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Faster path from policy intent to working ISO 42001 artefact

$199.00
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A tailored course, built for your situation

Faster path from policy intent to working ISO 42001 artefact

Turn AI governance intent into working compliance outcomes in days, not months

$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.
Governing AI without slowing delivery

The situation this course is for

Leaders in workplace and real estate strategy are now expected to lead on AI governance, but lack structured, proven methods to move from high-level intent to audit-ready artefacts without costly iterations or cross-team delays.

Who this is for

Senior practitioner driving governance in complex, cross-functional environments where real estate, workplace, and AI systems intersect

Who this is not for

Junior compliance staff, auditors focused only on checklists, or teams using generic ISO templates without domain adaptation

What you walk away with

  • Deliver ISO 42001-compliant documentation in under two weeks using a repeatable drafting workflow
  • Validate control mappings with stakeholders in a single review cycle
  • Generate artefacts that pass internal audit with minimal revisions
  • Deploy AI governance patterns that align with the firm-level execution standards
  • Reduce time from policy decision to signed-off framework by 60%

The 12 modules (with all 144 chapters)

Module 1. Mapping AI governance scope to workplace systems
Define the boundary of AI governance within real estate and workplace technology stacks using ISO 42001 Annex A controls.
12 chapters in this module
  1. Identify AI-impacted workplace systems
  2. Classify data flows by sensitivity
  3. Map locations to governance domains
  4. Tag interfaces with third-party tools
  5. Assign ownership by function
  6. Document decision rights
  7. Set control thresholds
  8. Align with global privacy rules
  9. Flag cross-border data risks
  10. Build asset inventory
  11. Integrate with facility management platforms
  12. Trace AI dependencies
Module 2. Building risk assessment workflows
Create structured, repeatable risk assessments that feed directly into control design without manual rework.
12 chapters in this module
  1. Define risk appetite statements
  2. Classify AI decision types
  3. Score impact on workforce
  4. Assess fairness thresholds
  5. Model bias propagation
  6. Estimate lifecycle duration
  7. Link to incident response
  8. Benchmark against NIST AI 100-1
  9. Incorporate stakeholder input
  10. Automate scoring logic
  11. Generate audit-ready registers
  12. Version control findings
Module 3. Designing human oversight controls
Implement oversight mechanisms that satisfy ISO 42001 requirements while fitting seamlessly into existing workplace operations.
12 chapters in this module
  1. Determine review frequency
  2. Assign escalation paths
  3. Document override procedures
  4. Log intervention points
  5. Train non-technical reviewers
  6. Integrate with HR systems
  7. Monitor shift patterns
  8. Validate decision logs
  9. Audit override usage
  10. Report to leadership
  11. Preserve context for regulators
  12. Maintain chain of custody
Module 4. Data quality assurance frameworks
Establish ongoing data integrity practices that support AI reliability and meet ISO 42001 data governance mandates.
12 chapters in this module
  1. Define data lineage standards
  2. Map collection methods
  3. Verify label accuracy
  4. Assess model drift triggers
  5. Set retraining thresholds
  6. Monitor input validity
  7. Flag outlier patterns
  8. Integrate with building sensors
  9. Audit data pipelines
  10. Report anomalies automatically
  11. Preserve historical snapshots
  12. Comply with retention policies
Module 5. Transparency and explainability implementation
Build documentation and communication protocols that satisfy internal and external explainability demands.
12 chapters in this module
  1. Define audience tiers
  2. Tailor technical depth
  3. Document model purpose
  4. Record training data sources
  5. Disclose limitations
  6. Publish disclosure formats
  7. Archive version narratives
  8. Update for model changes
  9. Link to incident reports
  10. Support regulator inquiries
  11. Train spokespeople
  12. Maintain public registers
Module 6. Security and robustness integration
Embed security practices into AI system design and maintenance cycles.
12 chapters in this module
  1. Assess adversarial risk
  2. Harden model endpoints
  3. Test input validation
  4. Monitor for manipulation
  5. Apply encryption standards
  6. Isolate environments
  7. Control access tightly
  8. Log all access events
  9. Enforce timeout rules
  10. Integrate with IAM
  11. Patch dependencies
  12. Audit configurations
Module 7. Performance monitoring systems
Set up continuous monitoring to track AI system behavior and detect deviations from expected performance.
12 chapters in this module
  1. Define KPIs for AI outputs
  2. Set baseline thresholds
  3. Measure accuracy decay
  4. Track fairness metrics
  5. Log decision patterns
  6. Alert on anomalies
  7. Integrate with Power BI
  8. Automate reporting
  9. Schedule health checks
  10. Trigger retraining
  11. Maintain trend history
  12. Support audit trails
Module 8. Accountability framework design
Clarify roles, responsibilities, and decision rights across AI governance lifecycle.
12 chapters in this module
  1. Assign RACI matrices
  2. Define escalation paths
  3. Document approval chains
  4. Set review cadence
  5. Integrate with legal
  6. Link to compliance teams
  7. Track decision lineage
  8. Preserve meeting notes
  9. Automate reminders
  10. Enforce gatekeeping steps
  11. Audit role assignments
  12. Update for org changes
Module 9. Stakeholder communication planning
Develop targeted messaging strategies for executives, auditors, regulators, and employees.
12 chapters in this module
  1. Identify audience needs
  2. Segment communication style
  3. Draft executive summaries
  4. Prepare regulator briefs
  5. Train spokespeople
  6. Publish transparency reports
  7. Host Q&A sessions
  8. Update internal portals
  9. Archive disclosures
  10. Track engagement
  11. Improve over time
  12. Align with ESG goals
Module 10. Incident response for AI systems
Build a clear, actionable response plan for AI-related incidents that satisfies ISO 42001 requirements.
12 chapters in this module
  1. Define incident types
  2. Classify severity levels
  3. Assign response teams
  4. Set notification timelines
  5. Document containment steps
  6. Preserve forensic data
  7. Engage legal counsel
  8. Report to regulators
  9. Notify affected parties
  10. Log actions taken
  11. Review post-event
  12. Update protocols
Module 11. Continuous improvement mechanisms
Implement feedback loops that ensure AI governance evolves with system changes and organizational needs.
12 chapters in this module
  1. Collect stakeholder input
  2. Track policy effectiveness
  3. Measure control gaps
  4. Update training materials
  5. Refresh risk registers
  6. Adjust oversight rules
  7. Reassess impact levels
  8. Optimize workflows
  9. Benchmark against peers
  10. Publish updates
  11. Archive old versions
  12. Ensure backward compatibility
Module 12. Internal audit readiness
Prepare comprehensive, organized documentation that passes internal audit with minimal follow-up.
12 chapters in this module
  1. Structure SoA documents
  2. Organize control evidence
  3. Link to policies
  4. Version all artefacts
  5. Verify completeness
  6. Conduct pre-audit review
  7. Assign reviewers
  8. Track open items
  9. Respond to findings
  10. Update playbooks
  11. Archive audit cycles
  12. Report to leadership

How this maps to your situation

  • When launching AI systems in workplace environments
  • During internal audit preparation cycles
  • After regulatory changes affecting AI use
  • Before executive governance reviews

Before vs. after

Before
Manual, inconsistent approaches to AI governance with long review cycles and repeated requests for clarification
After
Rapid, repeatable production of ISO 42001-aligned artefacts that pass audit and accelerate deployment

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 2.5 hours per module, designed for completion in parallel with active projects.

If nothing changes
Continuing with ad-hoc governance increases exposure to compliance delays, rework, and missed leadership opportunities in AI-driven transformation.

How this compares to the alternatives

Unlike generic ISO 42001 training, this course is tailored to senior practitioners in complex environments, delivering actionable workflows, not just theory. No other program combines domain-specific framing with the firm-grade execution standards.

Frequently asked

Is this course suitable for someone in a strategic leadership role?
Yes, this course is designed for senior practitioners who lead implementation, not just policy. It focuses on producing working artefacts quickly and with confidence.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does it cover ISO 42001 specifically?
Yes, every module is aligned to ISO 42001 control domains, with verbatim references and practical implementation methods.
$199 one-time. Approximately 2.5 hours per module, designed for completion in parallel with active projects..

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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