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Premium engagement picks with ISO 42001 implementation

$199.00
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A tailored course, built for your situation

Premium engagement picks with ISO 42001 implementation

Designed for developer support specialists leading security and compliance enablement

$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

Developer Support Specialist at a high-growth tech company, embedded in developer-facing infrastructure with growing responsibility for compliance enablement and control implementation

Who this is not for

This is not for compliance generalists, external auditors, or executives seeking board-level summaries. It is tailored to technical practitioners who implement frameworks, not delegate them.

What you walk away with

  • Prioritise and select high-impact engagements using ISO 42001 control criteria
  • Produce stakeholder-ready statements of applicability (SoA) in under 10 days
  • Lead cross-functional control mapping sessions without senior oversight
  • Re-use modular control templates across developer-facing compliance cycles
  • Earn direct assignment of AI governance escalations from engineering leads

The 12 modules (with all 144 chapters)

Module 1. Positioning ISO 42001 within developer support workflows
Understand how AI governance maps to developer support touchpoints across incident response, API access, and platform configuration. Align control objectives with existing enablement workflows.
12 chapters in this module
  1. Defining AI governance in developer support context
  2. Mapping ISO 42001 to developer onboarding
  3. Identifying control touchpoints in support tickets
  4. Linking AI controls to platform reliability
  5. Establishing governance escalation paths
  6. Documenting developer feedback loops
  7. Integrating AI risk into triage workflows
  8. Using support data to inform control scope
  9. Recognizing high-risk developer patterns
  10. Building control-aware support templates
  11. Coordinating with security engineering
  12. Tracking governance touchpoint frequency
Module 2. Scoping AI systems under ISO 42001
Learn to define boundaries for AI governance based on developer impact, data sensitivity, and deployment topology. Practice scoping decisions with real support case data.
12 chapters in this module
  1. Identifying AI-driven features in platform
  2. Classifying AI system criticality
  3. Mapping data flows for AI components
  4. Determining system ownership
  5. Setting scope boundaries for audit
  6. Documenting AI model inventory
  7. Assessing third-party AI dependencies
  8. Evaluating training data sources
  9. Tracking model versioning in support
  10. Linking scope to developer access logs
  11. Using support history to refine scope
  12. Producing scope justification artefacts
Module 3. Control identification for developer-facing AI
Extract and prioritise ISO 42001 controls relevant to developer workflows, API governance, and platform configuration. Focus on preventative and detective controls used in enforcement.
12 chapters in this module
  1. Reviewing ISO 42001 control A.8.1
  2. Mapping access controls to developer roles
  3. Implementing authentication safeguards
  4. Defining API usage policies
  5. Configuring rate limiting for AI endpoints
  6. Enforcing logging standards
  7. Validating model input sanitation
  8. Setting up model drift alerts
  9. Auditing prompt access controls
  10. Securing model training environments
  11. Controlling fine-tuning permissions
  12. Managing AI sandbox access
Module 4. Developing AI risk assessments with engineering teams
Lead joint risk workshops with developers using ISO 42001 risk criteria. Build risk registers that reflect actual platform behaviour and support load.
12 chapters in this module
  1. Framing risk with developer language
  2. Identifying AI failure modes
  3. Assessing bias in developer tools
  4. Evaluating model explainability gaps
  5. Rating likelihood using incident data
  6. Quantifying impact on developer trust
  7. Linking risk to SLA commitments
  8. Validating assumptions with logs
  9. Prioritizing risks by support volume
  10. Documenting risk treatment plans
  11. Presenting findings to engineering leads
  12. Updating risk register quarterly
Module 5. Building statements of applicability (SoA)
Create targeted SoAs that reflect developer platform reality. Use templates and decision rules to justify inclusion or exclusion of ISO 42001 controls.
12 chapters in this module
  1. Structuring SoA for technical teams
  2. Justifying control implementation status
  3. Documenting API authentication controls
  4. Referencing access policy documents
  5. Linking controls to existing safeguards
  6. Explaining deviations clearly
  7. Including developer workflow notes
  8. Using support ticket trends as evidence
  9. Aligning SoA with audit timelines
  10. Versioning SoA for reuse
  11. Redacting sensitive system details
  12. Sharing SoA with engineering leads
Module 6. Implementing access governance for AI tools
Design and enforce role-based access for AI development environments using ISO 42001 A.8.3 guidelines. Reduce support burden from misconfigured permissions.
12 chapters in this module
  1. Defining AI developer roles
  2. Mapping roles to least privilege
  3. Implementing just-in-time access
  4. Auditing access change requests
  5. Integrating with identity providers
  6. Enforcing MFA for AI systems
  7. Managing service account access
  8. Reviewing access quarterly
  9. Automating access revocation
  10. Logging access changes
  11. Linking access to incident response
  12. Reporting access metrics to leads
Module 7. Securing AI model development pipelines
Apply ISO 42001 controls to model training, fine-tuning, and deployment workflows. Ensure developer pipelines meet audit-ready standards.
12 chapters in this module
  1. Securing model training data
  2. Validating data preprocessing steps
  3. Isolating development environments
  4. Signing model artifacts
  5. Enforcing code reviews for AI
  6. Scanning for vulnerabilities
  7. Hardening container images
  8. Monitoring pipeline access
  9. Controlling model export
  10. Enabling rollback capability
  11. Auditing pipeline changes
  12. Integrating with CI/CD
Module 8. Managing third-party AI components
Evaluate and govern external AI tools and APIs used by developers. Use ISO 42001 to structure vendor review and ongoing monitoring.
12 chapters in this module
  1. Identifying third-party AI usage
  2. Assessing vendor security posture
  3. Reviewing data processing terms
  4. Validating API security controls
  5. Documenting integration risks
  6. Enforcing SLAs for AI vendors
  7. Monitoring vendor incident reports
  8. Conducting annual reviews
  9. Managing API key lifecycle
  10. Tracking subscription renewals
  11. Aligning vendor controls with ISO 42001
  12. Escalating vendor issues to legal
Module 9. Incident response for AI-related outages
Adapt incident response playbooks to include AI-specific failure modes. Train developer support to detect, triage, and document AI incidents.
12 chapters in this module
  1. Identifying AI-related incident types
  2. Classifying model degradation
  3. Detecting prompt injection attacks
  4. Responding to bias complaints
  5. Documenting model drift events
  6. Escalating to model owners
  7. Preserving model inputs for review
  8. Updating runbooks with AI paths
  9. Simulating AI failure drills
  10. Measuring MTTR for AI incidents
  11. Linking incidents to control gaps
  12. Reporting trends to security team
Module 10. Audit preparation and evidence collection
Organize audit-ready artefacts using developer support data. Automate evidence collection for recurring ISO 42001 control checks.
12 chapters in this module
  1. Identifying required audit evidence
  2. Extracting access logs for review
  3. Generating API usage reports
  4. Compiling incident response records
  5. Documenting control testing
  6. Packaging evidence packages
  7. Using support ticketing data
  8. Automating report generation
  9. Redacting sensitive information
  10. Validating completeness early
  11. Scheduling evidence collection
  12. Responding to auditor queries
Module 11. Continuous monitoring for AI systems
Design monitoring dashboards that track ISO 42001 control effectiveness. Use developer feedback to improve detection.
12 chapters in this module
  1. Defining AI control KPIs
  2. Tracking false positive rates
  3. Monitoring model performance decay
  4. Alerting on policy violations
  5. Reviewing access anomaly reports
  6. Measuring developer compliance
  7. Collecting usability feedback
  8. Reporting on control effectiveness
  9. Updating monitoring rules
  10. Integrating with observability tools
  11. Benchmarking against peer teams
  12. Optimizing alert thresholds
Module 12. Scaling AI governance across teams
Replicate successful control patterns across developer groups. Build reusable frameworks that reduce future support load.
12 chapters in this module
  1. Identifying governance champions
  2. Sharing SoA templates
  3. Hosting peer reviews
  4. Documenting lessons learned
  5. Standardizing control language
  6. Creating self-serve guides
  7. Reducing escalations through clarity
  8. Measuring governance maturity
  9. Aligning with platform roadmap
  10. Updating controls quarterly
  11. Celebrating compliance wins
  12. Planning next audit cycle

How this maps to your situation

  • When a new AI feature enters developer preview
  • When audit evidence is requested
  • When developers report permission issues
  • When third-party AI integration is proposed

Before vs. after

Before
Waiting for direction on compliance tasks, reacting to audit deadlines, relying on others to define control scope
After
Proactively leading ISO 42001 implementation, selecting high-value engagements, producing audit-ready artefacts independently

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 be completed alongside regular work. Most practitioners finish in 6-8 weeks with full implementation capacity.

How this compares to the alternatives

Unlike generic compliance courses, this program is built specifically for developer support roles implementing ISO 42001. It skips board-level abstractions and focuses on actionable, repeatable control patterns used in actual platform environments.

Frequently asked

How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this cover SOC 2 as well?
The course focuses on ISO 42001 but includes cross-walks to SOC 2 controls where they overlap, especially in access governance and incident response.
Can I use the templates in my current role?
Yes. Every template is field-tested and designed for use in developer-facing compliance roles at companies with complex platform environments.
$199 one-time. Approximately 3 hours per module, designed to be completed alongside regular work. Most practitioners finish in 6-8 weeks with full implementation capacity..

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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