Data Privacy Consulting for Operational Compliance and AI Data Governance
Data Privacy Consulting for Operational Compliance and AI Data Governance
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We build privacy programs that hold up in audits and day-to-day work. Scope includes GDPR and state privacy, ISO 27701 PIMS, data maps and records, DPIAs, retention and deletion, vendor risk, data subject rights, and AI data governance aligned to NIST AI RMF and ISO 42001.
Need a privacy and AI governance plan with metrics and evidence? Talk to a consultant
Why Privacy And AI Governance Matter In 2025
EU AI Act Dates
Banned practices and AI literacy from Feb 2, 2025. GPAI duties from Aug 2, 2025. Most rules apply Aug 2, 2026. High-risk in embedded products have until Aug 2, 2027.
CPPA Rules
California finalized new regulations in Sep 2025 with effective date Jan 1, 2026 and extra time for audits, risk assessments, and automated decisionmaking requirements.
State Laws
Nineteen US states have passed wide-scope privacy laws, raising the bar on notice, choice, and data rights.
Program Standards
ISO 27701 extends ISO 27001 for a PIMS, and ISO 42001 sets an AI management system baseline.
| Finding | Figure | Source |
|---|---|---|
| EU AI Act phased application dates | Feb 2025, Aug 2025, Aug 2026, Aug 2027 | European Commission |
| California CPPA final rules timeline | Finalized Sep 23, 2025, effective Jan 1, 2026 | CPPA |
| State privacy law landscape | 19 enacted state laws | IAPP overview |
| NIST AI RMF trustworthiness characteristics | Valid and reliable, safe, secure and resilient, accountable and transparent, explainable, privacy enhanced, and fair | NIST AI RMF 1.0 |
| GDPR principles guide program design | Lawfulness, fairness, transparency, purpose limitation, data minimisation, accuracy, storage limitation, integrity and confidentiality, accountability | GDPR Article 5 |
30-60-90 Program Build
First 30 Days: Map And Baseline
- Confirm scope across GDPR and key state laws. Publish owners and dates for records of processing, notices, and training.
- Build the data map and records of processing. Capture lawful basis, purpose limits, minimisation, retention, and special category flags.
- Stand up DPIA triage for high-risk processing and set a repeatable template.
- Start vendor inventory and standard data processing terms. Add risk and audit cadence.
Days 31 To 60: Implement Controls And Train
- Operate a PIMS aligned to ISO 27701 and link it to ISO 27001 controls. Track DSAR cycle time and deletion throughput.
- Roll out privacy by design defaults and templates for teams.
- For AI use cases, adopt NIST AI RMF functions and prepare ISO 42001 management routines. Add data lineage, consent or licensing checks, and dataset quality gates.
Days 61 To 90: Prove And Scale
- Run DPIAs on prioritized projects and close findings. Publish a monthly benefits and risk pack for executives.
- Prepare for CPPA items that start in 2026 with evidence for risk assessments, audits, and automated decisionmaking governance.
- Substantiate AI-related marketing claims. The FTC has acted against unsupported accuracy claims.
- Data Sourcing And Rights: consent or contract, licensing, or legitimate interest documented before model training or fine-tuning.
- Minimisation And Retention: limited features, masked or synthetic data where useful, and deletion schedules tied to purpose.
- Lineage And Provenance: dataset register, transformations, and provenance notes for audits.
- Access And Security: role-based access and logging tied to your ISMS.
- Evaluation And Drift: bias and privacy tests, red-team prompts, and monitoring after go live mapped to NIST AI RMF.
- Accountability: RACI for product, data, security, and legal with a review board for exceptions.
Workstreams, Moves, Metrics, References
| Workstream | Typical Moves | Metric | Reference |
|---|---|---|---|
| Program | ISO 27701 PIMS linked to ISO 27001; policy set; training and audits | Training coverage, audit closure rate | ISO 27701 |
| Lawful Basis And Notices | Records of processing, notice library, consent flows | Notice freshness, lawful basis coverage | GDPR Article 5 |
| DPIA And Risk | DPIA screening, templates, consultation steps | DPIAs completed, high-risk items mitigated | EU Commission DPIA |
| Vendor Management | DPA templates, security and privacy checks, monitoring | Vendors approved, re-assessment cadence | IAPP overview |
| AI Governance | NIST AI RMF functions with ISO 42001 routines | Use cases with lineage, tests, and owners | NIST AI RMF; ISO 42001 |
| US Rules In 2026 | Prep for CPPA audits, risk assessments, and automated decisionmaking controls | Evidence pack completeness | CPPA |
| Claims And Marketing | Substantiation files for AI-related claims | Claims with support on file | FTC enforcement |
Frequently Asked Questions
What Frameworks Should We Start With?
For privacy, use GDPR principles and ISO 27701 for a PIMS. For AI, use the NIST AI RMF functions and, where helpful, ISO 42001 to formalize management routines.
How Do GDPR And The EU AI Act Work Together?
GDPR covers personal data processing. The AI Act adds risk-based controls for AI systems with phased dates in 2025, 2026, and 2027. Privacy and AI governance should be built together so data rights and model controls match.
When Is A DPIA Required?
A DPIA is required in the EU for processing likely to pose high risk, including large-scale profiling and sensitive data. The ICO provides practical steps and templates.
Want An Audit-Ready Privacy Program And AI Governance? We can stand up the controls, run DPIAs, and set metrics and evidence with a ninety day plan.
Related Reading
- Cybersecurity & Data Privacy
- Regulatory Compliance Consulting Services That Reduce Risk And Speed Audits
- Management Consultants Fortifying Cybersecurity And Data Privacy Compliance
- Data Privacy And Cybersecurity Practice Group Launch
- Data Privacy And Cybersecurity Regulations: Introduction
- Data Privacy And Cybersecurity Tips
- Artificial Intelligence Consulting & GenAI Enablement
- Data & Technology Consulting To Modernize And Scale
Sources
- European Commission. EU AI Act application timeline. https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai
- California Privacy Protection Agency. Final regulations and timeline. https://cppa.ca.gov/announcements/2025/20250923.html
- IAPP. US state privacy laws overview and tracker. https://iapp.org/resources/article/us-state-privacy-laws-overview/ and https://iapp.org/resources/article/us-state-privacy-legislation-tracker/
- ISO. ISO/IEC 27701 PIMS and ISO/IEC 42001 AI management system. https://www.iso.org/standard/27701 and https://www.iso.org/standard/42001
- NIST. AI Risk Management Framework 1.0. https://nvlpubs.nist.gov/nistpubs/ai/nist.ai.100-1.pdf and overview https://www.nist.gov/itl/ai-risk-management-framework
- GDPR principles and data minimisation. https://gdpr-info.eu/art-5-gdpr/ and EDPS glossary entry on minimisation https://www.edps.europa.eu/data-protection/data-protection/glossary/d_en
- ICO. AI and data protection guidance and DPIA guidance. https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/artificial-intelligence/guidance-on-ai-and-data-protection/ and https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/accountability-and-governance/data-protection-impact-assessments-dpias/
- FTC. Enforcement on unsupported AI accuracy claims. https://www.ftc.gov/news-events/news/press-releases/2025/04/ftc-order-requires-workado-back-artificial-intelligence-detection-claims
About the Author
Aykut Cakir, Senior Partner and Chief Executive Officer, has a demonstrated history in negotiations, business planning, business development. He has served as a Finance Director for gases & energy, pharmaceuticals, retail, FMCG, and automotive industries. He has collaborated closely with client leadership to co-create a customized operating model tailored to the unique needs of each project segment in the region. Aykut conducted workshops focused on developing effective communication strategies to ensure team alignment with new operating models and organizational changes.
