Enterprise AI Governance & Compliance

This detailed syllabus for Enterprise AI Governance & Compliance is designed for high-stakes industries where "security is the product." It targets the Chief Risk Officer (CRO) and Data Privacy Officer (DPO) who need to move from fear-based blocking to architecture-based enablement.

Instructor-Led

40 hours

7 modules

Recommended Course Audience

Compliance Officers Data Privacy Officers and Legal IT Counsel

Pre-Required Skills

Cross-functional enterprise professionals bridging the gap between the Legal team
Compliance department
IT Security

Course Highlights

7 modules

The Shift from Static to Dynamic Governance: Why traditional RBAC fails in the age of Generative AI. The Solix Governance Fabric Architecture: Integrating compliance into the data ingestion layer rather than the application layer. Risk Assessment for LLMs: Identifying the Leakage Surface Area in RAG and Fine-tuning workflows.

Autonomous PII Hunting: Using ML-based discovery to find sensitive data in unstructured archives (PDFs, Images, Emails). Context-Aware Redaction: Difference between Hard Masking (Deletion) and Soft Masking (Tokenization) for AI training. Lab: Configuring the Solix discovery engine to identify HIPAA/GDPR sensitive strings across a multi-modal dataset.

Granular Data Scoping: Ensuring an AI Agent only sees the data the user is authorized to see. Tenant-Level Isolation: Preventing data leakage between different business units or geographic regions within a shared LLM. Zero-Trust AI Ingestion: Implementing the Verify-then-Feed protocol for high-security datasets.

Tracing the Digital Thread: Mapping an AI response back to the specific legacy record in the Solix archive. Managing AI Deletion Requests: How to handle GDPR Right to Erasure when data has already been used to train or ground a model. Provenance Metadata: Tagging data with source, timestamp, and sensitivity level before it enters the ML Flow.

Building the AI Black Box Log: Recording every prompt, retrieved context, and model output for regulatory review. Detecting Bias and Hallucination: Using observability tools to flag when AI output deviates from the Golden Source of truth. Audit-Ready Reporting: Generating one-click compliance reports for FINRA, HIPAA, or the EU AI Act.

Prompt Injection Defense: Architecting the Input Filter to prevent malicious users from bypassing safety controls. Output Sanitization: Ensuring the AI does not reveal internal trade secrets or protected PII in its conversational responses. Human-in-the-Loop (HITL) Workflows: Designing the approval process for high-risk AI decisions.

Resolve a high-profile AI hallucination, secure a leaking data pipeline, and satisfy a pending regulatory audit.

$699.00

This course is coming soon. Enrollment is not yet open.

Level : Intermediate

Modules : 7

Duration : 40 hours