable institutions. However, in the long run, the challenge for them will be to avoid remaining mere exporters of raw materials. They will need to move further up the value chains by transforming their raw inputs into intermediate products. This will, however, involve tackling significant environmental issues, particularly in Brazil, Chile and Argentina.
Hélène Drouot: The rise of AI is expected to drive up demand for raw materials, as well as for electricity. What is the current status of AI-related electricity consumption in emerging countries?
Lucas Plé: Well, at present, excluding China, it is marginal: the AI sector accounts for less than 0.5% of total electricity demand. For emerging economies, the focus continues to be on industrial development and air conditioning, which will be the primary factors driving the increase in electricity demand in the coming years.
Hélène Drouot: So China is a special case?
Lucas Plé: Absolutely. China holds a dominant position in AI. Electricity consumption by its data centres has risen by an average of 15% per year over the last decade, now matching the consumption of its entire fleet of electric vehicles. To meet the growing demand for electricity, it has a clear strategy, which involves increasing electricity generation by 4% per year between now and 2030. It is not the only emerging country banking on AI, incidentally. The Gulf states are also planning a massive roll-out of AI by 2030. They are relying on their abundant oil wealth to build and power data centres at an unbeatable cost.
Hélène Drouot: In this race to adopt AI, will there be any losers?
Lucas Plé: Due to its low electrification rate, sub-Saharan Africa risks being sidelined in the AI race. Its share of total global foreign investment flows is likely to fall, despite already being extremely low. This situation could even lead to challenges in securing external financing in both the short and medium term.
Hélène Drouot: Now that we’re on the subject of AI adoption, let’s look at the productivity gains it could bring: Christine, do you think AI will transform the economies of emerging countries in the short term?
Christine Peltier: We need to be cautious. At the moment, massive investment by the American Big Four is driving up demand for technology products, and this is directly fostering growth in several emerging economies. However, for AI to boost local productivity and increase growth potential in the medium term, it will take a long time for AI-related skills to become widespread. It’s not enough just to buy chips; you need to train people, reorganise production processes and invest heavily in human capital. That is the key challenge for Central Europe. Countries like Poland and Hungary may lack critical metals, yet they are banking on a skilled workforce and ambitious government plans to integrate AI into their industries and reap the benefits.
Hélène Drouot: Conversely, does AI also pose economic risks?
Christine Peltier: Of course. There is a high risk of dependence on a limited number of countries. At present, 82% of global AI development capacity is concentrated in the United States, the European Union and China. China’s presence across almost the entire AI value chain could increase global trade dependence on China in the short term. Furthermore, the rivalry between China and the United States poses a significant geopolitical risk that could lead to supply chain disruptions. Finally, and quite simply, economies are exposed to a potential correction in the technology boom – in other words, the bursting of the ‘AI bubble’.
Lucas Plé: Thank you very much for your insights, Christine and Hélène. In summary, emerging economies have various strategic resources that they can leverage due to the rise of artificial intelligence. Countries that are strategically positioned within AI supply chains, particularly in Asia, gain both a growth driver and a geopolitical advantage. Similarly, commodity-exporting countries hold strategic importance, but they need to move up the value chains to make the most of AI’s development. The outlook is therefore favourable. However, we must remain vigilant regarding the economic and geopolitical risks, as well as the challenges that the adoption of AI entails.
We invite our listeners to explore these topics in detail by consulting our latest issue of EcoPerspectives, which focuses on emerging economies and is available on the BNP Paribas Economic Research website. The links can be found in the description.
We’ll be back shortly with the next issue of MacroWaves.
EcoPerspectives - Emerging Economies | First quarter of 2026, as of February 27, 2026– Economic Research – BNP Paribas
