A tailored course, built for your situation
Mastering ISO 42001 for IT Programme Leaders in Enterprise Systems
Build AI governance frameworks that scale across leasing, finance, and global ERP programs.
$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
IT programme leader in large-scale enterprise systems managing cross-functional compliance and governance requirements across regions.
Who this is not for
This is not for individual contributors focused only on technical implementation or auditors seeking certification prep.
What you walk away with
- Lead ISO 42001 adoption across multiple business units using existing ERP programme structures
- Design AI governance workflows that align leasing, finance, and operations teams
- Produce audit-ready AI accountability statements mapped to global compliance expectations
- Position yourself as the internal reference for AI governance scoping in enterprise rollouts
- Deploy reusable governance templates that compound value across future initiatives
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 42001 Scope and Boundaries
Learn how to define AI system boundaries within complex ERP environments, focusing on leasing data flows and decision points.
12 chapters in this module
- What ISO 42001 means for enterprise IT
- Mapping AI systems in Oracle ERP contexts
- Defining accountable roles clearly
- Linking AI governance to existing controls
- Setting scope for multi-region programs
- Avoiding overreach in governance design
- Documenting AI purpose statements
- Identifying high-risk AI use cases
- Aligning with leasing compliance history
- Building audit readiness from the start
- Stakeholder mapping for AI decisions
- Creating a governance foundation document
Module 2. Establishing Leadership and Organizational Context
Position yourself as the governance anchor by aligning AI accountability with existing programme leadership structures.
12 chapters in this module
- Positioning ISO 42001 leadership appropriately
- Leveraging current programme authority
- Gaining cross-unit buy-in without mandates
- Framing AI governance as enabler not gate
- Connecting to broader digital transformation goals
- Identifying executive champions
- Clarifying decision rights early
- Avoiding duplication of effort
- Integrating with change management
- Scaling understanding across teams
- Maintaining focus on delivery
- Building credibility through consistency
Module 3. Designing Risk Management Processes for AI Systems
Apply structured risk assessment to AI features in enterprise software, tailored to leasing lifecycle exposure points.
12 chapters in this module
- Adapting risk frameworks to AI
- Identifying AI-specific risk factors
- Scoring impact on financial decisions
- Assessing vendor AI model transparency
- Evaluating data quality influence
- Mapping risk to lease classification rules
- Setting risk tolerance levels
- Creating escalation paths
- Documenting risk treatment plans
- Integrating with existing risk registers
- Updating assessments over time
- Reporting risk posture clearly
Module 4. Implementing Data Governance for AI Models
Ensure data quality, provenance, and alignment with leasing data standards across AI training and operation.
12 chapters in this module
- Defining data quality metrics for AI
- Tracking data lineage in ERP systems
- Validating training data appropriateness
- Managing lease data segmentation
- Handling missing or biased data
- Establishing feedback loops
- Protecting sensitive lease terms
- Controlling access to model inputs
- Documenting data governance rules
- Auditing data pipeline integrity
- Linking to master data policies
- Scaling data oversight across regions
Module 5. Building Transparent AI System Documentation
Create clear, actionable documentation that supports compliance and cross-team alignment.
12 chapters in this module
- Structuring AI system registries
- Documenting model purpose clearly
- Recording design assumptions
- Capturing data sources and logic
- Explaining decision variables
- Maintaining version control
- Linking to audit requirements
- Creating summary overviews
- Ensuring documentation stays current
- Using visuals to enhance clarity
- Standardizing documentation formats
- Making documentation accessible
Module 6. Designing Human Oversight Mechanisms
Implement practical human-in-the-loop processes suited to leasing operations and financial controls.
12 chapters in this module
- Identifying where humans must intervene
- Setting clear escalation triggers
- Defining review frequency rules
- Training reviewers effectively
- Balancing automation with control
- Designing override procedures
- Monitoring oversight quality
- Adapting to changing risk levels
- Integrating with financial sign-offs
- Documenting human decisions
- Auditing oversight effectiveness
- Improving processes over time
Module 7. Ensuring Accuracy and Reliability of AI Outputs
Apply validation techniques that reflect the precision needs of leasing and financial reporting.
12 chapters in this module
- Defining accuracy thresholds
- Testing model performance routinely
- Monitoring for concept drift
- Validating against lease benchmarks
- Assessing financial impact of errors
- Implementing model recalibration
- Using ground truth data
- Tracking false positives systematically
- Ensuring consistency across regions
- Communicating reliability levels
- Handling edge cases
- Improving models over time
Module 8. Managing AI System Lifecycle and Updates
Establish governance for model updates, versioning, and retirement within enterprise programme timelines.
12 chapters in this module
- Planning AI system lifecycles
- Managing model version control
- Testing updates before rollout
- Scheduling retirement events
- Communicating changes clearly
- Handling legacy system integration
- Documenting update rationale
- Ensuring backward compatibility
- Auditing change effectiveness
- Avoiding technical debt
- Scaling lifecycle management
- Aligning with ERP upgrade cycles
Module 9. Protecting Personal Information in AI Systems
Apply data protection principles to AI processing involving customer and employee data in leasing contexts.
12 chapters in this module
- Identifying personal data use
- Applying data minimization
- Ensuring lawful basis for processing
- Protecting data during model training
- Designing for data subject rights
- Implementing access controls
- Conducting DPIAs for AI
- Assessing cross-border risks
- Maintaining audit logs
- Responding to data requests
- Training teams on obligations
- Aligning with global standards
Module 10. Auditing and Monitoring AI Governance Effectiveness
Design internal review processes that validate compliance and drive continuous improvement.
12 chapters in this module
- Planning audit schedules
- Designing audit checklists
- Sampling AI decisions effectively
- Measuring control effectiveness
- Evaluating oversight quality
- Reviewing incident logs
- Assessing risk treatment
- Reporting findings clearly
- Tracking remediation progress
- Incorporating lessons learned
- Aligning with external audits
- Improving frameworks over time
Module 11. Responding to Incidents and Drift in AI Systems
Prepare response protocols for model performance issues, bias detection, or compliance gaps.
12 chapters in this module
- Defining incident types clearly
- Establishing detection mechanisms
- Setting response timelines
- Documenting incident details
- Assessing root causes
- Implementing corrective actions
- Communicating internally
- Reporting to stakeholders
- Updating controls accordingly
- Preventing recurrence
- Testing response plans
- Learning from near misses
Module 12. Scaling AI Governance Across Business Units
Extend proven practices from leasing programs to other lines of business and regions.
12 chapters in this module
- Identifying transferable practices
- Adapting frameworks to new domains
- Training other programme leads
- Creating central support resources
- Standardizing documentation
- Building cross-unit networks
- Sharing success stories
- Establishing governance communities
- Measuring expansion impact
- Optimizing shared processes
- Maintaining local flexibility
- Driving enterprise-wide consistency
How this maps to your situation
- Initial scoping of AI governance in ERP environment
- Alignment with leasing compliance and operations teams
- Rollout of first AI accountability framework
- Expansion to additional business units
Before vs. after
Before
AI governance felt siloed, reactive, and disconnected from core programme delivery.
After
You lead intentional, scalable AI accountability that strengthens cross-unit trust and compliance outcomes.
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 3-4 hours per module, designed to fit around delivery commitments.
If nothing changes
Without structured governance, AI initiatives may face increased scrutiny, rework, or failed audits, especially as regulatory expectations evolve.
How this compares to the alternatives
Unlike generic compliance courses, this is built specifically for IT programme leaders managing enterprise systems who need to scale governance without expanding headcount or budget.
Frequently asked
Who is this course for?
IT programme leaders managing global systems with exposure to AI governance, especially in regulated environments like leasing and finance.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I apply this without direct authority over AI teams?
Yes, this is designed for influence through structured frameworks, not top-down mandates.
$199 one-time. Approximately 3-4 hours per module, designed to fit around delivery commitments..
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