A tailored course, built for your situation
Enterprise-Class Generative AI Policy Design for Regulated Industries
Build compliant, auditable, and scalable AI governance frameworks for high-regulation environments
$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.
Lack of standardized, enterprise-grade AI policy leaves regulated organizations exposed to compliance gaps and audit findings
The situation this course is for
As generative AI use expands across departments, existing governance frameworks are too vague or reactive. Without structured policy design tailored to regulated environments, organizations face inconsistent enforcement, compliance drift, and reputational risk during audits or reviews.
Who this is for
Compliance officers, risk managers, AI governance leads, and technology executives in finance, healthcare, legal, and other highly regulated sectors who need to implement defensible, board-ready AI policies
Who this is not for
Individual contributors without governance authority, startups in unregulated spaces, or those seeking only high-level AI awareness training
What you walk away with
- Design AI policies aligned with NIST, ISO, and sector-specific regulatory expectations
- Implement audit-ready documentation and control workflows
- Map AI use cases to risk tiers and compliance obligations
- Integrate human-in-the-loop and escalation protocols across business units
- Operationalize ongoing monitoring and policy evolution cycles
The 12 modules (with all 144 chapters)
Module 1. Foundations of Enterprise AI Governance
Establish core principles, regulatory touchpoints, and organizational alignment models
12 chapters in this module
- Defining enterprise AI policy scope
- Regulatory landscape overview
- Stakeholder mapping
- Policy vs. procedure distinctions
- Governance maturity models
- Risk taxonomy for AI systems
- Cross-functional collaboration models
- Board-level reporting structures
- Ethical AI principles integration
- Policy lifecycle management
- Integration with existing compliance programs
- Use case prioritization frameworks
Module 2. Regulatory Alignment Frameworks
Map AI policies to current standards from NIST, ISO, SEC, HIPAA, and GDPR
12 chapters in this module
- NIST AI RMF integration
- ISO 42001 alignment strategies
- SEC disclosure requirements
- HIPAA and AI-driven health tools
- GDPR and automated decision-making
- Jurisdictional overlap challenges
- Regulator engagement protocols
- Compliance-by-design workflows
- Documentation for external reviewers
- Third-party model risk assessment
- Audit trail requirements
- Cross-border data flow implications
Module 3. Risk-Tiered Policy Architecture
Classify AI applications by impact level and apply differentiated governance
12 chapters in this module
- High-risk system identification
- Medium-risk control frameworks
- Low-risk monitoring protocols
- Dynamic reclassification triggers
- Human oversight thresholds
- Escalation pathways for edge cases
- Model drift detection integration
- Incident response integration
- Bias mitigation expectations by tier
- Transparency requirements scaling
- Data lineage expectations
- Vendor AI usage oversight
Module 4. Policy Implementation Workflows
Operationalize governance through cross-functional playbooks and tooling
12 chapters in this module
- AI use case registration process
- Pre-deployment review checklist
- Stakeholder sign-off workflows
- Change control integration
- Model inventory management
- Version control for AI assets
- Access control frameworks
- Monitoring dashboard design
- Automated policy compliance alerts
- Periodic review cycles
- Training validation requirements
- Decommissioning protocols
Module 5. Audit-Ready Documentation
Produce defensible, standardized records for internal and external reviewers
12 chapters in this module
- Policy documentation standards
- Control evidence collection
- Versioned policy archives
- Decision rationale logging
- Model card integration
- System card generation
- Compliance assertion templates
- External auditor coordination
- Regulatory submission packages
- Internal audit preparation
- Documentation automation tools
- Redaction and confidentiality handling
Module 6. Cross-Functional Enforcement
Embed policy adherence into engineering, legal, HR, and operations
12 chapters in this module
- Legal team integration
- HR policy alignment
- Engineering team onboarding
- Procurement vetting workflows
- Sales and marketing guardrails
- Customer service boundaries
- Finance use case controls
- Third-party vendor oversight
- Incident reporting escalation
- Enforcement tracking metrics
- Remediation workflows
- Disciplinary action frameworks
Module 7. Model Provenance and Lineage
Track AI system origins, dependencies, and evolution across lifecycle
12 chapters in this module
- Training data sourcing logs
- Model version tracking
- Fine-tuning provenance
- Prompt engineering documentation
- Third-party model attribution
- Data preprocessing records
- Feature lineage mapping
- Model dependency graphs
- Reproducibility standards
- Chain-of-custody protocols
- External audit trail access
- Version rollback procedures
Module 8. Human-in-the-Loop Design
Define oversight roles, review thresholds, and escalation triggers
12 chapters in this module
- Critical decision points
- Review frequency by risk tier
- Human override mechanisms
- Escalation path design
- Fallback process documentation
- Reviewer qualification standards
- Training requirements for overseers
- Performance monitoring of human reviewers
- Bias detection triggers
- Disagreement resolution protocols
- Audit logging of human actions
- Continuous improvement feedback loops
Module 9. Continuous Monitoring and Evolution
Maintain policy relevance through ongoing assessment and updates
12 chapters in this module
- Performance drift detection
- Bias monitoring over time
- Regulatory change tracking
- Quarterly review cadence
- Stakeholder feedback integration
- Incident-driven policy updates
- Model retirement reviews
- New use case intake process
- External benchmarking
- Industry trend monitoring
- Policy sunset criteria
- Version comparison tools
Module 10. Third-Party and Vendor Oversight
Extend policy controls to external AI providers and partners
12 chapters in this module
- Vendor risk classification
- Contractual compliance clauses
- Third-party audit rights
- Model transparency requirements
- Data handling assurances
- Subprocessor oversight
- Performance SLAs for AI services
- Incident notification expectations
- Compliance certification verification
- Penalty enforcement mechanisms
- Exit strategy documentation
- Ongoing vendor monitoring
Module 11. Sector-Specific Policy Adaptation
Tailor frameworks for finance, healthcare, legal, and government use
12 chapters in this module
- Finance: credit decisioning rules
- Healthcare: diagnostic support controls
- Legal: discovery and confidentiality
- Government: public records access
- Insurance: underwriting fairness
- Education: student data handling
- Energy: safety-critical systems
- Transportation: operational risk
- Retail: consumer data use
- Telecom: network automation
- Pharma: research integrity
- Nonprofit: donor privacy
Module 12. Board-Level Readiness and Reporting
Prepare executive summaries, risk dashboards, and governance updates
12 chapters in this module
- Board reporting frequency
- Risk exposure summaries
- Incident trend reporting
- Compliance status dashboards
- Budget implications of AI risk
- Strategic alignment documentation
- Escalation to board level
- Crisis communication planning
- External relations coordination
- Reputation risk management
- Board training on AI policy
- Success metrics for governance
How this maps to your situation
- Organizations adopting generative AI without formal policy frameworks
- Teams preparing for regulatory audits or compliance reviews
- Leadership seeking to standardize AI governance across divisions
- Compliance officers responding to new regulatory scrutiny
Before vs. after
Before
Fragmented, reactive AI governance with inconsistent enforcement and audit exposure
After
Structured, defensible policy framework with clear ownership, controls, and compliance evidence
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 45, 60 hours of structured learning, designed for busy professionals to complete at their own pace over 6, 8 weeks.
If nothing changes
Continuing with ad-hoc AI governance increases exposure to regulatory findings, audit failures, and reputational incidents that undermine stakeholder trust.
How this compares to the alternatives
Unlike generic AI ethics courses or vendor-specific training, this program delivers implementation-grade policy design tailored to regulated environments, with templates and workflows that align directly with NIST, ISO, and sector-specific requirements.
Frequently asked
Who is this course designed for?
Compliance officers, risk managers, AI governance leads, and technology executives in regulated industries who need to build defensible, auditable AI policies.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is there a money-back guarantee?
Yes, a 30-day money-back guarantee is included.
$199 one-time. Approximately 45, 60 hours of structured learning, designed for busy professionals to complete at their own pace over 6, 8 weeks..
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