A tailored course, built for your situation
Mastering ISO 42001 for Financial Services AI Governance Leads
Build the first internal AI governance framework recognized across the firm Chase teams
$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.
Avoid being the team that reacts to AI governance audits, become the one others align to
The situation this course is for
Without a recognized internal framework, AI governance remains fragmented, reactive, and invisible until audit time. Practitioners with documented approaches are now being pulled into strategy conversations, those without are left out.
Who this is for
Senior AI governance or compliance lead in a large financial institution, driving framework adoption ahead of regulatory scrutiny
Who this is not for
Individual contributors focused only on checklist compliance, practitioners without cross-functional influence, or those not involved in AI policy rollout
What you walk away with
- Define the first internal ISO 42001 implementation playbook used across AI teams
- Become the go-to reference for audit and compliance teams on AI governance
- Produce artefacts that survive leadership changes and regulatory follow-ups
- Lead cross-functional alignment sessions using structured templates and real-world examples
- Document decision trails that pre-empt internal reviewer challenges
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 42001 in Financial Services Context
Lay the foundation for ISO 42001 implementation tailored to large financial institutions with complex AI deployments. This module introduces the standard’s structure, its alignment with internal audit expectations, and how top firms are interpreting controls.
12 chapters in this module
- Overview of ISO 42001 structure and clause intent
- How financial services firms interpret Clause 5 differently
- Mapping AI governance risk to ISO 42001 control domains
- Regulatory overlap between ISO 42001 and existing compliance frameworks
- Key differences from ISO 27001 in AI contexts
- Internal audit expectations for AI control documentation
- Role of legal and compliance in signing off on AI policies
- Documenting intent versus implementation for regulator review
- Tracking control maturity across AI development lifecycle
- Building evidence packs that survive reviewer scrutiny
- Integrating ISO 42001 with existing model risk governance
- Common misconceptions about AI-specific controls
Module 2. Stakeholder Alignment for AI Governance Rollout
Identify and engage key stakeholders across compliance, audit, legal, and AI engineering. Learn how to frame ISO 42001 as an enabler, not a constraint, and secure early buy-in.
12 chapters in this module
- Mapping decision owners across AI and compliance teams
- Crafting value-based messages for each stakeholder group
- Running alignment workshops that drive consensus
- Handling objections from engineering teams on agility impact
- Positioning controls as guardrails, not roadblocks
- Using precedent from early-adopter firms to build credibility
- Securing commitment from senior sponsors
- Creating shared ownership of control implementation
- Documenting agreements to prevent rework
- Maintaining momentum after initial alignment
- Escalation paths when stakeholder priorities diverge
- Tracking engagement across business units
Module 3. Building the AI Governance Statement of Applicability
Develop a defensible, living Statement of Applicability that answers both internal auditor and regulator questions. This module walks through real examples from financial institutions.
12 chapters in this module
- Structure of a regulator-ready Statement of Applicability
- Justifying exclusions with documented risk assessments
- Linking controls to specific AI use cases
- Versioning SoA for iterative AI model development
- Using templates to accelerate SoA creation
- Avoiding common gaps in scope definition
- Incorporating feedback from legal and compliance
- Handling dynamic scope changes in AI pipelines
- Maintaining traceability to control implementation
- Preparing SoA for internal audit review
- Common reviewer questions and how to answer them
- Updating SoA without restarting the approval process
Module 4. Control Mapping and Risk Prioritization
Map ISO 42001 controls to existing AI governance practices and identify highest-impact gaps. Prioritize based on audit likelihood and business risk exposure.
12 chapters in this module
- Crosswalking existing AI policies to ISO 42001 clauses
- Identifying duplicative or missing controls
- Prioritizing controls based on audit risk
- Using risk heatmaps to guide implementation order
- Aligning control priorities with model risk tiers
- Documenting rationale for control sequencing
- Engaging audit teams early in prioritization
- Scoping controls for third-party AI vendors
- Integrating control tracking with GRC tools
- Updating control maps for new AI deployments
- Common pitfalls in control ownership assignment
- Ensuring continuity during leadership transitions
Module 5. Developing AI Governance Policies and Procedures
Write internal policies that satisfy audit requirements and are actually usable by AI teams. Move beyond generic templates to practical, role-specific guidance.
12 chapters in this module
- Structuring policies for readability and compliance
- Writing procedures that engineers will follow
- Defining roles and responsibilities clearly
- Incorporating feedback loops into policy design
- Version control for policy documents
- Linking policies to training and onboarding
- Handling policy exceptions and deviations
- Using real incidents to strengthen policy language
- Aligning with global regulatory expectations
- Maintaining consistency across business units
- Automating policy distribution and attestation
- Auditing policy adherence without creating friction
Module 6. Evidence Collection for Internal and External Audits
Streamline evidence gathering so audits are predictable and low-effort. Build a central repository that maintains integrity across review cycles.
12 chapters in this module
- Designing evidence requirements for each control
- Automating evidence collection from AI pipelines
- Storing evidence in audit-ready formats
- Versioning and access control for audit packs
- Preparing for auditor walkthroughs
- Responding to follow-up requests efficiently
- Using templates to reduce evidence rework
- Validating evidence completeness before audit
- Handling requests for real-time data access
- Documenting evidence gaps transparently
- Maintaining records across organizational changes
- Reducing evidence burden through process design
Module 7. Third-Party and Vendor Governance Integration
Extend ISO 42001 controls to vendor-managed AI systems. Ensure compliance doesn't break at the outsourcing boundary.
12 chapters in this module
- Mapping ISO 42001 controls to vendor contracts
- Assessing vendor compliance maturity
- Running due diligence on AI platform providers
- Incorporating controls into procurement checklists
- Auditing third-party AI systems remotely
- Managing multi-vendor control overlaps
- Defining accountability for control failures
- Handling SLA violations related to governance
- Requiring evidence from vendors in standard format
- Updating vendor governance with AI model updates
- Using SIG and CAIQ questionnaires effectively
- Building long-term vendor collaboration
Module 8. Training and Change Management for AI Teams
Roll out AI governance training that sticks. Move beyond one-time sessions to ongoing reinforcement embedded in workflows.
12 chapters in this module
- Assessing current awareness of AI governance standards
- Designing role-based training paths
- Creating short, actionable learning modules
- Integrating training into onboarding
- Using real audit findings as teaching tools
- Measuring training effectiveness
- Engaging team leads as champions
- Reinforcing principles through code reviews
- Updating training for new regulations
- Gamifying compliance adoption
- Tracking completion and understanding
- Iterating content based on feedback
Module 9. Monitoring, Review, and Continuous Improvement
Establish routines to keep AI governance effective over time. Move from project to operational discipline.
12 chapters in this module
- Setting up regular control reviews
- Using metrics to track governance maturity
- Conducting internal audits of AI systems
- Incorporating lessons from incidents
- Updating controls based on new threats
- Benchmarking against peer institutions
- Reporting governance status to leadership
- Handling regulatory inspection outcomes
- Driving improvements through feedback
- Automating control monitoring where possible
- Maintaining momentum after certification
- Sustaining engagement through recognition
Module 10. Preparing for Certification and External Audit
Navigate the certification process smoothly. Understand what assessors look for and how to present your program confidently.
12 chapters in this module
- Selecting a certification body
- Understanding stage 1 and stage 2 audit differences
- Preparing documentation for external review
- Running internal mock audits
- Coordinating with legal and compliance
- Training teams for auditor interviews
- Presenting control implementation clearly
- Responding to non-conformance reports
- Maintaining composure during intense questioning
- Using audit outcomes for improvement
- Communicating certification to stakeholders
- Maintaining certification over time
Module 11. Scaling AI Governance Across Business Units
Replicate success across divisions without reinventing the wheel. Build a model that spreads through influence, not mandate.
12 chapters in this module
- Identifying early-adopter business units
- Adapting framework to different AI use cases
- Sharing playbooks across teams
- Creating internal consulting capability
- Recognizing and rewarding adoption
- Handling resistance from independent units
- Standardizing reporting without stifling innovation
- Using central resources to accelerate rollout
- Measuring cross-unit adoption
- Building communities of practice
- Scaling training and support
- Documenting lessons from expansion
Module 12. Sustaining Leadership and Strategic Influence
Transition from implementer to strategic advisor. Shape how AI governance evolves across the enterprise.
12 chapters in this module
- Positioning yourself as a thought leader
- Contributing to enterprise AI strategy
- Influencing budget and resource decisions
- Building cross-functional alliances
- Speaking the language of business value
- Anticipating future regulatory changes
- Staying ahead of emerging AI risks
- Mentoring next-generation practitioners
- Shaping internal policy evolution
- Representing the firm in external forums
- Balancing innovation and compliance
- Leaving a lasting governance legacy
How this maps to your situation
- Early-stage ISO 42001 adoption in financial services
- Cross-functional alignment challenges in AI governance
- Preparation for internal audit scrutiny
- Strategic positioning ahead of regulatory enforcement
Before vs. after
Before
AI governance is reactive, fragmented, and invisible until audit time
After
AI governance is proactive, unified, and recognized as a strategic asset across the organization
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 to fit around full-time responsibilities. Most practitioners complete the course in 6-8 weeks.
If nothing changes
Without a structured approach, teams remain reactive to audits, miss opportunities to influence AI strategy, and risk being bypassed in key decisions. Practitioners who wait are following frameworks built by others.
How this compares to the alternatives
Unlike generic compliance courses, this program delivers a field-tested implementation path for ISO 42001 in financial services AI governance , with templates and examples used by practitioners at global banks navigating the same challenges.
Frequently asked
Is this course relevant if we haven’t started ISO 42001 implementation?
Yes. The course is designed for practitioners at all stages , from early exploration to audit preparation. You’ll gain a clear roadmap and tools to start strong.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will the templates work in our GRC system?
Yes. Templates are provided in plain-text and CSV formats, designed for easy import into ServiceNow, RSA Archer, or custom platforms.
$199 one-time. Approximately 3 hours per module, designed to fit around full-time responsibilities. Most practitioners complete the course in 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