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Updated Oct 31, 2026 · 16:18
Computer News Updated Oct 31, 2026

MeitY launches DEPA handbook for secure AI data training

MeitY Secretary S. Krishnan launched the Handbook on Data Empowerment and Protection Architecture for AI Training in Bengaluru. The framework lets institutions share data for AI training while keeping control over privacy and intellectual property. Ajay Kumar Sood said the model travels to the data rather than the data travelling to the model.

MeitY launches DEPA handbook to enable secure data sharing for AI training

New Delhi, October 31

India's artificial intelligence ambitions could receive a boost through wider access to high-quality datasets, with the Union Ministry of Electronics and Information Technology launching a new framework to enable secure data collaboration while protecting privacy, intellectual property and institutional control.

The ministry on Saturday launched the Handbook on Data Empowerment and Protection Architecture (DEPA) for AI Training at a high-level roundtable in Bengaluru. The handbook was unveiled by S. Krishnan, Secretary, MeitY, with support from the iSPIRT Foundation.

The framework seeks to address challenges that often restrict data sharing, including concerns around privacy, confidentiality, intellectual property and institutional control. It establishes a techno-legal framework for purpose-bound data collaboration, allowing institutions to share data for AI training while retaining control over their information.

The framework combines contractual permissions, controlled computing environments and privacy-enhancing safeguards. It also incorporates data provenance, allowing the origin, permissions and use of data to be tracked throughout the AI training process to ensure accountability and transparency.

"India's AI ambitions must be matched by the ability to use data responsibly and securely. The DEPA Training Framework enables trusted data collaboration at scale, unlocking access to large-scale datasets for AI training while safeguarding privacy, commercial confidentiality and institutional control," Krishnan said.

Principal Scientific Adviser to the Government of India Ajay Kumar Sood highlighted that the framework allows AI models to access data without requiring institutions to transfer the underlying information.

"Under DEPA, the model travels to the data, rather than the data travelling to the model," Sood said, adding that the approach could facilitate trusted, multi-party and cross-border data collaboration and accelerate scientific discovery.

He described the framework as India's contribution to global science diplomacy and efforts to develop an inclusive and responsible global AI ecosystem.

Sharad Sharma, Co-founder of iSPIRT Foundation, described the launch as a significant milestone for India's data economy, comparing its importance with the announcement of the Unified Payment Interface (UPI) in February 2016.

Kris Gopalakrishnan, Co-founder of Infosys and Chairman of Axilor Ventures, said the framework could help researchers access diverse datasets to develop more robust AI models while protecting the rights of data custodians and contributors.

The roundtable brought together representatives from government, industry, technology, academia, research and media to discuss trusted data collaboration and its role in advancing AI innovation and public good.

— ANI

Reader’s Guide · AI-assisted, based only on the report above

What the report makes clear: A new government handbook sets out how institutions can share data for AI training while keeping control of it.

Still open: The report does not yet say when the framework takes effect or which institutions will adopt it first.

Another way to look at it: Easier data collaboration could widen access for researchers, while custodians weigh how much control they retain.

What safeguards would make you comfortable sharing data for AI training?

Reader Voices

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