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DAT6270 Mastering ISO 42001 for Senior Technology Architects

$199.00
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A tailored course, built for your situation

Mastering ISO 42001 for Senior Technology Architects

Build AI governance systems that ship faster and stand up to review

$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.
AI governance is slowing down deployment cycles

The situation this course is for

Teams are stuck translating high-level AI policies into working controls, leading to delayed rollouts, repeated review cycles, and disconnected compliance artefacts. Architects are pulled in multiple directions without a clear path to implement standards efficiently.

Who this is for

Senior technology architect in a regulated enterprise, responsible for translating governance mandates into implemented systems, especially in AI and automation

Who this is not for

Junior administrators, non-technical compliance staff, or consultants without hands-on implementation experience

What you walk away with

  • Produce ISO 42001-compliant AI governance artefacts in under 10 business days
  • Reduce review cycles by 50% with pre-validated control templates
  • Map policies directly to ServiceNow configuration blueprints
  • Turn compliance checklists into automated workflows
  • Deliver audit-ready documentation as a byproduct of implementation

The 12 modules (with all 144 chapters)

Module 1. Understanding ISO 42001 and Its Impact on Enterprise AI
Foundational overview of ISO 42001, its structure, and how it applies specifically to enterprise architects. Learn how the standard intersects with existing ServiceNow governance workflows and where it introduces new requirements.
12 chapters in this module
  1. Introduction to ISO 42001 and the need for AI governance
  2. Key differences between ISO 42001 and earlier governance frameworks
  3. How ISO 42001 applies to automation and AI workflows
  4. The role of enterprise architects in AI governance adoption
  5. Overview of ISO 42001 clauses relevant to platform design
  6. Linking ISO 42001 to existing ServiceNow IT governance modules
  7. Emerging audit expectations around AI system documentation
  8. How regulators are interpreting AI governance controls
  9. Crosswalk between ISO 42001 and internal policy frameworks
  10. Architectural implications of transparency and explainability clauses
  11. Understanding the scope definition process in clause 4
  12. Preparing for organizational readiness assessments
Module 2. Scoping AI Governance for Complex IT Environments
Learn how to define the boundaries of AI governance within large, distributed systems. Focuses on identifying in-scope AI components, integrating with CMDB, and avoiding overreach.
12 chapters in this module
  1. Defining the scope of AI governance in enterprise architecture
  2. Identifying AI-driven workflows in ServiceNow instances
  3. Differentiating between AI, RPA, and automation systems
  4. Integrating AI inventory with CMDB and service mapping
  5. Avoiding scope creep in governance implementation
  6. Documenting decision rationale for audit purposes
  7. Using service ownership data to assign accountability
  8. Mapping AI capabilities to business service lines
  9. Handling shadow AI and unapproved models
  10. Setting boundaries for generative AI use cases
  11. Establishing criteria for AI system classification
  12. Creating a living scope register for continuous update
Module 3. Designing AI Governance Controls in ServiceNow
Translate ISO 42001 requirements into specific, implementable controls within ServiceNow. Covers policy automation, access reviews, and workflow enforcement.
12 chapters in this module
  1. Translating ISO 42001 clause 5 into technical controls
  2. Building policy-aware workflows in ServiceNow
  3. Automating access certification for AI systems
  4. Implementing approval chains for model deployment
  5. Configuring audit trails for AI decision logs
  6. Enforcing data lineage tracking in automation
  7. Creating policy gates in CI/CD pipelines
  8. Integrating ethical review checklists into deployment
  9. Using ServiceNow to enforce model update cycles
  10. Designing fallback mechanisms for AI failure
  11. Mapping controls to ISO 42001 Annex A references
  12. Validating control completeness before rollout
Module 4. Documenting AI System Artefacts for Audit Readiness
Generate comprehensive, audit-ready documentation that satisfies ISO 42001 requirements without redundant effort. Emphasizes automation and integration with existing reporting.
12 chapters in this module
  1. Required documentation under ISO 42001 clause 7
  2. Automating SoA generation from configuration data
  3. Maintaining AI inventory with auto-discovery
  4. Documenting decision-making logic in plain language
  5. Capturing training data sources and lineage
  6. Creating model performance monitoring plans
  7. Recording human oversight mechanisms
  8. Generating transparency statements automatically
  9. Maintaining version history for AI components
  10. Linking artefacts to change and release records
  11. Using templates to standardize documentation
  12. Integrating with GRC modules for centralized reporting
Module 5. Implementing Risk Assessments for AI Systems
Apply structured risk assessment methods to AI deployments, aligned with ISO 42001 clause 6. Focuses on repeatable processes and integration with enterprise risk frameworks.
12 chapters in this module
  1. Understanding risk assessment requirements in ISO 42001
  2. Adapting FAIR and OCTAVE for AI systems
  3. Identifying AI-specific threat scenarios
  4. Assessing bias, drift, and explainability risks
  5. Integrating with existing enterprise risk registers
  6. Conducting stakeholder impact assessments
  7. Documenting risk treatment decisions
  8. Building risk scoring models in ServiceNow
  9. Tying risk outcomes to control implementation
  10. Updating assessments after model changes
  11. Automating risk reassessment triggers
  12. Generating risk summary reports for leadership
Module 6. Establishing Human Oversight Mechanisms
Design and implement human-in-the-loop controls that satisfy ISO 42001 requirements. Focuses on meaningful oversight, not just token approvals.
12 chapters in this module
  1. Understanding human oversight in ISO 42001 clause 8
  2. Designing escalation paths for AI decisions
  3. Implementing override capabilities in workflows
  4. Ensuring human reviewers have context
  5. Recording human review rationale
  6. Balancing automation with intervention
  7. Setting thresholds for human review
  8. Training reviewers to assess AI output
  9. Auditing oversight effectiveness
  10. Monitoring time-to-intervention metrics
  11. Improving oversight based on feedback
  12. Scaling oversight across high-volume systems
Module 7. Managing AI System Lifecycle and Updates
Apply ISO 42001 principles across the full AI lifecycle, from deployment to decommissioning. Focuses on version control and continuous compliance.
12 chapters in this module
  1. Applying change management to AI models
  2. Defining update approval workflows
  3. Tracking model versions and dependencies
  4. Maintaining rollback capabilities
  5. Decommissioning AI systems securely
  6. Updating documentation after changes
  7. Handling model drift detection
  8. Scheduling retraining and validation
  9. Managing third-party model updates
  10. Integrating with DevSecOps pipelines
  11. Auditing lifecycle events for compliance
  12. Building lifecycle dashboards in ServiceNow
Module 8. Integrating AI Governance with Existing Compliance Programs
Connect AI governance to broader compliance efforts like SOC 2, ISO 27001, and SOX. Avoid siloed programs and redundant work.
12 chapters in this module
  1. Mapping ISO 42001 to SOC 2 trust principles
  2. Integrating with ISO 27001 security controls
  3. Aligning with SOX controls for automated decisions
  4. Using existing GRC platforms for AI oversight
  5. Avoiding duplicate evidence collection
  6. Conducting cross-framework control assessments
  7. Streamlining audit preparation across standards
  8. Leveraging ServiceNow for unified compliance
  9. Training auditors on AI-specific nuances
  10. Reporting compliance posture to leadership
  11. Managing overlapping control requirements
  12. Optimizing resource allocation across programs
Module 9. Measuring and Reporting on AI Governance Effectiveness
Define KPIs and dashboards to track the success of AI governance. Move beyond checkbox compliance to meaningful metrics.
12 chapters in this module
  1. Defining success for AI governance programs
  2. Tracking control implementation completeness
  3. Measuring review cycle times
  4. Monitoring audit finding closure rates
  5. Assessing human oversight effectiveness
  6. Measuring model drift and response
  7. Calculating time-to-compliance for new AI
  8. Benchmarking against industry standards
  9. Reporting to leadership on governance health
  10. Using dashboards to drive improvement
  11. Automating metric collection in ServiceNow
  12. Adjusting strategy based on performance
Module 10. Scaling Governance Across Multiple Business Units
Extend AI governance practices across the enterprise. Focuses on consistency, localization, and architectural enablement.
12 chapters in this module
  1. Designing centralized governance with local input
  2. Creating reusable governance blueprints
  3. Enabling self-service compliance for teams
  4. Managing exceptions and variances
  5. Ensuring consistency across global units
  6. Localizing policies for regional requirements
  7. Training architects on governance standards
  8. Sharing best practices across units
  9. Auditing cross-unit compliance
  10. Scaling tooling to support growth
  11. Integrating with enterprise architecture
  12. Maintaining governance at pace of innovation
Module 11. Preparing for External Audits and Certifications
Get ready for ISO 42001 certification audits. Covers evidence collection, auditor communication, and post-audit improvement.
12 chapters in this module
  1. Understanding ISO 42001 certification process
  2. Selecting certification bodies
  3. Preparing audit timelines and resources
  4. Gathering required documentation
  5. Conducting pre-audit readiness checks
  6. Responding to auditor inquiries
  7. Handling non-conformance reports
  8. Presenting governance maturity
  9. Demonstrating continuous improvement
  10. Leveraging ServiceNow data for evidence
  11. Training staff for audit interactions
  12. Closing audit findings efficiently
Module 12. Sustaining and Improving AI Governance Over Time
Ensure long-term success of AI governance. Focuses on continuous improvement, feedback loops, and adapting to change.
12 chapters in this module
  1. Establishing continuous improvement cycles
  2. Collecting feedback from users and auditors
  3. Updating policies based on lessons learned
  4. Monitoring regulatory changes
  5. Adapting to new AI technologies
  6. Revising governance scope as needed
  7. Maintaining stakeholder engagement
  8. Investing in architect upskilling
  9. Sharing governance innovations
  10. Benchmarking against evolving standards
  11. Building organizational muscle memory
  12. Institutionalizing governance as a core capability

How this maps to your situation

  • Architecture design under ISO 42001
  • Control implementation in ServiceNow
  • Audit preparation and evidence flow
  • Cross-functional governance scaling

Before vs. after

Before
Spending weeks translating AI governance policies into working controls, facing repeated review cycles and audit gaps.
After
Turning policy into production-ready artefacts in days, with documented, reusable implementation patterns that pass review the first time.

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: 90 minutes per module, designed to be completed over weekends or focused weekday blocks. Total course time: approximately 18 hours.

If nothing changes
Without a structured approach, AI governance efforts remain slow, inconsistent, and audit-prone , risking delays in deployment and increased scrutiny during compliance reviews.

How this compares to the alternatives

Unlike generic compliance courses, this program delivers architect-specific implementation patterns for ISO 42001 in real enterprise environments , not abstract theory. It’s faster than internal upskilling programs and more targeted than vendor-led certifications.

Frequently asked

Is this course technical or strategic?
It's architect-focused: technical enough to implement controls in ServiceNow, strategic enough to align with enterprise governance.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I apply this to non-ServiceNow systems?
Yes , while examples use ServiceNow, the patterns apply to any enterprise platform.
$199 one-time. 90 minutes per module, designed to be completed over weekends or focused weekday blocks. Total course time: approximately 18 hours..

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
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