AI Privacy & Data Protection
for GenAI Deployments
Your team adopted GenAI last quarter. Your privacy notices, data inventory, and risk assessments haven't caught up yet.
We close the gap between innovation speed and privacy readiness.
- Audit and manage privacy risks in AI training data and deployments
- Update privacy notices, data inventories, and risk registers for AI systems
- Build AI-ready policies that work with your existing privacy program
- Establish privacy-preserving practices for safe AI development
The AI Privacy Gap
AI moves faster than privacy programs. Here's what that gap looks like in practice.
Training Data Exposure
Personal data used to train AI models may include customer information, employee records, or regulated data — but it's not in your data inventory or risk register.
Privacy Notice Gaps
Your privacy notice was written before AI adoption. It doesn't disclose AI-based decision-making, automated processing, or how personal data feeds AI systems.
Deployment Risk Blindness
AI deployments introduce new processing purposes, data flows, and third-party integrations — but no privacy impact assessment was performed before launch.
Core AI Privacy Services
Four integrated services to bring your AI systems into your privacy program.
AI Training Data Audit
Identify and assess privacy risks in datasets used to train, fine-tune, or evaluate AI models.
- Personal data discovery in training datasets
- Data provenance and consent verification
- Re-identification risk assessment
- Data minimization and retention recommendations
AI Deployment Risk Assessment
Evaluate privacy implications before and after deploying AI systems in production.
- AI Privacy Impact Assessment (PIA)
- Data flow mapping for AI systems
- Third-party AI vendor assessment
- Automated decision-making disclosure requirements
AI-Ready Privacy Policies
Update privacy notices and internal policies to cover AI processing activities.
- Privacy notice updates for AI disclosures
- AI data use and acceptable use policies
- Consent frameworks for AI processing
- GDPR Article 22 compliance (automated decision-making)
Privacy-Preserving AI Development
Embed privacy into AI development lifecycle and establish safe development practices.
- Privacy-by-design framework for AI
- Data anonymization and synthetic data strategies
- AI model privacy controls and safeguards
- Developer training on privacy-preserving techniques
AI Privacy Regulatory Landscape
Multiple regulatory frameworks now address AI privacy risks. We help you navigate them.
GDPR Article 22
Automated decision-making and profiling restrictions require transparency and human review for significant decisions.
CCPA/CPRA (California)
Enhanced rights for automated decision-making, profiling disclosures, and opt-out requirements for AI processing.
EU AI Act
Risk-based framework for AI systems with transparency, data governance, and accountability requirements. (We provide practical guidance aligned with emerging requirements; we do not claim to certify AI Act compliance.)
NIST AI Risk Management
Framework for managing AI risks including privacy, transparency, and accountability considerations.
State AI Privacy Laws
Growing number of state laws (Colorado, Virginia, Connecticut) require AI impact assessments and disclosures.
Sector-Specific Rules
HIPAA, FCRA, and financial services regulations impose additional requirements on AI-based processing.
How AI Privacy Integrates with Your Program
AI privacy isn't a separate silo. It extends your existing NIST Privacy Framework program.
AI Governance & Security Integration
AI privacy works best when integrated with AI governance and security. Our ecosystem partners provide complementary services.
AI Governance
AI acceptable use policies, board reporting, strategic oversight, and risk-based AI adoption frameworks.
Ideal for establishing AI governance structure, oversight committees, and AI security controls.
→ Hudson Valley CISO
Shadow AI Discovery
Find unapproved AI tools and map actual AI use across your organization with operational discovery sprints.
Essential for understanding what AI is actually deployed before privacy assessment begins.
→ CyberIntelPro
Program Packages
Full AI security & privacy program packages coordinated across privacy, governance, and security operations.
Central hub for comprehensive AI program management.
→ Security Medic
Start with an AI Privacy Gap Analysis
In 30 minutes, we'll identify where your AI deployments create privacy exposure, outline regulatory requirements, and map a practical path to compliance.