AI Becomes a Geopolitical Race as Governments Expand National Strategies

AI Moves Into the Geopolitical Arena

Artificial intelligence is increasingly becoming a matter of national strategy as governments seek greater control over the technologies, infrastructure and resources needed to develop and deploy advanced AI.

The emerging competition extends beyond the race between individual technology companies. Governments are focusing on computing capacity, advanced semiconductors, data, skilled workers, cloud infrastructure and access to AI models as strategic resources.

Stanford University's 2026 AI Index describes this approach as AI sovereignty: a country's ability to independently control important parts of its AI ecosystem, including compute, models, talent, data and deployment.

The shift reflects a broader recognition that AI can influence economic competitiveness, public services, scientific research, cybersecurity and national security.

Washington and Beijing Compete for Advantage

The United States has placed AI leadership at the centre of its economic and national-security strategy. The White House's AI Action Plan contains more than 90 policy actions covering innovation, infrastructure, international diplomacy and security.

The plan also includes efforts to export American AI technology to allied countries, linking technological leadership with international influence.

In June 2026, the White House directed the national-security establishment to accelerate AI adoption and make advanced AI capabilities available across national-security applications.

China is pursuing its own broad national approach. Beijing's "AI+" strategy seeks to integrate artificial intelligence into science, industry, consumption, public services and governance.

Chinese policy targets widespread AI integration, including more than 70% adoption of intelligent terminals and agents in six priority areas by 2027, with the target rising above 90% by 2030.

The competition therefore involves not only the development of powerful AI models, but also the infrastructure and industrial systems required to use them at scale.

Europe and Middle Powers Seek Autonomy

The European Union is pursuing a different model, combining technological development with regulation and efforts to strengthen domestic capacity.

Its AI Continent strategy focuses on computing infrastructure, data, skills, AI adoption and governance. By April 2026, the EU said it had 19 operational AI Factories and 13 AI Factory antennas.

The bloc has also described AI capability as part of technological sovereignty. Its cybersecurity planning calls for continued investment in sovereign AI capabilities.

Other countries are seeking to avoid becoming completely dependent on either Washington or Beijing. Brazil, for example, announced roughly $444 million in AI infrastructure investment, dividing major projects between Chinese and US technology suppliers as part of an effort to maintain strategic autonomy.

China has accused Washington of pressuring countries to choose sides in the AI competition and has promoted the concept of digital sovereignty.

The Race Is Also About Energy and Resources

The geopolitical AI race is increasingly connected to physical resources. Advanced AI requires large amounts of computing power, which in turn requires data centres, electricity, cooling systems, networks and skilled workers.

A recent academic analysis identified electricity, water, data and skilled labour as important strategic resources in AI competition.

The expansion of data centres is already affecting energy policy. Australia, for example, is preparing regulation for growing data-centre demand as AI and cloud computing expand.

The emerging AI competition is therefore a contest over infrastructure and resources as much as algorithms.

For developing countries, the question is how to participate without becoming permanently dependent on foreign technology.

What It Means for Bangladesh

Bangladesh does not need to compete with the United States or China in developing frontier AI models to benefit from the technology. A national strategy could instead focus on areas where local capacity can have practical value.

These include AI skills, local-language models and datasets, digital public services, cybersecurity, research capacity, affordable computing and partnerships with multiple technology providers.

The central strategic concern is dependency. If AI models, chips, cloud services and computing infrastructure become concentrated among a small number of countries and companies, developing economies could find themselves primarily consuming technology rather than shaping its development.

For Bangladesh and other emerging economies, the expanding AI race therefore presents both an opportunity and a strategic challenge: build domestic capability while maintaining access to global technology, investment and expertise.