A tailored course, built for your situation
Broader AI Governance Scope in Your Current Role with AI Act
Earn expanded responsibility for AI governance decisions without changing roles
$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.
Stuck influencing only a slice of the AI governance picture?
The situation this course is for
Even senior practitioners find their impact limited to execution, delivering what’s asked, but not shaping what gets decided. The work is solid, but scope stays narrow.
Who this is for
Senior IC in data or AI engineering who delivers high-quality systems but hasn’t yet claimed ownership over governance scope or decision rights
Who this is not for
Individuals seeking promotion to management, or those building AI products from scratch without governance context
What you walk away with
- Own end-to-end AI governance workflows under the AI Act
- Lead cross-functional AI compliance reviews without escalation
- Document and justify governance decisions with regulatory-grade clarity
- Design internal playbooks that become the reference across teams
- Earn direct input on AI policy exceptions and risk tolerances
The 12 modules (with all 144 chapters)
Module 1. AI Act Foundations for Practitioners
Understand the binding requirements and organisational obligations defined in the AI Act from an implementer's perspective.
12 chapters in this module
- Scope of regulated AI systems
- Risk classification tiers explained
- High-risk use case inventory
- Prohibited AI practices list
- Obligations by role provider vs deployer
- Geographic applicability boundaries
- Timeline for compliance enforcement
- Interaction with sectoral laws
- National competent authorities
- Penalty structure overview
- Exemptions for research and development
- Transparency requirements summary
Module 2. Governance Integration Planning
Map existing data and AI workflows to AI Act compliance domains and identify integration touchpoints.
12 chapters in this module
- Current state workflow audit
- Identify AI lifecycle stages
- Data provenance linkage
- Model documentation touchpoints
- Human oversight checkpoints
- Version control integration
- Monitoring system alignment
- Incident logging requirements
- Third-party component tracking
- Change management process fit
- QA validation stages
- Deployment gate criteria
Module 3. Risk Categorisation Framework
Apply consistent methodology to classify AI systems by risk level and justify categorisation decisions.
12 chapters in this module
- High-risk system identifiers
- System purpose analysis
- Context of use evaluation
- Impact severity scoring
- Likelihood of harm assessment
- Cumulative risk multipliers
- Documentation for auditors
- Cross-domain risk spillover
- Reclassification triggers
- Temporal risk evolution
- Feedback loop influence
- Stakeholder exposure mapping
Module 4. Compliance Evidence Architecture
Design evidence collection systems that support audit readiness and internal assurance.
12 chapters in this module
- Evidence types by article
- Automated logging design
- Manual process documentation
- Storage duration requirements
- Access control for reviewers
- Versioned artefact management
- Chain of custody protocols
- Third-party validation paths
- Internal audit trail format
- External auditor handover
- Retention policy alignment
- Data subject access response
Module 5. Data Quality Management for AI
Ensure training, validation, and monitoring data meet AI Act quality and representativeness mandates.
12 chapters in this module
- Representativeness benchmarks
- Bias testing protocols
- Adversarial robustness checks
- Data lineage standards
- Monitoring data drift
- Annotated dataset curation
- Preprocessing documentation
- Label accuracy verification
- Synthetic data governance
- Open source data compliance
- Data versioning schema
- Data split integrity
Module 6. Technical Documentation Systems
Build maintainable, version-controlled technical documentation that satisfies regulatory scrutiny.
12 chapters in this module
- System description template
- Intended use definition
- Performance metrics registry
- Lifecycle phase tracking
- Version compatibility matrix
- Change log structure
- Architecture diagrams standard
- Interface specifications
- Dependencies registry
- Security hardening notes
- Failover procedures
- Decommissioning plan
Module 7. Human Oversight Design
Implement human-in-the-loop mechanisms appropriate to risk level and use case.
12 chapters in this module
- Oversight timing decisions
- Role assignment matrix
- Alert threshold setting
- Escalation path design
- Training for oversight role
- Intervention logging
- False positive tolerance
- Workload balancing
- Contextual override guidance
- Auditability of decisions
- Feedback to model loop
- Rotation planning
Module 8. Model Risk Assessment Execution
Conduct structured model risk assessments that align with AI Act requirements.
12 chapters in this module
- Model inventory creation
- Hazard identification session
- Harm scenario modelling
- Probability estimation
- Impact severity scoring
- Risk matrix application
- Mitigation control mapping
- Residual risk calculation
- Independent review setup
- Risk register maintenance
- Reassessment triggers
- Cross-model comparison
Module 9. Transparency and Information Design
Design user-facing transparency materials that meet legal obligations and build trust.
12 chapters in this module
- User instruction templates
- Limitations disclosure
- Human oversight explanation
- Contact information inclusion
- Performance benchmarking
- Intended audience identification
- Language accessibility
- Update notification process
- Multimodal delivery options
- Versioned release notes
- Feedback mechanism inclusion
- Third-party content notices
Module 10. Conformity Assessment Pathways
Navigate conformity routes and prepare for technical documentation review by notified bodies.
12 chapters in this module
- Internal vs external audit choice
- Notified body selection
- Assessment scope definition
- Document package assembly
- Gap analysis execution
- Remediation planning
- Stage gate review design
- Audit response protocol
- Certificate maintenance
- Post-market monitoring linkage
- Incident reporting integration
- Surveillance compliance
Module 11. Stakeholder Alignment Workflows
Coordinate across legal, compliance, engineering, and product teams to maintain governance coherence.
12 chapters in this module
- Cross-functional RACI
- Governance committee design
- Escalation path mapping
- Decision rights clarity
- Policy exception process
- Change advisory board
- Vendor governance alignment
- M&A integration planning
- Training material development
- Compliance metric tracking
- Regulatory update monitoring
- Benchmarking participation
Module 12. Governance Automation Toolkit
Implement tooling to automate evidence collection, monitoring, and reporting.
12 chapters in this module
- Policy as code framework
- Automated compliance checks
- Continuous documentation
- Risk score dashboards
- Alerting configuration
- API-based evidence pull
- Metadata tagging schema
- Audit trail enrichment
- Integration with ticketing
- Model registry linkage
- CI CD pipeline hooks
- Versioned playbook updates
How this maps to your situation
- Before first audit
- After policy draft
- During vendor selection
- Post incident review
Before vs. after
Before
Delivering assigned components without decision rights over broader AI governance approach
After
Leading AI governance scope with recognised authority across teams and systems
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 for integration with real-world deliverables.
If nothing changes
Continuing to deliver high-quality work without claiming broader decision influence means others define the governance perimeter you operate within.
How this compares to the alternatives
Unlike generic AI ethics courses, this programme delivers actionable compliance frameworks tied directly to the AI Act, with documentation standards and decision workflows used by leading organisations.
Frequently asked
Is this course technical enough for a developer role?
Yes. It’s built for practitioners who implement systems and focuses on technical documentation, data quality, and integration points with engineering workflows.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does it cover NIST AI RMF or ISO 42001?
The primary anchor is AI Act, but crosswalks to NIST AI RMF and ISO 42001 are included where relevant.
$199 one-time. Approximately 3 hours per module, designed for integration with real-world deliverables..
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