A tailored course, built for your situation
Premium engagement picks with AI Act compliance mastery
Position yourself for high-impact, high-visibility AI governance work as new standards reshape demand
$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
Senior AI governance practitioner in a cloud or data platform environment, seeking higher-impact, higher-visibility engagements with strategic influence
Who this is not for
Entry-level compliance staff, auditors focused on checklist adherence, or professionals outside data/AI governance domains
What you walk away with
- Confidently lead AI Act compliance assessments using regulator-tested frameworks
- Access high-margin consulting opportunities by demonstrating structured implementation logic
- Position yourself as a first-call advisor for AI governance scope and evidence collection
- Deploy repeatable compliance artefacts that reduce setup time across engagements
- Navigate cross-functional AI governance decisions with precedent-backed reasoning
The 12 modules (with all 144 chapters)
Module 1. AI Act foundation and enterprise impact
Understand the binding obligations of the AI Act, how they map to real-world AI deployments, and where enforcement focus is forming.
12 chapters in this module
- Scope of the AI Act
- High-risk AI system classification
- Obligations for deployers and providers
- Regulatory timeline and enforcement bodies
- Relationship to existing data laws
- Sector-specific implications
- Exemptions and edge cases
- Vendor obligations under the Act
- Documentation requirements
- Transparency mandates
- Human oversight rules
- Penalties and liability
Module 2. Mapping AI Act to technical architecture
Align AI Act requirements with data pipelines, model design, and monitoring systems used in enterprise environments.
12 chapters in this module
- Data provenance and traceability
- Training data documentation
- Model risk tiering
- System logging standards
- Input monitoring design
- Output transparency implementation
- Human-in-the-loop integration
- Bias assessment protocols
- Accuracy validation cycles
- Robustness testing
- Security hardening
- Fallback mechanism design
Module 3. Evidence collection for high-risk systems
Build defensible compliance packages that anticipate auditor and regulator scrutiny.
12 chapters in this module
- Risk assessment templates
- Technical documentation structure
- Version control for models
- Change management logs
- Incident reporting protocols
- Quality assurance checklists
- Third-party audit prep
- Internal review workflows
- Conformity declaration drafting
- Legal accountability mapping
- Policy exception logging
- Maintenance update tracking
Module 4. Governance framework integration
Embed AI Act compliance into existing enterprise risk and governance structures.
12 chapters in this module
- Integrating with risk registers
- Cross-functional ownership
- Escalation pathways
- Policy update cycles
- Training program design
- Stakeholder communication
- Board-level reporting
- Vendor oversight coordination
- Internal audit alignment
- External certification prep
- Insurance implications
- Crisis response planning
Module 5. Stakeholder alignment and influence
Lead consensus across legal, engineering, and product teams on AI Act compliance priorities.
12 chapters in this module
- Translating legal terms to technical specs
- Facilitating cross-department workshops
- Negotiating risk thresholds
- Documenting design trade-offs
- Prioritizing implementation phases
- Managing executive expectations
- Securing budget approvals
- Aligning with procurement
- Vendor selection criteria
- Building internal coalitions
- Communicating compliance progress
- Handling pushback with evidence
Module 6. Vendor and partner compliance
Assess third-party AI systems and services against AI Act requirements.
12 chapters in this module
- Third-party due diligence
- Contractual obligations
- API transparency requirements
- Sub-processor accountability
- Model card evaluation
- Data processing agreements
- Audit rights negotiation
- Compliance warranties
- Liability allocation
- Exit strategy planning
- Ongoing monitoring
- Certification acceptance
Module 7. Internal policy design and rollout
Develop and deploy organization-wide AI governance policies aligned with the AI Act.
12 chapters in this module
- Policy drafting framework
- Approval workflows
- Version control systems
- Employee training rollout
- Acknowledgement tracking
- Policy exception handling
- Enforcement mechanisms
- Feedback integration
- Compliance monitoring
- Update communication
- Cross-regional alignment
- Policy retirement process
Module 8. Audit preparation and response
Prepare for and respond to internal and external audits under the AI Act.
12 chapters in this module
- Audit scope definition
- Evidence packaging
- Interview preparation
- Deficiency response planning
- Corrective action workflows
- Regulatory communication
- Mock audit exercises
- Third-party auditor coordination
- Findings documentation
- Follow-up tracking
- Report drafting
- Management response
Module 9. Continuous compliance monitoring
Design systems to maintain compliance as models and environments evolve.
12 chapters in this module
- Model lifecycle monitoring
- Drift detection systems
- Retraining validation
- Version comparison tools
- Automated documentation
- Alert thresholds
- Human review triggers
- Incident logging
- Compliance dashboards
- Periodic reassessment
- Change impact analysis
- Decommissioning records
Module 10. Case studies in AI Act alignment
Review real-world implementations and regulatory responses from peer organizations.
12 chapters in this module
- Healthcare diagnostics system
- Credit scoring model
- Recruiting tool
- Biometric surveillance
- Public sector chatbot
- Automated content moderation
- Financial advisory system
- Industrial automation
- Legal document review
- Insurance underwriting
- Educational assessment
- Autonomous vehicle control
Module 11. Global standards alignment
Map AI Act requirements to NIST AI RMF, OECD principles, and other frameworks.
12 chapters in this module
- NIST AI RMF crosswalk
- OECD AI principles
- ISO 42001 mapping
- EU Fundamental Rights alignment
- US Executive Order on AI
- UK AI regulation
- Canada's AI Act
- Japan's governance approach
- Singapore framework
- Australia's AI ethics
- India's draft policy
- Global interoperability
Module 12. Future-proofing AI governance
Anticipate next-phase AI regulation and position your practice ahead of shifts.
12 chapters in this module
- Upcoming EU regulations
- US federal movement
- Anticipated enforcement focus
- Model transparency demands
- Open source implications
- General-purpose AI rules
- Liability expansion
- Insurance product changes
- Cross-border data flows
- Human rights impact
- Workforce transformation
- Ethical boundary setting
How this maps to your situation
- When starting an AI Act compliance project
- During cross-functional alignment meetings
- Preparing for third-party audits
- Designing internal AI governance policy
Before vs. after
Before
Reactive support role in AI governance discussions, relying on ad-hoc documentation and fragmented guidance.
After
First-call advisor for AI Act implementation, leading engagements with structured frameworks and regulator-tested artefacts.
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 module, with flexible pacing to fit around active engagements.
If nothing changes
Without structured AI Act compliance capabilities, practitioners risk being sidelined in strategic AI initiatives, losing access to high-margin work, and missing opportunities to shape governance frameworks before they are locked in by external vendors or consultants.
How this compares to the alternatives
Unlike generic AI ethics courses or vendor-specific certifications, this program focuses exclusively on actionable AI Act compliance , providing specific, regulator-recognized frameworks, real-world implementation examples, and artefact templates that practitioners can deploy immediately in high-stakes engagements.
Frequently asked
How is this different from general AI ethics training?
This course focuses on binding regulatory requirements under the AI Act, not broad ethical principles. You'll get specific compliance frameworks, evidence collection methods, and real-world artefacts used in actual audits and regulatory engagements.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is this relevant if I work at a technology provider?
Yes. The AI Act applies to both deployers and providers of high-risk AI systems. This course covers obligations for system designers, vendors, and platform providers, with specific examples relevant to cloud and data platform environments.
$199 one-time. Approximately 3-4 hours per module, with flexible pacing to fit around active engagements..
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