Privacy centric design treats privacy like product quality. Collect only what you need, explain it in plain English, and build consent and choice into the flow. This removes buyer friction, reduces complaints, and supports faster releases.

Map data flows for each AI use case. Choose a lawful basis. Minimize and pseudonymize training data. Explain when AI is in the loop. Honor data rights, secure training sets, and run DPIAs when risk is high or data is sensitive.