India's Ministry of Electronics and Information Technology (MeitY) launched the "Handbook on Data Empowerment and Protection Architecture (DEPA) for AI Training" on October 31, 2026. This framework aims to enable secure sharing of data from institutions like hospitals and banks for AI model training while strictly protecting privacy and intellectual property.
$500 billion
Projected AI-driven Value
⏳ Time Machine
How today’s news fits into the bigger picture
2017
Start of Data Protection Discussions
India began its journey toward a comprehensive data protection law, leading to later drafts and extensive public and industry discussions on data privacy.
August 2020
NITI Aayog Introduces Original DEPA
NITI Aayog initially introduced the Data Empowerment and Protection Architecture (DEPA) framework, focusing on consent-based individual data sharing for various services.
August 2021
Analysis of DEPA Framework
Observer Research Foundation published a brief dissecting DEPA's conceptual layers and assessing its potential for data empowerment and innovation in India.
2023
DPDP Act Passed
The Digital Personal Data Protection (DPDP) Act, 2023, was passed, laying the legal groundwork for comprehensive data privacy and protection in India.
October 2026
Key Principle Articulated for AI
Principal Scientific Adviser to the Government of India, Ajay Kumar Sood, highlighted that the framework would allow AI models to access data without requiring institutions to transfer the underlying information.
Today
India launched the DEPA framework to enable secure data sharing for AI model training.
What happens next?
The DEPA framework will undergo pilot programs and extensive consultations before full implementation, potentially influencing international AI data governance.
The Indian government, through the Ministry of Electronics and Information Technology (MeitY), introduced the "Handbook on Data Empowerment and Protection Architecture (DEPA) for AI Training" on October 31, 2026, in Bengaluru. This innovative framework is designed to facilitate the secure sharing of large datasets from various sources, including hospitals, banks, and public agencies, for the purpose of training Artificial Intelligence models. A central tenet of DEPA is to allow AI models to "travel to the data," rather than requiring the raw data to be transferred to the models, thereby safeguarding privacy and institutional control. The government anticipates that this framework has the potential to unlock a staggering **$500 billion in AI-driven value for India's GDP by 2030**, addressing crucial concerns around privacy, confidentiality, and intellectual property in AI development.
💭 If you're wondering…
Differential privacy is a system that allows researchers to learn as much as possible about a large dataset while minimizing the chances of identifying individual records within that dataset, thereby protecting individual privacy.
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