Point of view
AI Governance & Risk
Data privacy
Privacy-by-design for AI and analytics, including data minimization, consent and cross-border considerations.
Overview
AI and analytics depend on data, and much of that data relates to people. Obligations under laws such as GDPR, HIPAA and US state privacy laws apply throughout the lifecycle, from collecting training data to generating outputs. Getting privacy right early avoids costly redesigns and protects trust.
We help teams apply privacy-by-design to AI and analytics initiatives. That includes data protection impact assessments for higher-risk processing, data minimization and purpose limitation, de-identification and pseudonymization, consent and lawful basis analysis, and retention rules. For generative AI, we address specific risks such as personal data in prompts and training sets, model memorization and data shared with third-party model providers.
We also support cross-border considerations for organizations operating across regions, including data residency and transfer mechanisms. Our role is to translate requirements into practical technical and process controls, working alongside your privacy office and legal counsel, who remain responsible for legal interpretation.
What you receive
- 01Privacy risk assessment for AI and analytics initiatives
- 02Support for data protection impact assessments
- 03Privacy-by-design requirements and technical controls
- 04De-identification and data minimization approach
- 05Guidance on personal data in generative AI solutions
Technologies we work with
- OneTrust
- Microsoft Purview
- BigID
- Microsoft Presidio
- Data masking and tokenization tools
- In-tenancy model endpoints and private networking
We are technology-agnostic: tools are chosen to fit your requirements and existing investments.
Questions we often hear
Can we use personal data to build AI systems?
Often yes, with the right lawful basis, safeguards and minimization. We help identify what data is genuinely needed and which techniques, such as pseudonymization or synthetic data, can reduce risk, while your legal counsel confirms the legal position.
Is it safe to send personal data to external AI model providers?
It depends on the provider terms, data location, contractual protections and the sensitivity of the data. We assess these factors and design options such as redaction, in-tenancy endpoints or self-hosted models where needed.
Insights
Related thinking
Let’s build what’s next, together.
Tell us about your goals. We’ll connect you with the right experts, usually within one business day.