DPIA Under the DPDP Act: Data Protection Impact Assessment Template

A Data Protection Impact Assessment (DPIA) is a structured review of how a specific processing activity affects the privacy of the people whose data is involved: what you collect, why, what could go wrong, and what safeguards address it. Under the DPDP Rules, a DPIA is a legal requirement specifically for Significant Data Fiduciaries, who must complete one annually alongside an audit [Rule 13(1)]. If you are not an SDF, nothing in the Rules obligates you to run one.

What a DPDP-aligned DPIA should cover

1. 1.Processing activity description. What data, what purpose, what system, and who within your company owns it.
2. 2.Necessity and proportionality. Does this processing activity need all the data it collects, or could the same purpose be served with less? [§8(3) purpose limitation]
3. 3.Data flow mapping. Where the data originates, where it is stored, which vendors or processors touch it, and whether it crosses outside India.
4. 4.Consent basis. Which specific consent covers this processing, and whether it is itemised separately from other purposes [§6].
5. 5.Retention and erasure. The specific retention period for this data category and how erasure is executed when the period ends [Rule 8].
6. 6.Security safeguards. Encryption, access controls, and logging in place for this specific data flow [Rule 6].
7. 7.Risk assessment. What is the realistic harm to a Data Principal if this data is exposed, misused, or retained too long, and how severe is that harm.
8. 8.Mitigations and residual risk. What you are doing about the risks identified, and what risk remains even after mitigation.
9. 9.Review date and owner. A DPIA is a snapshot. Assign a named owner and a re-review date, especially before launching a new feature that changes the data flow.

A worked example

Say you are adding a feature that shares customer order history with a third-party AI vendor to generate personalised recommendations. A DPIA for this feature would document: the specific data fields shared, that this is a new purpose requiring its own itemised consent (not covered by your general terms of use), that the vendor is contractually bound to the same retention period as your primary system, and that the realistic risk is profiling-based harm if the vendor's security is weaker than yours. This is close to the exact gap we found in our Swiggy teardown's AI data-sharing clause.

Why a document is not the finish line

A DPIA answers the question "is this safe?" for one point in time. The moment you ship a new integration, change a vendor, or add a data field, the assessment is stale. Significant Data Fiduciaries are required to redo the exercise annually for exactly this reason. Treat a DPIA as the audit-ready artifact your accountability programme produces continuously, not a Word document filled once and filed away.

This is the gap between a template and a system: Privacy Labs generates DPIA-equivalent documentation automatically from your live data map, so it stays current every time your data flows change instead of going stale the week after you write it. Pair this with a RoPA to inventory every processing activity, or see the full DPDP compliance checklist for where a DPIA fits in the bigger picture. Run a free Compliance Score below to see where your current data flows stand.