The Digital Personal Data Protection Act reframes how AI systems may ingest, retain and act on personal data. For teams running models at scale, three obligations dominate: lawful consent, purpose limitation, and the data-principal's right to correction and erasure.
Consent is now a pipeline concern
Consent can no longer be a checkbox captured once at onboarding. It must flow through every downstream model that touches the record, which means your feature store needs a consent lineage as rigorous as its data lineage.
Build the DPIA into the model lifecycle
A Data Protection Impact Assessment is most useful before a model ships, not after. Fold it into model validation so privacy risk is scored alongside performance and fairness.
DPDPPrivacyData Governance