India AI Impact Summit 2026 Convenes Global Leaders on Open Data Regulation; Panel Calls for "Structured Openness"
VMPL
New Delhi [India], February 23: The Cyril Shroff Centre for AI, Law and Regulation at Jindal Global Law School, O.P. Jindal Global University, in partnership with Cyril Amarchand Mangaldas, convened a high-profile panel titled "Exploring a Regulatory Framework for Open Data" at Bharat Mandapam as part of the India AI Impact Summit 2026.
Dr. Shashi Tharoor, Member of Parliament (Lok Sabha) for Thiruvananthapuram, delivered the keynote address, framing data governance as a question of power, sovereignty and value extraction and advocated for "structured openness", an approach that prioritises open data infrastructure while deliberately building guardrails and domestic capacity to prevent inequalities and external dependency.
Mr. Cyril Shroff, Managing Partner, Cyril Amarchand Mangaldas, argued for a statutory and regulatory open-data framework to overcome government data siloing and provide the legal certainty that fosters investor confidence, responsible innovation and market-led growth.
Ms. Rama Vedashree, former Chief Executive Officer, Data Security Council of India (DSCI), highlighted that India's open-data ecosystem often lacks machine-readability, rich metadata and interoperability, and that "open" must increasingly mean usable for AI and other advanced applications.
Dr. Sasmit Patra, Member of Parliament (Rajya Sabha), noted how a trusted, reliable data infrastructure is essential for evidence-based policymaking and cited AI-driven crop-loss prediction as a high-impact public-interest use case.
Speakers emphasised that open data must increasingly mean usable, and that datasets should be machine-readable, richly annotated, and provided through AI-ready public data infrastructure (APIs, interoperability standards, and reliable, scalable access) so they can safely power public-interest AI applications. The session concluded that a combination of enforceable law, technical standards and international cooperation will be central to a workable open-data regime suitable for the AI age.
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