Sovereignty vs Safety: Can India Shape the Future of Cross-Border AI?

As artificial intelligence scales across borders, a fundamental question is becoming unavoidable: who controls data flows, and who captures the value they generate?

The global AI race is no longer defined purely by innovation. It is increasingly about governance, sovereignty, compensation, and systemic risk. For countries like India, the stakes are not incremental; they are structural.

History offers a familiar pattern. Industries often scale faster than regulation. Pharmaceuticals operated with limited oversight before safety standards were enforced. Railroads and oil conglomerates expanded aggressively before antitrust frameworks emerged. Regulation did not kill these industries; it stabilised them.

AI appears to be approaching a similar inflection point.

Cross-Border Data as an Economic Fault Line

Today, AI systems largely developed in the US and China are being deployed across emerging markets. These systems ingest local data, automate services, and reshape workflows, often without equivalent domestic value capture.

For India, this raises hard economic questions.

If foreign AI systems automate segments of India’s IT and digital services workforce, where does the resulting value accrue? Does it remain within the domestic economy, or does it concentrate in offshore model providers?

This is not merely a technical issue. It is a question of digital economic sovereignty.

India may find it difficult to impose unilateral levies or compensation mechanisms on global AI firms. However, coordinated approaches, alongside other middle powers, could shift the balance. The European Union, Brazil, and South Korea are already experimenting with regulatory models that require upfront risk disclosures and compliance commitments before AI systems enter the market.

India could pursue a similar strategy: mandating pre-deployment disclosures on risk, mitigation plans, and safety protocols. Such measures would move governance upstream, from reactive damage control to proactive oversight.

Lessons from Social Media’s Regulatory Lag

The social media era offers a cautionary precedent. Internal research within major platforms reportedly flagged mental health and societal risks years before public scrutiny forced regulatory action. By then, addiction patterns, misinformation loops, and trust deficits were deeply entrenched.

AI presents a comparable moment, perhaps with higher stakes.

The question is whether India regulates AI at the point of deployment or waits until systemic harm becomes visible. Safety cannot remain an afterthought. It must become a licensing condition.

The Case for an “AI Zone”

An emerging idea among policymakers is the creation of a coordinated “AI zone”, a multinational framework for developing AI intentionally, rather than through scale-first experimentation.

The current model prioritises capability expansion first and governance later, mirroring early social media’s trajectory. But alternatives exist.

Researchers and safety advocates are exploring development paths that emphasise controllability, domain-specific utility, and built-in governance from inception. Instead of racing blindly towards frontier capabilities, coalitions of states could pool talent, infrastructure, and standards to build AI aligned with developmental priorities.

This reframes sovereignty.

Sovereignty does not require matching superpower scale at any cost. It can mean collaborating to set safety-first benchmarks that influence how frontier systems are built and deployed globally.

Speed, Safety, and the New Risk Equation

A deeper tension is now visible worldwide. Nations seeking sovereign AI capabilities often feel compelled to match the speed of US- and China-led development. But speed carries risk.

If advanced AI systems become opaque, self-improving, and globally embedded before adequate safeguards are in place, failures will not respect national borders. AI is no longer a garage-scale experiment; it is a multi-billion-dollar infrastructure layer shaping economies, defence systems, and public services.

Its risks demand industrial-scale governance.

Reconciling Sovereignty with Responsibility

The false binary between sovereignty and safety must be dismantled.

Sovereignty does not require recklessness. Safety does not require stagnation.

India, alongside other middle powers, can apply constructive pressure on frontier AI developers, demanding transparency, evaluation benchmarks, and enforceable compliance frameworks. Reactive regulation following major failures will be far costlier than proactive coordination.

The smarter path lies in coalition-building.

By aligning AI deployment with sustainable development goals, insisting on multilingual and culturally grounded systems, and embedding auditability into norms, India can help shape global standards rather than merely respond to them.

AI still holds transformative promise in healthcare, education, logistics, and governance. A high-impact future remains possible.

But only if nations resist the illusion that speed alone equals strength.

The next phase of AI will determine whether emerging economies remain data suppliers and application markets or become rule-makers in the intelligence economy.

Cross-border data flows are not just pipelines of information.
They are pipelines of power.

And how India responds now will shape its leverage in the AI economy for decades to come.