India's AI Strategy: A Data-Driven Dance

India's approach to artificial intelligence (AI) is more than just regulating a new technology; it's a carefully orchestrated dance between technological innovation, data governance, and national sovereignty.

At the heart of this dance lies a data-driven vision, one that isn't entirely new to India. Since the Atal Bihari Vajpayee government, India has envisioned a digital-first, data-driven governance model, akin to an "informational highway" delivering seamless services to citizens. Early endeavors like the Aadhaar project laid the groundwork, navigating privacy concerns and constitutional boundaries while proving the potential of data-centric governance.

With growing confidence and judicial support, India is doubling down on this data-driven model. The Digital Personal Data Protection Act, which allows public data to be used for AI model training, is a testament to this commitment. Moreover, India is investing heavily in data centers, chip manufacturing, and hardware infrastructure, effectively constructing the foundation for a data-powered future.

A cornerstone of this strategy is data localization – the principle of keeping data within the country's borders. This not only ensures sovereignty and accountability but also strengthens regulatory control. While early attempts focused on regulating internet gatekeepers, the limited success of this approach led to a shift towards a more sectoral strategy. Today, India mandates data localization in critical sectors like finance, geo-spatial data, and healthcare.

Interestingly, AI itself isn't the primary target of regulation. Instead, AI is viewed as a catalyst for achieving data localization goals. By minimizing human intervention in data processing, modern AI can actually reduce privacy concerns. Take robotic vacuums as an example: what was once a privacy concern due to human data collection is now resolved through autonomous AI cataloging.

Looking ahead, India's AI regulation will evolve. Robust institutional frameworks will be essential, with standard-setting bodies and government approvals playing key roles, particularly in high-risk public sectors. As data localization progresses, regulations will become more narrowly tailored, focusing on specific datasets rather than AI tools themselves.

The path forward isn't without challenges. Striking the right balance between promoting innovation and managing risk will be an ongoing process. However, India's approach demonstrates a clear understanding that AI is not just a technological tool but a strategic asset. By integrating data localization with robust infrastructure, India is creating a controlled, accountable data environment where AI can thrive. Self-regulation will continue to play a role, but India recognizes, much like the 2008 financial crisis exposed the dangers of relying solely on credit rating agencies, that self-regulation alone is not sufficient for long-term success.

India's AI governance strategy is a testament to its nuanced understanding of the challenges and opportunities that AI presents. It's a strategy that prioritizes not just the technological potential of AI, but also its societal impact. By carefully choreographing a dance between data localization, infrastructure development, and technological innovation, India is paving the way for a data-driven future that is both innovative and accountable.

About the author: Aasish Somasi is an Associate Partner at SNG & Partners.

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