The AI Arms Race: Governance, Decoupling, and Tech Cold Wars

From chip wars to classrooms, AI is redefining geopolitics. With its Vikram-32 chip, India steps onto the battlefield. Who decides how AI reshapes our world?

Introduction: A Different Kind of Global Contest

The superpower rivalries of the past revolved around nuclear arsenals and space exploration. Today, the struggle has shifted to a new frontier—artificial intelligence. Nations are competing not just to innovate but to dictate the terms of how AI will be developed, governed, and deployed. The winner won’t just lead in technology; they’ll shape the future rules of economics, defense strategy, and even global education.

Calling it an “AI arms race” is no exaggeration. It has become a real geopolitical clash. The United States, China, and Europe are scrambling for influence, while countries like India, South Korea, and the UAE push to secure their place in this new order. The result is a rapidly intensifying tech cold war, where competition over governance and economic independence is at the core.

The Global AI Arms Race:

Artificial intelligence has moved far beyond digital assistants and recommendation engines. We’ve entered the era of autonomous AI, or “agentic AI,” where systems can operate with a degree of independence and make decisions without constant human oversight. This leap creates fresh opportunities—but also serious risks around ethics, accountability, and security.

United States: 

The U.S. remains home to some of the most influential AI players—OpenAI, Anthropic, and Google DeepMind. Washington backs these firms while imposing export restrictions on advanced chips to slow China’s progress.

China: 

Beijing is pouring billions into domestic AI research and semiconductor manufacturing. Its model is heavily centralized, combining state-backed funding with strict oversight and censorship.

Europe: 

Although behind in cutting-edge research, the EU has turned itself into a rule-setter. The EU AI Act aims to enforce accountability, transparency, and human-centric AI design.

Emerging economies: 

India, South Korea, and the UAE are nurturing their own AI ecosystems, while African nations are testing AI in agriculture, healthcare, and education, albeit with limited resources.

This contest isn’t only about building better algorithms—it’s about who embeds their values and political systems into the global AI landscape.

India’s Entry: From Consumer to Creator

India has long been seen as a provider of talent in the digital economy rather than as a global AI power. That narrative began to shift in 2025 when the country revealed its first fully indigenous microprocessor—the Vikram-32.

The Vikram-32 Breakthrough

▪️Unveiled at Semicon India 2025 and developed by ISRO’s Semiconductor Laboratory and Vikram Sarabhai Space Centre, the Vikram-32 (VIKRAM3201) marked India’s debut in designing its own advanced chip.

▪️Built to withstand extreme conditions such as radiation, high vibration, and wide temperature ranges, it has already been flight-tested on a PSLV mission, proving it’s space-ready.

▪️The processor supports floating-point computation, a custom instruction set, and Ada programming (with C support under development).

While designed for space missions, its durability makes it attractive for defense, automotive, and industrial applications.

This development signals India’s intent to reduce dependency on foreign chipmakers and carve out a place in the global semiconductor supply chain.

Strengths and Weaknesses

Strengths: India’s vast pool of engineers, a growing startup scene, and one of the world’s largest internet user bases provide fertile ground for AI adoption. Government programs like Digital India and Semicon India Mission add momentum.

Weaknesses: The country still lacks large-scale chip fabrication plants and trails far behind the U.S. and China in AI R&D funding. Its regulatory landscape remains underdeveloped compared to the EU’s.

The Road Ahead for India

For India to play a decisive role in the AI race, it must:

▪️Scale up semiconductor manufacturing through initiatives like the India Semiconductor Mission and production-linked incentives.

▪️Increase AI research funding and promote industry–university collaborations, building on models like IIT Madras’s SHAKTI processors.

▪️Establish balanced regulations—not overly restrictive, but strong enough to ensure trust and accountability.

Champion AI for social good, using it in agriculture, public health, disaster relief, and inclusive education to differentiate its approach from purely profit or control-driven models.

Strengthen diplomatic partnerships, particularly through platforms like the Quad and G20, positioning itself as a mediator between competing global blocs.

Governance Battles: Competing Models

The AI race isn’t only about who builds the most advanced systems. It’s also about who decides the rules under which those systems operate.

European Union: The EU AI Act categorizes AI tools by their risk level, imposing strict oversight on high-risk applications like facial recognition or recruitment software. The goal is trust, but critics worry about stifling innovation.

United States: Washington emphasizes innovation first, with minimal regulatory interference. While an executive order in 2023 outlined safety principles, the U.S. has avoided rigid laws in favor of market-driven development.

China: By contrast, Beijing requires AI models to reflect “core socialist values.” Generative AI is filtered for politically sensitive outputs, reflecting the government’s priority of state stability over individual rights.

The divergence among these frameworks risks splitting the AI world into separate regulatory zones—a “splinternet of AI.”

Tech Cold Wars: Chips, Data, and Corporate Proxies

Much of the U.S.–China standoff comes down to two things: hardware and data.

▪️Chips as leverage: Advanced GPUs, mostly from Nvidia and AMD, are the lifeblood of modern AI. The U.S. has tightened exports, aiming to choke off China’s supply. In response, China is accelerating local chipmaking projects.

▪️Data control: Liberal democracies generally allow cross-border data flows, while China maintains centralized, state-controlled datasets. This raises deep concerns about privacy and bias.

▪️Companies on the front line: U.S. firms like Microsoft and Google often align with national security objectives, while Chinese giants Baidu and Huawei serve as extensions of state policy.

This isn’t just a technological rivalry—it’s about economic and strategic dominance. Control over chips and data today could determine leadership in healthcare, education, defense, and more tomorrow.

Impact on Education and Work

The AI race has immediate consequences for classrooms and workplaces worldwide.

Classrooms Transformed

AI-powered tutors and adaptive platforms personalize learning. Students can now access lessons tailored to their pace and strengths. But this innovation comes with risks:

.Wealthier schools and nations adopt these tools first, creating a global education gap.

.Poorly designed AI risks reinforcing bias or misinformation.

Reskilling for Survival

AI threatens routine jobs but also creates demand for new skill sets: data analysis, coding, problem-solving, and ethical reasoning. Governments that invest in reskilling programs will keep their workforce relevant in the AI economy.

Education as Soft Power

Edtech is also a tool of influence. American companies promote creativity and innovation through their platforms, while Chinese tools prioritize state-approved content. For countries adopting them, AI learning tools carry the values of the exporting nation. India, by focusing on socially responsible AI, has a chance to stand apart in this contest.

Future Scenarios: Which Path Will the World Take?

The trajectory of the AI arms race could follow several paths:

Global Cooperation: Countries agree on international safety standards and use AI to address shared challenges like pandemics and climate change.

Escalating Conflict: Nations weaponize AI for cyberattacks and autonomous military systems. Export controls harden into digital protectionism.

Fragmented Stability: The most plausible outcome—separate AI ecosystems emerge (U.S., China, EU), but remain loosely connected through limited standards and trade.

India’s choices in chipmaking, governance, and global diplomacy will influence which of these scenarios prevails.

Conclusion: Who Controls Tomorrow?

The AI arms race isn’t just about smarter machines. It’s a competition over whose vision of the future becomes reality.

▪️Economically, AI promises to add trillions of dollars to global GDP.

▪️Politically, it could redraw the balance of global power.

▪️Socially, it risks widening inequality—or could help bridge it if applied inclusively.

With the launch of the Vikram-32 chip, India has taken its first step from being an AI consumer to becoming a potential AI producer. The next phase will depend on how fast it can scale hardware capacity, shape fair regulations, and use AI for the public good.

The race is on. The question isn’t whether AI will reshape the world—it’s who will decide how it reshapes it.

The insight review 

Upasna Sharma