IBM India Chief Praises India’s Balanced Approach to AI Regulation and Innovation

MUMBAI — India is pursuing a balanced approach to artificial intelligence regulation that protects users without discouraging innovation and investment, according to Sandip Patel, managing director of IBM India and South Asia.

Speaking on the sidelines of the IBM Think Mumbai 2026 conference Tuesday, Patel said India’s approach to AI governance recognizes the need for safeguards while allowing businesses to develop and deploy emerging technologies.

He expects that balance to continue as AI technology evolves, emphasizing that effective governance will become increasingly important as organizations expand their use of artificial intelligence.

“I think the bigger question that we should be asking ourselves is how do we drive digital sovereignty? And the issue of sovereignty, it’s not just an India issue; it’s global,” Patel said.

Patel described digital sovereignty as “Digital Swaraj,” emphasizing the importance of maintaining control over data, technology infrastructure and AI systems while complying with regulatory requirements.

“I think it’s important, both from an AI and infrastructure standpoint. You have to maintain a level of sovereignty that is aligned to the regulations that you are governed by as an enterprise, but also the kinds of workloads that you are, in fact, working with,” he said.

His comments come as the Indian government prepares to release a consultation paper on AI regulation, with an emphasis on safety, workforce development and addressing risks associated with deepfakes.

The proposed framework is also expected to focus on ensuring that advances in artificial intelligence benefit a broad range of society.

India’s Minister of Electronics and Information Technology, Ashwini Vaishnaw, has argued that legislation alone cannot adequately address the challenges posed by AI.

“We have to bring a techno-legal solution,” Vaishnaw said, emphasizing the need to combine regulatory oversight with technological safeguards.

Patel identified data governance, model governance and transparency as essential components of responsible AI development.

He said companies must understand where their data originates, verify its accuracy and ensure that information is being used appropriately.

“Model governance is also the key, which means what models are you using, when are you using it. Are you updating the models? Is your model relevant for what you are trying to use it for? Those are all questions that come into model governance,” Patel said.

Beyond managing data and AI models, Patel stressed the importance of transparency and the ability to explain AI-generated decisions.

“Do you have transparency in terms of how your models are being used by AI? What data are you using and all the rest of it. But most importantly, the explainability of outcomes. Can you explain your outcomes? Or are you letting your models hallucinate and do whatever they want?” he said.

These considerations, he explained, form the foundation of comprehensive AI governance systems designed to improve reliability and accountability.

Patel also highlighted growing corporate adoption of IBM’s AI governance technology, citing Indian technology services company Infosys as an example.

According to Patel, Infosys initially began developing its own AI governance framework but ultimately decided to adopt IBM’s watsonx governance platform after evaluating its capabilities.

“They had started to build their own governance model. When they saw what we had, they abandoned that, and they adopted our IBM watsonx.gov. And they are using it now, not only for internal work, but also for clients,” Patel said.

He added that adoption of IBM’s governance technology is expanding as organizations seek tools to manage AI systems responsibly.

Patel’s remarks underscore the growing importance of regulatory clarity, digital sovereignty and corporate accountability as India expands its artificial intelligence capabilities and positions itself as a major market for AI development and investment. (Source: IANS)