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On 22 January 2026, Ikigai Law, in collaboration with the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), the Data Security Council of India (DSCI), and NASSCOM, launched the Handbook on Data Protection and Privacy for Developers of Artificial Intelligence (AI) in India. The Handbook serves as a practical guide to help AI developers navigate India's evolving data protection and responsible AI landscape.
The Handbook was developed under GIZ's FAIR Forward: AI for All initiative, and reflects a shared effort to translate legal and ethical principles into actionable guidance for developers, startups, and product teams building AI systems in India.
You can read the full Handbook here.
This post offers a snapshot of the Handbook, the process behind it, and why it matters.
About the Handbook
India's AI ecosystem is growing rapidly, from early-stage startups building sectoral AI tools to large companies deploying AI at scale across healthcare, finance, agriculture, and governance. At the same time, regulatory expectations around data protection, accountability, and responsible AI are becoming clearer, particularly with the enactment of the Digital Personal Data Protection Act, 2023 (DPDP Act) and the release of the DPDP Rules, 2025.
Yet, for many developers, compliance remains abstract, fragmented, and difficult to operationalise.
This Handbook was designed to bridge that gap.
Over several months, the Handbook was developed through a multi-stakeholder, iterative process that combined legal analysis with technical and operational inputs from across the ecosystem:
- Legal and policy research mapping India's data protection regime and global regulatory guidance on AI.
- Structured consultations with AI developers, startups, civil society organisations, researchers, and industry experts.
- Collaborative review with GIZ, DSCI, and NASSCOM to ensure relevance, usability, and technical accuracy.
- Real-world case studies contributed by practitioners building and deploying AI systems in high-impact contexts.
The outcome is a lifecycle-based guide that helps people developing and deploying AI to think through compliance and responsibility from design to deployment, not as an afterthought, but as part of how AI is built.
What the Handbook Covers
The Handbook is organised around the AI lifecycle (conception and design, development, and deployment) and is divided into two core sections:
- Data protection
This section unpacks how India's data protection law applies to AI development in practice, including:
- When data used for AI training qualifies as personal data
- How to identify a lawful basis for processing (consent or legitimate use)
- Using publicly available data and scraping data responsibly
- Anonymisation, pseudonymisation, and minimisation strategies
- Rights of individuals and organisational compliance measures
Rather than restating the law, the Handbook explains how developers can apply these rules in real workflows, especially when working with mixed datasets or continuously learning models.
- Responsible AI
The second section translates widely recognised responsible AI principles (specifically, fairness, transparency, accountability, and security) into practical design and governance choices that teams can make while building AI systems.
Each chapter, across both sections, is paired with examples and checklists to support decision-making under real constraints and make the advice actionable.
Learning from Real Systems: Case Studies
The annexures of the Handbook offer great value through five detailed case studies, which illustrate how teams navigate trade-offs such as privacy vs performance or personalisation vs data minimisation. An example of this that the Handbook delves into is how teams building AI for healthcare must decide how much personal data is truly necessary, often choosing to sacrifice a small degree of model accuracy to protect user privacy and reduce regulatory risk
These case studies show how developers make context-sensitive choices while still aligning with legal and ethical expectations. The aim is not to present perfect models, but to surface how responsible AI is practiced in the real world.
Why This Handbook Matters
As India positions itself as a global AI hub, the success of its ecosystem will depend not only on innovation, but also on trustworthy deployment.
Developers today are expected to internalise legal, ethical, and governance considerations, often without clear, accessible guidance. This Handbook responds to that gap by:
- Making compliance developer-readable, not just lawyer-readable;
- Embedding responsibility into design decisions, not just documentation;
- Supporting early-stage teams that lack dedicated legal or policy resources;
- Creating a shared reference point for industry, policymakers, and practitioners.
LookingAhead
The Handbook on Data Protection and Privacy for Developers of AI in India offers a clear and actionable baseline for responsible AI development in India today, grounded in current law, regulatory thinking, and real-world practice.
At Ikigai Law, we see this Handbook as a foundation for continued engagement with developers, regulators, and ecosystem partners to ensure that compliance, innovation, and responsible AI grow together.
We're grateful to GIZ, DSCI, and NASSCOM for their close collaboration, and to the many experts and practitioners who contributed their time and insights to this project.
Read the full Handbook here.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
