A new era of digital inequality is emerging worldwide, as recent research reveals that artificial intelligence (AI) computing power is rapidly becoming concentrated in just a handful of countries and companies. This growing divide between AI “haves” and “have-nots” is set to disrupt economies, fuel geopolitical rivalries, and shape the scientific and social futures of entire nations, according to a major new investigation by Oxford University researchers and reporting by The New York Times (nytimes.com).
The opening of OpenAI’s planned $60 billion AI data center in Texas—set to be one of the world’s largest—highlights the staggering resources now required to run the most powerful AI systems. Meanwhile, researchers in countries such as Argentina are operating hubs with aging chips in makeshift facilities, underscoring how the gulf in “compute power” is widening faster than ever.
Why does this matter for Thailand and other developing nations? Compute power—the immense processing capability needed to train and run advanced AI—has become an essential national resource, often compared to oil in its potential to influence global power structures. Without it, even countries with skilled engineers and ambitious start-ups face severe limitations: language barriers in AI tools, restrictions on scientific innovation, reduced competitiveness, and dependency on foreign technology giants for digital infrastructure.
According to the Oxford study, just 32 nations—or about 16% of countries—possess major AI data centers. The US, China, and the European Union together account for over half of the world’s advanced AI infrastructure. US and Chinese firms, including Amazon, Google, Microsoft, Tencent, and Alibaba, control over 90% of the data centers used for global AI work, making the divide even more stark. Africa and South America have almost no large AI computing hubs, and while Japan and India are making progress with a handful of centers each, most of Southeast Asia—Thailand included—lags far behind (nytimes.com).
Data centers today are far more complex than their predecessors that ran email or provided video streaming. They demand billions in investment, robust electrical grids, advanced cooling systems, and clusters of highly specialised microchips—primarily from the US chipmaker Nvidia. With this immense concentration of resources, tech behemoths with access to cutting-edge equipment are rapidly advancing in data processing, automation, AI-assisted scientific research, and even AI-driven weapons systems.
This divide is also linguistic: most high-performing AI platforms, including OpenAI’s ChatGPT, perform best in English and Chinese, languages dominant in the regions with the greatest compute capacity. For communities speaking less-represented languages—from Swahili to Thai—the lack of dedicated data centers means a persistent gap in AI functionality and access.
The risks go well beyond technology. Nations left out of the AI revolution are experiencing “brain drain,” with top talent moving abroad for access to better resources. As a leading Kenyan AI start-up founder explained, “If you don’t have the resources for compute to process the data and to build your AI models, then you can’t go anywhere.” Renting AI compute remotely is costly and unreliable, presenting hurdles such as slow connections, legal complications, and vulnerability to the monopoly power of foreign corporations.
Major players acknowledge the challenge. Executives from OpenAI, Microsoft, Nvidia, and African digital policy bodies told The New York Times that the ‘compute gap’ now threatens to reinforce the inequalities of earlier technology revolutions. “It’s not merely a hardware problem. It’s the sovereignty of our digital future,” said the Director General of Smart Africa.
In response, some governments are taking bold steps. India is subsidizing local AI development for its diverse languages. Brazil has committed $4 billion to homegrown AI, while the EU is investing €200 billion in local data infrastructure. Africa’s Cassava Technologies, founded by a Zimbabwean billionaire and backed by Google, plans to open a cutting-edge data center continental-wide, although demand is projected to far outstrip the available supply.
But the global race is marked by jostling between the US and China, both wielding strike policies to maintain their tech edge. US trade restrictions have limited which countries can buy advanced AI chips, thereby choosing technological ‘winners’ and ‘losers.’ China has financed its own AI centers globally, often with incentives tied to using Chinese technology.
Southeast Asia, including Thailand, finds itself swept into this digital competition. While tech giants such as Amazon, Alibaba, and ByteDance are investing in regional infrastructure in Singapore and Malaysia, many neighbors still rely on external compute, limiting their ability to customize AI for local needs and languages (nytimes.com).
For Thailand, the stakes are significant. Without adequate AI infrastructure, Thai researchers and start-ups struggle to create competitive AI solutions tailored to the Thai language, healthcare challenges, or local industries. The education sector, a top national priority, risks falling behind if it cannot harness AI tools customized for local curricula and cultural contexts.
Thailand’s government, universities, and the private sector should take this research as a wake-up call. As AI becomes a driver of everything from economic competitiveness to national security, the ability to access and control local compute power will be a decisive factor in shaping the country’s digital sovereignty and social future. Policy choices—from public investment in AI research infrastructure, to regional collaborations with ASEAN neighbors, to incentives for local data center construction—will determine Thailand’s place in the emerging global AI landscape.
Looking ahead, the coming years will likely see even greater focus on building localized, “sovereign AI” capabilities in emerging markets. Multilateral partnerships, public-private alliances, and regional coalitions—such as the ongoing ASEAN Smart Cities Network—should be leveraged to pool resources for shared digital infrastructure. At the same time, Thai researchers and educators must continue advocating for open, equitable access to AI tools, especially for Thai-language innovation and culturally relevant applications.
For businesses, educators, and policymakers in Thailand, the path forward includes supporting domestic investment in advanced digital infrastructure, exploring regional consortiums for shared computing resources, and pressing for open access to global AI technology. Increasing the number of Thai students entering STEM fields and encouraging return migration of digital talent will be crucial. For the public, understanding the implications of this digital divide—on job opportunities, linguistic representation in AI, and national resilience—will be essential in shaping democratic debate and sound policy choices.
If Thailand is to thrive in the age of AI, bridging the compute gap must become a national priority. Equitable digital access, investment in infrastructure, and strategic partnerships are not just technological questions—they are now central to Thailand’s economic and social wellbeing in a world rapidly divided by digital power.
Sources: nytimes.com