AI & Data Companies

AI and data companies face risks that standard control sets often miss: prompt injection, sensitive information disclosure, model and data poisoning, supply-chain vulnerabilities, and excessive agent autonomy.

Our approach: Standard CCPA / CPRA readiness first. AI and data-specific hardening second. The advisory modules below are optional enhancements on top of mandatory controls.

Standard Controls vs. AI/Data Enhancements

Standard CCPA / CPRA Readiness

Mandatory controls required for compliance:

  • Logical access and privileged access
  • Change management
  • Incident response
  • Risk management
  • Vendor management
  • Backup and availability
  • Logging and monitoring
  • Confidentiality and privacy (where applicable)

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AI/Data Advisory Enhancements

Optional modules justified by AI-risk frameworks:

  • Data lineage and training data governance
  • Prompt/response telemetry
  • RAG and retrieval governance
  • Model/provider vendor review
  • Agent approval gates
  • AI-assisted SDLC controls
  • Warehouse and analytics governance

Advisory Modules

Each module adds specific controls and documentation practices to address risks unique to AI and data-intensive products.

AI-Assisted SDLC Controls

CCPA's data minimization and purpose limitation principles (§1798.100(c)) apply directly to AI systems that generate, infer, or collect personal information during the software development lifecycle.

What This Module Adds

  • Rules governing AI-generated personal information and inferred PI categories
  • Privacy review gates for automated PI collection introduced via AI features
  • Data minimization assessment for AI training data derived from consumer PI
  • Purpose limitation documentation for PI used in development, testing, and staging environments

Human Review & Agent Gates

CPRA's profiling provisions (§1798.185(a)(16)) and right to opt out of automated decision-making require human oversight when automated systems produce legal or similarly significant effects on consumers.

What This Module Adds

  • Human-in-the-loop checkpoints for AI decisions that affect consumer rights or access
  • Escalation procedures when automated processing impacts consumer PI access, pricing, or service availability
  • Documentation of automated decision logic for right-to-know response fulfillment
  • Consumer-facing disclosure of significant automated decision-making involving PI

Model/Provider Vendor Risk

CCPA service provider requirements (§1798.140(ag)) extend to AI model providers that process consumer PI, requiring written contracts restricting PI use and prohibiting secondary use of consumer data for model improvement.

What This Module Adds

  • AI model provider register with PI exposure assessment for each integration
  • Data processing agreement review for model providers covering PI retention and training exclusions
  • Contractual prohibition on model providers using consumer PI for model training without explicit authorization
  • Incident notification requirements for model provider PI breaches or unauthorized access

Prompt & Response Logging

CCPA's right to know (§1798.110) requires businesses to disclose the specific pieces of PI collected, which includes PI captured in AI prompt and response logs when those logs are retained.

What This Module Adds

  • Classification policy for prompt/response logs containing consumer PI
  • Retention limits on AI interaction logs aligned with data minimization requirements
  • Inclusion of AI interaction logs in right-to-know and deletion request scope
  • Access controls and encryption for prompt/response log storage

RAG & Vector Store Controls

Vector stores that embed consumer PI must comply with CCPA deletion rights (§1798.105) and purpose limitations, yet vector embeddings resist conventional record-level deletion.

What This Module Adds

  • PI classification for documents ingested into RAG pipelines
  • Deletion capability assessment for vector stores holding consumer PI embeddings
  • Purpose limitation controls restricting RAG queries to authorized use cases
  • Access controls on vector store query interfaces to prevent unauthorized PI retrieval

Training & Inference Data Governance

Using consumer PI for model training may constitute a 'business purpose' under §1798.140(e) requiring disclosure in the privacy notice, and repurposing PI collected for one purpose into training data may violate purpose limitation (§1798.100(c)).

What This Module Adds

  • Training data provenance documentation linking datasets to original collection purposes
  • Consumer notice disclosures when PI is used for model training or fine-tuning
  • Opt-out mechanism for consumers whose PI is used in training datasets
  • De-identification or aggregation requirements for PI incorporated into training data

Warehouse & Analytics Governance

Data warehouses that aggregate consumer PI across contexts must respect CPRA's cross-context behavioral advertising restrictions (§1798.140(k)) and the prohibition on combining PI from different sources without appropriate authorization.

What This Module Adds

  • Cross-context PI aggregation controls preventing unauthorized behavioral profiling
  • Warehouse-level access controls aligned with purpose limitation for each PI dataset
  • Automated PI retention enforcement within warehouse and analytics pipelines
  • Consumer rights fulfillment procedures covering warehouse-resident PI

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