A tailored course, built for your situation
Mastering ISO 42001 for Principal Security Architects
Build authoritative AI governance frameworks with full decision ownership
$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.
Struggling to assert control over AI governance decisions despite senior role?
The situation this course is for
Many senior architects are sidelined in AI framework ownership, despite their deep controls expertise. They're consulted late, overrides are common, and their input rarely shapes final policy or vendor selection. This erodes influence and delays compliance-readiness.
Who this is for
Principal-level security architects in consulting or client-facing roles who lead security operations and architecture for financial services clients. They have deep compliance and controls expertise but want greater decision authority in emerging AI governance.
Who this is not for
Junior security analysts, developers building AI models, or IT support staff who don't own enterprise-wide control frameworks.
What you walk away with
- Own the final control boundary definition for AI systems under ISO 42001
- Approve or reject third-party AI vendor integrations without escalation
- Set audit-readiness thresholds for AI components in security operations
- Lead client-facing AI governance reviews without senior review
- Document and replicate a repeatable AI control framework deployment playbook
The 12 modules (with all 144 chapters)
Module 1. Foundations of ISO 42001 in Security Architecture
Establish core principles of AI management systems within enterprise security frameworks, with focus on integration points for existing controls environments.
12 chapters in this module
- Defining AI scope in security architecture
- Mapping ISO 42001 to NIST CSF
- Control ownership models
- AI risk context for financial clients
- Integrating with SOC 2 frameworks
- Vendor AI lifecycle oversight
- Client-specific control overlays
- Documenting AI system inventories
- Establishing accountability tiers
- AI policy alignment checkpoints
- Regulatory expectation mapping
- Baseline control templates
Module 2. Control Boundary Design for AI Systems
Learn to define where security control responsibility starts and stops across AI models, data pipelines, and infrastructure.
12 chapters in this module
- Identifying AI system interfaces
- Data ingress control points
- Model training boundaries
- Inference endpoint ownership
- Third-party API control splits
- On-premise vs cloud AI controls
- Client data segregation rules
- Boundary documentation standards
- Control overlap resolution
- Boundary sign-off workflows
- Escalation thresholds
- Boundary audit trails
Module 3. Vendor Integration Approval Process
Establish criteria and workflows to independently approve or reject AI vendors against ISO 42001 and client-specific controls.
12 chapters in this module
- Pre-vetted vendor criteria
- Security questionnaire design
- Model explainability requirements
- Data handling compliance checks
- Audit log access validation
- Incident response SLA review
- Right-to-audit clause enforcement
- Penetration testing expectations
- Vendor control mapping
- Third-party attestation review
- Integration approval checklist
- Rejection documentation template
Module 4. Audit-Readiness Thresholds for AI Components
Set measurable, enforceable standards for when AI systems are ready for internal or external compliance review.
12 chapters in this module
- Defining audit-eligible status
- Control evidence requirements
- Logging completeness standards
- Access review frequency rules
- Change management compliance
- Model version tracking
- Data lineage expectations
- Anomaly detection readiness
- Remediation SLA definitions
- Stakeholder notification triggers
- Threshold sign-off authority
- Client-specific audit overlays
Module 5. Client-Facing Governance Review Leadership
Lead governance discussions with client stakeholders using ISO 42001 as the anchor for control decisions.
12 chapters in this module
- Client governance meeting structure
- Presenting control rationale
- Handling client override requests
- Documenting client agreements
- Risk acceptance workflows
- Escalation pathways
- Review frequency calendars
- Change impact communication
- Stakeholder alignment tools
- Regulator-readiness briefings
- Client-specific control registers
- Review sign-off authority
Module 6. Policy Alignment Across Security Domains
Ensure AI governance policies are consistent with broader security, privacy, and operations policies.
12 chapters in this module
- Cross-domain policy mapping
- Privacy policy integration
- Incident response alignment
- Access control consistency
- Data retention coordination
- Network security integration
- Change management sync
- Vendor risk policy links
- Compliance policy mapping
- Policy exception handling
- Version control process
- Policy audit trail setup
Module 7. Documented Framework Replication
Create a reusable, organization-wide playbook for deploying ISO 42001-aligned AI governance.
12 chapters in this module
- Playbook structure design
- Modular control templates
- Client onboarding workflows
- Team handover protocols
- Knowledge transfer sessions
- Version control system
- Update review cycles
- Lessons learned integration
- Client feedback loops
- Performance benchmarking
- Toolchain integration
- Continuous improvement process
Module 8. AI Risk Assessment Integration
Embed AI-specific risk assessments into existing security risk frameworks.
12 chapters in this module
- AI-specific threat modeling
- Bias risk evaluation
- Model drift monitoring
- Data poisoning risks
- Explainability gaps
- Adversarial attack vectors
- Supply chain risks
- Reputational impact scoring
- Regulatory violation likelihood
- Risk scoring methodology
- Acceptable risk thresholds
- Risk treatment workflows
Module 9. Change Management for AI Systems
Apply rigorous change control to AI model updates, data pipeline changes, and infrastructure shifts.
12 chapters in this module
- AI change request process
- Model update approvals
- Data pipeline versioning
- Infrastructure change reviews
- Rollback planning
- Staging environment use
- Peer review requirements
- Client notification triggers
- Documentation update rules
- Audit trail maintenance
- Change freeze policies
- Emergency change protocols
Module 10. Incident Response for AI Systems
Develop and lead incident response plans specific to AI system failures, bias events, or model compromises.
12 chapters in this module
- AI-specific incident types
- Detection mechanisms
- Containment strategies
- Bias event response
- Model compromise protocol
- Data integrity breaches
- Stakeholder communication
- Regulator notification
- Post-mortem process
- Root cause analysis
- Remediation tracking
- Response playbooks
Module 11. Regulatory Engagement Preparation
Prepare for regulator inquiries and examinations using ISO 42001 as the foundational framework.
12 chapters in this module
- Regulator question anticipation
- Evidence preparation
- Response documentation
- Interview preparation
- Client coordination
- Gap remediation planning
- Compliance timeline management
- Audit follow-up process
- Regulatory change tracking
- Cross-border compliance
- Reporting obligation mapping
- Regulator communication protocol
Module 12. Sustaining Governance Through Leadership Change
Ensure AI governance continuity regardless of personnel shifts or client transitions.
12 chapters in this module
- Succession planning
- Knowledge retention
- Documentation standards
- Onboarding new leads
- Client transition protocols
- Framework versioning
- Audit trail completeness
- External reviewer readiness
- Lessons learned archives
- Peer review rotations
- Cross-team alignment
- Governance maturity assessment
How this maps to your situation
- Designing AI control frameworks for financial clients
- Leading vendor due diligence for AI tools
- Preparing for client audit reviews
- Establishing governance under leadership transition
Before vs. after
Before
Reactive participation in AI governance discussions with limited authority over framework design or vendor decisions.
After
Proactive leadership with documented sign-off authority on AI control boundaries, vendor integrations, and audit-readiness thresholds.
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 integration into active client engagements.
If nothing changes
Without clear ownership, AI governance decisions will default to less-specialized teams, increasing compliance risk and reducing the strategic impact of your expertise.
How this compares to the alternatives
Unlike generic compliance courses, this program delivers actionable, role-specific authority in AI governance with verifiable decision ownership aligned to ISO 42001 and enterprise security architecture.
Frequently asked
Who is this course designed for?
Principal Security Architects leading AI governance for regulated financial services clients.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this course cover ISO 27001 as well?
Focus is on ISO 42001, with integration points to ISO 27001 where relevant for AI control alignment.
$199 one-time. Approximately 3 hours per module, designed for integration into active client engagements..
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