A tailored course, built for your situation
Mastering ISO 27001 for AI Trust and Security Practitioners
Produce auditable, regulator-ready outputs the first time, with precision and confidence.
$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.
Spending cycles revising compliance outputs that should have landed cleanly the first time
The situation this course is for
High-performing practitioners like Chris are expected to deliver flawless documentation under tight windows, yet many still face rework due to misalignment with ISO 27001 control expectations or incomplete evidence packaging. The gap isn’t knowledge, it’s precision under pressure.
Who this is for
Senior AI Trust and Security practitioners leading compliance artifacts in regulated tech environments
Who this is not for
Entry-level auditors, general IT staff, or those without direct responsibility for compliance documentation in AI or security contexts
What you walk away with
- Produce ISO 27001 compliance documentation that passes review without revision loops
- Anchor AI governance controls firmly within established information security frameworks
- Access ready-made templates for SoA, control narratives, and evidence checklists
- Reduce time spent on rework by 60-80% across audit cycles
- Build defensible, source-backed narratives for control implementation
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 27001 in AI Contexts
Map core ISO 27001 clauses to AI-specific trust and security risks, with emphasis on control relevance and exclusion justification.
12 chapters in this module
- Scope of ISO 27001 in modern AI systems
- Linking AI data flows to ISMS boundaries
- Control applicability for machine learning pipelines
- Exclusion criteria with defensible reasoning
- Documenting AI-specific control rationale
- Integrating risk assessments across models
- Establishing asset inventories for training data
- Classifying AI model outputs by sensitivity
- Mapping roles in AI development to ISMS roles
- Defining ownership for model lifecycle controls
- First-time accuracy in scope documentation
- Avoiding common misalignments in AI contexts
Module 2. Building the Statement of Applicability
Construct a defensible, error-resistant SoA that aligns with both AI system architecture and auditor expectations.
12 chapters in this module
- Control-by-control relevance assessment
- Justifying exclusions with policy links
- Referencing AI-specific risk treatment plans
- Using standardized language for consistency
- Cross-walking controls to NIST CSF
- Version control for SoA iterations
- Evidence mapping per control
- Formatting for readability and audit
- Automating consistency checks
- Common pitfalls in AI-related SoAs
- Validating completeness before review
- Producing clean SoA drafts on first pass
Module 3. Risk Assessment Alignment
Align AI governance risk findings with ISO 27001 risk treatment processes to ensure artefacts support compliance by design.
12 chapters in this module
- Starting with AI threat modeling outputs
- Translating model risks to ISMS risks
- Scoring likelihood with AI-specific factors
- Impact analysis for data poisoning events
- Risk treatment options for algorithmic bias
- Integrating risk register with SoA
- Documenting risk acceptance justifications
- Review cycles with legal and privacy
- Maintaining traceability to controls
- Updating assessments with model changes
- Avoiding overstatement in risk ratings
- First-time accuracy in risk documentation
Module 4. Control Implementation Evidence
Generate precise, audit-ready evidence packages that stand up to regulator scrutiny without revision.
12 chapters in this module
- Identifying evidence types per control
- Sampling strategies for AI workflows
- Documenting access reviews for model repos
- Capturing logging practices in training jobs
- Proving retention policies for model weights
- Demonstrating secure development for AI
- Evidence for third-party model components
- Version control for fine-tuning pipelines
- Access controls for inference endpoints
- Encryption practices for training data
- Audit trail completeness for AI systems
- Packaging evidence for external review
Module 5. Policy Documentation Precision
Write policies that are both technically accurate and auditor-compliant, reducing back-and-forth during review.
12 chapters in this module
- Scope definition for AI systems
- Acceptable use for foundation models
- Data handling in training and inference
- Model ownership and stewardship
- Version control for AI artifacts
- Incident response for model breaches
- Monitoring requirements for drift
- Ethical use guidelines and enforcement
- Review cycles with legal teams
- Policy alignment with ISO 27001 clause 5
- Clarity without oversimplification
- First-pass approval strategies
Module 6. Internal Audit Readiness
Prepare for internal audits with self-validating checklists and clean documentation flows.
12 chapters in this module
- Scheduling audits around model releases
- Checklist design for AI-specific controls
- Assigning auditors with technical depth
- Conducting walkthroughs on training jobs
- Sampling model inference logs
- Tracking findings in remediation
- Linking findings to SoA updates
- Reporting to leadership on AI posture
- Benchmarking against industry peers
- Improving audit speed and accuracy
- Reducing repeat findings
- Closing cycles before external audits
Module 7. External Audit Navigation
Enter external audits with confidence, delivering complete and defensible artefacts from the outset.
12 chapters in this module
- Selecting a certification body
- Preparing for stage 1 audit
- Submitting documentation package
- Responding to auditor questions
- Clarifying AI-specific control mappings
- Addressing scope concerns
- Handling requests for additional evidence
- Negotiating timelines effectively
- Finalizing certification decision
- Post-certification surveillance
- Maintaining artefacts between cycles
- Demonstrating continuous improvement
Module 8. Continuous Compliance for AI Systems
Maintain ISO 27001 compliance across model updates, deploys, and infrastructure changes.
12 chapters in this module
- Change management for AI pipelines
- Versioning model and data artifacts
- Automated compliance checks in CI/CD
- Monitoring drift in production models
- Reassessing controls post-update
- Documenting model retraining events
- Updating SoA with architectural changes
- Logging model inference activity
- Retention policies for AI outputs
- Decommissioning models securely
- Audit trails for model lineage
- Sustaining compliance with agility
Module 9. Cross-Functional Alignment
Lead alignment across engineering, legal, and product teams to ensure artefacts reflect ground truth.
12 chapters in this module
- Engaging legal on AI risk appetite
- Partnering with privacy on data use
- Aligning with platform teams on logging
- Working with product on feature scope
- Coordinating incident response
- Facilitating cross-team reviews
- Resolving ownership disputes
- Documenting agreements in writing
- Building trust with engineering
- Escalating misalignments early
- Driving consensus on control design
- Maintaining alignment at scale
Module 10. Regulator-Facing Communication
Craft clear, evidence-based narratives that anticipate follow-up and reduce scrutiny pressure.
12 chapters in this module
- Structuring responses to inquiries
- Preparing for on-site visits
- Anticipating follow-up questions
- Presenting control effectiveness
- Explaining AI-specific mitigations
- Using visuals to clarify complexity
- Maintaining composure under pressure
- Documenting verbal exchanges
- Coordinating legal presence
- Preserving tone of cooperation
- Avoiding overcommitment
- Closing reviews with confidence
Module 11. Leveraging Automation Tools
Use tooling to enforce consistency and accuracy in compliance outputs from the start.
12 chapters in this module
- Integrating ISO 27001 checks in CI/CD
- Automating asset inventory updates
- Validating SoA against control lists
- Generating policy templates from code
- Scanning for configuration drift
- Alerting on evidence gaps
- Versioning compliance artefacts
- Embedding controls in IaC
- Tracking exceptions automatically
- Reporting compliance status
- Reducing manual effort
- Improving first-time accuracy
Module 12. Building a Reusable Compliance Playbook
Document a tailored, repeatable process that survives team changes and scales across projects.
12 chapters in this module
- Capturing institutional knowledge
- Standardizing control mappings
- Creating template libraries
- Documenting decision rationales
- Training new team members
- Updating playbook with lessons
- Securing leadership buy-in
- Versioning and access control
- Linking to incident response
- Integrating with vendor reviews
- Using playbook across audits
- Ensuring long-term durability
How this maps to your situation
- Preparing for ISO 27001 certification with AI systems in scope
- Reducing rework during internal and external audits
- Aligning cross-functional teams on compliance expectations
- Sustaining compliance across rapid AI development cycles
Before vs. after
Before
Spending weeks revising compliance outputs, responding to auditor follow-ups, and reconciling team misalignments.
After
Producing clean, accurate, and defensible ISO 27001 documentation the first time, freeing up time for strategic work.
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 week over 12 weeks, with self-paced access for 12 months.
If nothing changes
Continuing to invest in rework-heavy compliance processes risks delays in certification, increased audit fatigue, and diminished credibility when delivering under pressure.
How this compares to the alternatives
Unlike generic ISO 27001 training, this course is tailored to AI Trust and Security practitioners, with specific focus on producing high-quality outputs for complex, modern systems, without rework.
Frequently asked
Who is this course for?
AI Trust and Security practitioners responsible for ISO 27001 compliance artefacts in technology organizations.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is this course technical or managerial?
It balances both, focused on producing accurate, defensible documentation that reflects technical reality while meeting compliance standards.
$199 one-time. Approximately 3-4 hours per week over 12 weeks, with self-paced access for 12 months..
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