A tailored course, built for your situation
Deeper command of AI governance frameworks
Master the architecture, controls, and compliance layers shaping modern insurance AI systems
$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.
Who this is for
Senior governance practitioner in a regulated financial services environment leading AI oversight initiatives
Who this is not for
Individuals looking for introductory AI ethics content or high-level trend summaries
What you walk away with
- Confidently structure AI governance frameworks aligned to ISO/IEC 42001 and internal audit expectations
- Deploy control mappings that stand up to regulator-facing review cycles
- Adapt governance patterns rapidly when new AI vendors or use cases emerge
- Produce audit-ready documentation the first time, without revision loops
- Lead cross-functional discussions with concrete examples and enforceable standards
The 12 modules (with all 144 chapters)
Module 1. Foundations of AI Governance in Insurance
Establish core principles specific to AI use in underwriting, claims, and customer service systems within regulated environments.
12 chapters in this module
- What AI governance means in insurance
- Difference between ethics and controls
- Regulatory expectations today
- Internal audit thresholds
- Vendor risk tiers
- Policy vs standard scope
- Roles in governance workflow
- Decision logs and traceability
- Incident escalation paths
- Model lifecycle stages
- Documentation benchmarks
- Compliance debt tracking
Module 2. Control Mapping to Frameworks
Translate high-level standards like ISO 42001 into operational controls mapped to specific AI system components.
12 chapters in this module
- ISO 42001 clause interpretation
- Mapping controls to data flows
- Control ownership definition
- Automated vs manual checks
- Sampling frequency logic
- Evidence collection design
- Control overlap reduction
- Crosswalk with NIST AI RMF
- Third-party attestation paths
- Control maturity scoring
- Exception handling process
- Audit trail preservation
Module 3. AI Risk Assessment Execution
Conduct repeatable, defensible risk assessments for new AI deployments using standardized scoring and documentation.
12 chapters in this module
- Risk domain categorization
- Harm likelihood scoring
- Impact severity bands
- Stakeholder sensitivity matrix
- Data provenance checks
- Bias testing triggers
- Explainability thresholds
- Human oversight design
- Red teaming scope
- Risk register structure
- Risk treatment options
- Escalation criteria
Module 4. Policy Design and Enforcement
Create enforceable AI policies with clear applicability, monitoring mechanisms, and compliance verification steps.
12 chapters in this module
- Policy scoping rules
- Trigger-based applicability
- Monitoring mechanism design
- Compliance verification cycle
- Remediation workflows
- Version control process
- Deviation approval path
- Training alignment
- Audit integration
- Stakeholder feedback loop
- Policy decay detection
- Enforcement dashboards
Module 5. Vendor Governance Integration
Extend governance to third-party AI providers with contractual levers, technical assurances, and monitoring requirements.
12 chapters in this module
- Vendor risk classification
- Contractual control clauses
- Right-to-audit terms
- Security questionnaire design
- Technical validation steps
- Performance benchmarking
- Subprocessor tracking
- Compliance attestation
- Onboarding checklists
- Ongoing monitoring rhythm
- Exit contingency planning
- Joint incident response
Module 6. Audit Readiness and Documentation
Produce complete, consistent, and defensible audit packages for internal and external reviewers.
12 chapters in this module
- Audit scope definition
- Evidence packaging format
- Control mapping presentation
- Exception documentation
- Timeline alignment
- Cross-reference indexing
- Executive summary drafting
- Gap analysis discipline
- Remediation tracking
- Peer review checklist
- Version control logging
- Secure delivery method
Module 7. Incident Response and Escalation
Define clear protocols for identifying, triaging, and resolving AI-related incidents with proper oversight and documentation.
12 chapters in this module
- Incident definition criteria
- Detection mechanisms
- Triage workflow design
- Severity classification
- Escalation path definition
- Cross-functional roles
- Containment procedures
- Root cause analysis
- Remediation tracking
- Regulatory notification
- Lessons learned process
- Prevention updates
Module 8. Change Management and Adaptation
Implement structured processes for updating governance as AI systems, regulations, or business needs evolve.
12 chapters in this module
- Change trigger identification
- Impact assessment method
- Stakeholder consultation
- Policy update workflow
- Control adaptation rules
- Training refresh cycle
- Communication plan
- Version migration path
- Legacy system handling
- Feedback integration
- Change validation
- Compliance monitoring
Module 9. Cross-Functional Alignment
Align legal, risk, IT, and business teams around shared AI governance expectations and responsibilities.
12 chapters in this module
- Stakeholder identification
- Role clarity mapping
- Communication rhythm design
- Conflict resolution path
- Shared terminology
- Decision authority chart
- Escalation coordination
- Joint review meetings
- Feedback integration
- Alignment metrics
- Conflict documentation
- Governance ambassador
Module 10. Metrics and Reporting
Design meaningful KPIs and dashboards that reflect true governance effectiveness to leadership and auditors.
12 chapters in this module
- Metric selection criteria
- Compliance rate tracking
- Risk exposure trends
- Audit finding resolution
- Control effectiveness
- Incident frequency
- Policy adherence rate
- Training completion
- Vendor compliance rate
- Dashboard design
- Executive reporting
- Data source validation
Module 11. Continuous Improvement
Embed feedback loops and improvement cycles into governance to maintain relevance and effectiveness over time.
12 chapters in this module
- Feedback channel design
- Lessons learned capture
- Benchmarking process
- Gap identification
- Improvement backlog
- Prioritization framework
- Resource allocation
- Pilot testing
- Change implementation
- Effectiveness validation
- Stakeholder review
- Update dissemination
Module 12. Future-Proofing and Evolution
Anticipate emerging trends and regulatory shifts to keep governance agile and forward-looking.
12 chapters in this module
- Regulatory horizon scanning
- Emerging risk patterns
- Technology shift monitoring
- Stakeholder expectation changes
- Scenario planning
- Flexible control design
- Adaptive policy clauses
- Governance innovation
- Skills development
- External benchmarking
- Strategic alignment
- Organizational readiness
How this maps to your situation
- New AI initiative launch
- Regulatory examination cycle
- Third-party AI vendor onboarding
- Internal audit preparation
Before vs. after
Before
Governance efforts are reactive, documentation is inconsistent, and control enforcement varies across teams.
After
You lead with a consistent, auditable framework, applying proven patterns that align with regulatory expectations and internal standards.
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, or 36 hours total, designed to be completed at your pace over 6-8 weeks.
How this compares to the alternatives
Unlike generic AI ethics courses or one-size-fits-all compliance templates, this program delivers insurance-specific governance patterns with decision-level precision, built for practitioners who lead real implementations under scrutiny.
Frequently asked
Is this course technical or policy-focused?
It balances both, focused on operationalizing governance with concrete control design, documentation, and enforcement processes.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help with external audits?
Yes, modules include audit-ready documentation templates and control mapping strategies used in regulated environments.
$199 one-time. Approximately 3 hours per module, or 36 hours total, designed to be completed at your 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