A tailored course, built for your situation
Tailored AI Governance & Compliance Course for Legal Counsel
A 12-module system to lead AI-driven privacy and compliance with confidence
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
You’re trusted to protect data, but AI moves faster than policy. Without a clear framework, you risk being reactive instead of leading.
The situation this course is for
Legal and privacy leaders like you are expected to govern emerging tech while maintaining compliance under evolving regulations. The pressure to deliver fast, airtight decisions, on AI contracts, data flows, and risk assessments, is intensifying. Generic training doesn’t cut it. You need actionable, jurisdiction-aware methods that align with your CIPP/E and CIPM expertise and build on your ISO 27005 foundation.
Who this is for
Solutions-focused legal counsel with AI and data privacy specialization, certified in CIPP/E and CIPM, experienced in risk frameworks like ISO 27005, operating at the intersection of law, technology, and compliance.
Who this is not for
Entry-level privacy officers without decision authority, developers seeking technical AI build guides, or compliance teams looking for video lectures instead of implementable frameworks.
What you walk away with
- Lead AI governance initiatives with structured, defensible frameworks
- Draft and negotiate AI-related contracts using proven templates
- Apply GDPR and CIPM principles to emerging AI use cases
- Build audit-ready compliance documentation aligned with ISO 27005 logic
- Reduce review cycles by applying standardized risk assessment playbooks
The 12 modules (with all 144 chapters)
Module 1. AI Governance Foundations
Establish the legal and operational pillars of AI governance, tailored to privacy-first jurisdictions. Understand how AI intersects with existing compliance mandates and where risk concentrates in deployment lifecycles.
12 chapters in this module
- AI definition tiers
- Legal vs ethical risk
- Jurisdiction mapping
- Compliance overlap zones
- Risk ownership models
- Policy enforcement gaps
- Audit triggers
- Third-party exposure
- Incident response links
- Data provenance tracking
- Model lifecycle stages
- Governance maturity levels
Module 2. AI Contracting Essentials
Master the core clauses needed in AI vendor agreements. Focus on liability, data usage rights, model transparency, and exit rights, structured to align with GDPR and CIPM standards.
12 chapters in this module
- Scope definition traps
- Data licensing terms
- Model ownership clauses
- Output rights framework
- Transparency obligations
- Audit access rights
- Liability caps design
- Subprocessor rules
- Exit data return
- IP carveouts
- Performance guarantees
- Breach notification terms
Module 3. Data Privacy in AI Systems
Apply GDPR and CIPM principles to AI data flows. Learn how to map consent, lawful basis, and data subject rights across training, inference, and logging layers.
12 chapters in this module
- Consent in training data
- Lawful basis alignment
- Subject access workflows
- Right to explanation
- Data minimization tactics
- Anonymization thresholds
- Purpose limitation checks
- Cross-border data rules
- Processor agreements
- Data protection impact
- Bias disclosure duty
- Retention boundaries
Module 4. Risk Assessment Integration
Adapt ISO 27005-style risk logic to AI-specific threats. Build repeatable assessments that integrate with existing compliance workflows and audit cycles.
12 chapters in this module
- Threat modeling setup
- Asset inventory mapping
- Likelihood calibration
- Impact scoring matrix
- Risk register structure
- Control effectiveness
- Residual risk thresholds
- Third-party risk inputs
- Scenario stress tests
- Risk acceptance criteria
- Escalation protocols
- Review cadence design
Module 5. AI Audits and Compliance
Prepare for internal and external AI audits with documentation frameworks that satisfy regulators and internal stakeholders. Focus on evidence trails and defensible decisions.
12 chapters in this module
- Audit scope definition
- Evidence collection plan
- Compliance checklist build
- Documentation standards
- Version control needs
- Stakeholder alignment
- Findings response protocol
- Remediation tracking
- Regulator communication
- Internal reporting format
- External assessor prep
- Audit closure steps
Module 6. Model Transparency and Explainability
Deliver legally sound explanations of AI decisions without compromising IP. Balance transparency obligations with commercial protection needs.
12 chapters in this module
- Explainability tiers
- Stakeholder needs mapping
- Simplified output reports
- Technical documentation
- Bias assessment summary
- Confidentiality boundaries
- User-facing disclosures
- Regulator-ready dossiers
- Model card standards
- Performance metrics
- Drift detection alerts
- Human oversight links
Module 7. AI Incident Response
Build an incident playbook specific to AI failures, bias, drift, hallucination, or data leakage. Align with existing DPO and security team workflows.
12 chapters in this module
- Incident classification
- Detection triggers
- Response team roles
- Containment steps
- Notification timelines
- Regulatory reporting
- Public statement prep
- Root cause analysis
- Remediation tracking
- Escalation paths
- Post-mortem process
- Update deployment
Module 8. Bias and Fairness Compliance
Implement fairness assessments that meet legal expectations. Use structured methods to detect, document, and mitigate bias in AI systems.
12 chapters in this module
- Bias definition framework
- Protected attribute handling
- Disparity measurement
- Fairness metrics selection
- Audit sampling method
- Documentation standards
- Remediation options
- Stakeholder review
- Third-party validation
- Bias disclosure
- Ongoing monitoring
- Performance tradeoffs
Module 9. AI and Cross-Border Data Flows
Navigate international data transfers in AI systems. Apply GDPR SCCs and other mechanisms to model training and inference across regions.
12 chapters in this module
- Data flow mapping
- SCC clause integration
- Adequacy decision checks
- Model hosting locations
- Inference geography
- Data residency rules
- Vendor location risks
- Encryption standards
- Access request handling
- Regulator notification
- Data localization costs
- Exit planning
Module 10. AI in HR and Employment
Govern AI tools used in hiring, performance, and termination. Ensure compliance with labor laws and data protection standards.
12 chapters in this module
- Candidate consent
- Bias screening
- Decision logging
- Human review mandate
- Transparency to employees
- Data retention limits
- Audit rights
- Union consultation
- Legal counsel review
- Impact assessment
- Vendor oversight
- Remediation path
Module 11. AI Vendor Oversight
Establish vendor management practices for AI providers. Focus on due diligence, ongoing monitoring, and exit readiness.
12 chapters in this module
- Due diligence checklist
- Security certification review
- Compliance audit rights
- Performance monitoring
- Change management
- Exit data return
- Subprocessor tracking
- Incident response coordination
- Contract renewal prep
- Risk reassessment
- Transparency reporting
- Termination triggers
Module 12. Scaling AI Governance
Turn individual wins into organization-wide governance. Build frameworks that grow with AI adoption and maintain compliance at scale.
12 chapters in this module
- Governance committee
- Policy standardization
- Training rollout
- Tooling integration
- Compliance dashboards
- Audit automation
- Stakeholder reporting
- Escalation workflows
- Feedback loops
- Continuous improvement
- Maturity benchmarking
- Board reporting
How this maps to your situation
- You’re drafting an AI vendor contract and need enforceable clauses
- You’re assessing risk in a new AI use case and need a structured approach
- You’re preparing for an internal audit on AI compliance
- You’re explaining AI decisions to stakeholders without technical background
Before vs. after
Before
Uncertain about how to apply your privacy expertise to fast-moving AI projects, relying on fragmented guidance and reactive decisions.
After
Confidently leading AI governance with structured, compliant frameworks that align with your CIPP/E, CIPM, and ISO 27005 experience.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3 hours per module, designed for busy professionals to complete one module per week.
If nothing changes
Without a tailored approach, you risk falling behind on AI compliance expectations, leading to avoidable audits, contract delays, or regulatory scrutiny, despite your strong foundation.
How this compares to the alternatives
Unlike generic compliance courses, this program builds directly on your CIPP/E, CIPM, and ISO 27005 background, delivering targeted, implementable frameworks for AI governance, not theory, but tools you can use immediately.
Frequently asked
Is this course technical or legal?
It’s designed for legal and compliance professionals. No coding required, just clear, actionable frameworks for governing AI systems.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I use this with my existing compliance toolkit?
Yes. Templates and playbooks are designed to integrate with ISO 27005, GDPR, and CIPM workflows.
$199 one-time. Approximately 3 hours per module, designed for busy professionals to complete one module per week..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours