AI infrastructure, the key to global AI supremacy Premium

Artificial Intelligence infrastructure is the key factor in the global race for AI supremacy

The United States has made a bold move in the global artificial intelligence (AI) race with its new federal AI infrastructure policy. What appears to be a domestic initiative to establish AI data centres across federal lands, is actually a well-thought-out strategy to maintain America’s technological supremacy in this field. Other countries have also developed their own AI infrastructure strategies to face this competition. India faces resource constraints. The challenge for India, therefore, lies in adopting a strategy which will work without the deep financial reserves of the U.S. or China.

AI can be considered to be a technology in the mould of general purpose technologies (GPTs) that Jeffrey Ding has described in his GPT Diffusion Theory. It has a pervasive impact on different sectors, and requires a comprehensive infrastructure, including skill infrastructure, to thrive and diffuse.

The U.S. policy aims at national security and AI leadership at its core. This is not just about building data centres. It is about building enough infrastructure domestically to ensure that research and development in this field can progress without any impediments. It can help strengthen America’s position as the global AI gatekeeper, if it can control the compute or resources layer of the AI technology stack. However, does not this raise important questions about the future of technological cooperation in an interconnected world? This throws to the wind the traditional concepts of market forces and comparative advantages which should be driving the allocation of resources globally. Are these to be superseded by national security concerns?

The answer is not straightforward. Techno-nationalism is here to stay, where a country’s worth is decided by its technological prowess. The U.S. has already imposed restrictions on the export of high-end AI chips to China. This highlights the geopolitical dimensions of AI infrastructure development.

The world will see a lot of this competitive one-upmanship in the garb of narratives of self-sufficiency and technological leadership. It would be better for nations to do a comprehensive cost-benefit analysis of such decisions to be able to harmonise national interests with global partnerships.

China also has invested heavily in domestic AI chip manufacturing and government-backed AI research. Companies such as Huawei and the Semiconductor Manufacturing International Corporation (SMIC) are at the forefront of developing indigenous alternatives to Nvidia’s AI chips, ensuring that China is not entirely dependent on western technology. A lot of this is driven by creative insecurity brought on by the tech and trade wars unleashed by the U.S. In addition, China, too, has aggressively been expanding its data centre networks, integrating AI computing with its broader push for digital infrastructure dominance under the Belt and Road Initiative. These are different models of doing the same thing — establishing AI supremacy. Unlike the U.S., which is leveraging public-private partnerships, China’s model is deeply state-driven, with massive subsidies and policy support ensuring rapid progress. One could argue that both are market distorting interventions.

The European Union is also taking AI infrastructure seriously but with a focus on ethics, regulation, and sustainability. They have been investing in sovereign cloud infrastructure to reduce reliance on foreign multi-national companies. Additionally, it is actively promoting open-source AI models. The aim is to keep AI development transparent and accessible to smaller businesses and researchers.