A new wave of digital inequality is forming as AI computing power concentrates in a few countries and firms. An Oxford University study, reinforced by in-depth reporting from a leading U.S. newspaper, shows that most powerful AI systems run on data centers owned by a handful of players. This gap threatens economic competitiveness, scientific progress, and national security for countries outside the core hubs, including Thailand.
The opening of OpenAI’s planned massive data center in Texas illustrates the scale of resources now required to run cutting-edge AI. In contrast, researchers in some regions operate aging hardware in makeshift facilities, underscoring a widening gulf in compute power that is outpacing growth elsewhere.
What does this mean for Thailand and other developing nations? Compute power is increasingly treated as a strategic national resource. Without sufficient access, even skilled engineers and ambitious startups face barriers: AI tools that don’t fully support Thai language nuances, slower innovation, reduced global competitiveness, and greater reliance on foreign tech providers for digital infrastructure.
Key findings from the Oxford study highlight that only about 32 nations—roughly 16% of all countries—host major AI data centers. The United States, China, and the European Union together account for the majority of advanced AI infrastructure. Major tech firms control the bulk of global AI data centers, reinforcing the divide. In Africa and South America, large-scale AI hubs are scarce; Southeast Asia, including Thailand, shows lagging progress. Data from leading outlets emphasizes how regional gaps persist despite regional growth in tech ecosystems.
Modern data centers exceed the scale of older facilities. They require substantial investment, dependable electricity, advanced cooling, and specialized semiconductor chips—predominantly from Nvidia. This concentration of resources accelerates advances in data processing, automation, AI-assisted research, and, in some cases, AI-enabled weapons development.
Language matters in the AI race. High-performing platforms tend to excel in English and Chinese, languages dominant in the regions with the most compute capacity. For languages with smaller digital footprints, such as Thai, the absence of nearby data centers means limited AI functionality and slower access to new tools.
The consequences extend beyond technology. Nations left outside the AI revolution risk “brain drain,” as top talent seeks better resources abroad. Renting AI compute remotely can be expensive and unreliable, complicating cross-border work and creating dependencies on foreign firms.
Industry and government leaders acknowledge these challenges. Executives from major AI players and regional policy bodies point to the compute gap as a threat to digital sovereignty. The emphasis is clear: it is about more than hardware; it is about shaping a nation’s digital future.
Some governments are responding decisively. India is supporting local AI development across diverse languages. Brazil is dedicating substantial funding to homegrown AI, while the European Union is investing heavily in domestic data infrastructure. In Africa, efforts to build continental data capabilities are underway, though demand often outstrips supply. Regional initiatives in Southeast Asia are also evolving, with investments in infrastructure that could benefit neighboring countries including Thailand.
The competition remains intensely regional and global, with the United States and China shaping policies to protect their tech edge. Trade controls influence which nations can access advanced AI chips, while China supports its AI centers with incentives linked to domestic technologies.
Thailand sits in the middle of this dynamic, as multinational firms expand regional infrastructure in nearby hubs. Yet many neighbors still rely on overseas compute, limiting customization for local needs and languages. This has direct implications for Thai education, healthcare, and industry if AI tools cannot be effectively localized.
The implications are clear for Thailand: without robust AI infrastructure, researchers and startups may struggle to develop Thai-language AI solutions, address local health challenges, or tailor technology to local industries. Education, a national priority, risks falling behind if AI tools don’t align with Thai curricula and cultural contexts.
Thailand’s leadership—government, universities, and private enterprises—should treat this report as a warning and a call to action. Building domestic compute capacity, fostering regional collaboration, and incentivizing local data centers are essential steps to protect digital sovereignty and future prosperity. Open collaboration with ASEAN partners can help pool resources for shared infrastructure while ensuring Thai-language innovation remains central.
Looking ahead, the push for sovereign AI capabilities is likely to intensify. Public-private partnerships and regional coalitions should be leveraged to expand local infrastructure, with a focus on open access to AI tools and language-friendly technologies. Thai researchers and educators must advocate for inclusive AI that serves local languages and cultural needs.
For policymakers, educators, and business leaders in Thailand, practical steps include increasing investment in advanced digital infrastructure, forming regional computing consortia, and pursuing open access to global AI technology with safeguards. Encouraging more Thai students into STEM fields and attracting returning digital talent will be crucial. The public should engage in discussions about how AI affects jobs, language representation, and national resilience to inform sound policy choices.
If Thailand is to thrive in the AI era, bridging the compute divide must become a national priority. Equitable digital access, strategic investment, and regional collaboration are not mere technical concerns—they are central to Thailand’s economic and social wellbeing in a rapidly shifting global landscape.