Artificial Intelligence (AI) has become an increasingly strategic tool for influencing a country’s geopolitical position on the global stage. India is the world’s fastest-growing major digital economy and the third-largest AI talent hub. It is at the crossroads of positioning itself between realizing its importance in AI governance and shaping the future landscape by encouraging AI innovations.
The Digital Personal Data Protection Act (DPDPA, 2023) laid the foundation of AI regulations. This legislation signals New Delhi’s intention to focus on developing AI safety frameworks to minimize the risks of excessive and unethical use. The term “responsible and inclusive AI” clarifies that India’s regulatory objective is not only risk reduction, but also the expansion of AI-led innovation systems.
In contrast, the European Union approved the first comprehensive AI legislation, the EU Artificial Intelligence Act, imposing stricter controls and penalties on high-risk systems. The United Kingdom has taken a middle path, balancing risk standards with an innovation-friendly environment. In this context, this article examines where India’s regulatory framework can align with the EU and UK models without compromising its innovation ecosystem and digital autonomy.
India’s AI Regulatory Framework
India’s AI regulatory framework rests on three pillars: innovation, inclusion, and digital sovereignty. Unlike the EU, India has emphasized a risk-based, innovation-first model that recognizes AI’s developmental potential across agriculture, health, public services, and financial inclusion.
India’s digital public infrastructure, from Aadhaar and UPI to DigiLocker, has demonstrated practical readiness for large-scale technological empowerment. With over 12 billion monthly digital transactions through UPI, India already operates one of the world’s most active digital ecosystems.
New Delhi remains deliberate in choosing its regulatory posture. Given concerns that stringent frameworks can dampen startup investment, India is calibrating governance in a way that reduces unethical AI use while preserving market momentum and strategic autonomy.
EU AI Act vs the UK’s AI Regulation
The EU and UK have adopted clearly different governance philosophies. The EU model relies on hard regulation with strict risk classification, broad compliance obligations, and severe penalties for non-compliance. The framework places safety and rights at the center, but can increase compliance burden for scaling startups.
The UK model is more principle-based and adaptive. The 2023 AI White Paper focuses on applying risk standards through existing sectoral regulators rather than immediately imposing one broad statutory regime. The UK objective is to regulate risk without suppressing innovation capacity.
India Between the EU and the UK
India is increasingly shaping a third pathway: regulate strategically while capturing AI-led growth potential. Its approach is closer to the UK in agility and co-regulation, but with stronger emphasis on developmental scale and public digital infrastructure.
At the same time, India is actively engaging the EU through frameworks like the Trade and Technology Council (TTC) on standards, secure infrastructure, and frontier technologies. Through G20 and GPAI, India also advocates an inclusive AI rulebook for the Global South, including multilingual access, affordability, and equitable data ecosystems.
Risks for India
India’s balancing strategy faces risks if global interoperability and domestic innovation are not calibrated together:
| # | Risk |
|---|---|
| 1 | Importing overly stringent external models could slow India’s projected AI growth trajectory. |
| 2 | Excessive compliance burden in compute-intensive generative AI could hinder cross-border data mobility and access to advanced cloud and GPU infrastructure. |
| 3 | Despite a large share of global AI talent, structural fragmentation and limited high-value pathways can weaken retention. |
| 4 | Over-alignment with Western frameworks may constrain India’s independent Global South positioning in AI strategy. |
Roadmap for Cooperation
With AI governance now central to India’s external technology engagements, India should calibrate, not copy. A practical cooperation roadmap can protect autonomy while strengthening interoperability:
| Areas of Cooperation | Actions / Steps |
|---|---|
| AI research and computing capabilities | Establish trilateral India-UK-EU compute corridors and shared GPU clusters. |
| AI safety | Build joint red-teaming and model evaluation hubs inspired by institutional safety labs. |
| AI for public good | Co-develop multilingual LLMs and low-resource language AI systems to support wider inclusion. |
| Regulatory interoperability | Develop compatible ethical AI benchmarks and risk standards while preserving domestic policy space. |
Conclusion
India stands at a critical point in global AI divergence. The EU highlights the urgency of strict safeguards against harmful applications. The UK demonstrates how innovation can be protected through agile principles. India cannot simply import either model wholesale.
A calibrated third model grounded in democratic governance, digital inclusion, and innovation-led public value can position India as a leading AI governance actor, especially for the Global South.
