A tailored course, built for your situation
Reference of choice on cross-functional AI Act compliance calls
Become the internal touchpoint others proactively loop into AI governance conversations
$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
IC at a high-growth data and AI platform company managing operational compliance workflows and cross-functional coordination
Who this is not for
Individuals seeking foundational AI literacy or technical model auditing skills
What you walk away with
- Proactively recognized as the go-to interpreter of AI Act requirements across teams
- Consistently included in governance escalation paths without self-advocacy
- Confidence to draft AI compliance positions that hold in cross-departmental review
- Clear, reusable templates for AI risk classification and conformity assessment
- Structured response patterns for high-pressure compliance queries from legal and product
The 12 modules (with all 144 chapters)
Module 1. AI Act scope and applicability mapping
Learn how to identify which AI systems fall under the AI Act’s high-risk categories and determine organizational obligations based on deployment context.
12 chapters in this module
- AI Act high-risk system definitions
- Determining deployment context
- Role classification under the Act
- Geographic scope triggers
- Sector-specific rules
- Third-party integration boundaries
- Legacy system exemptions
- Exclusions and edge cases
- Internal classification protocol
- Vendor-provided AI systems
- Model development phase rules
- Documentation thresholds
Module 2. Obligations for providers and deployers
Clarify legal and operational duties assigned to different roles under the AI Act, with emphasis on internal process alignment.
12 chapters in this module
- Provider vs deployer distinctions
- Transparency requirements
- Data provenance rules
- Human oversight mandates
- Risk management systems
- Record-keeping expectations
- Post-market monitoring
- Incident reporting duties
- Conformity assessment paths
- Quality management systems
- Technical documentation scope
- Compliance burden allocation
Module 3. Conformity assessment preparation
Build step-by-step readiness for formal evaluation under the AI Act, including documentation, stakeholder alignment, and gap analysis.
12 chapters in this module
- Internal audit checklist design
- Gap identification framework
- Stakeholder mapping
- Control evidence collection
- Process walk-through planning
- Documentation audit trail
- Legal alignment sessions
- Product team coordination
- Third-party validation prep
- Timeline for compliance
- Ownership matrix
- Escalation response plan
Module 4. Risk classification and categorization
Apply consistent, defensible logic to classify AI systems according to risk level and regulatory treatment.
12 chapters in this module
- High-risk determination criteria
- Safety component linkage
- Fundamental rights impact
- Automated decision rules
- Biometric identification limits
- Emotion recognition rules
- Remote biometric surveillance
- Critical infrastructure impact
- Education and employment systems
- Law enforcement exceptions
- Public-facing notice rules
- Classification decision log
Module 5. Data governance for AI systems
Implement data practices that meet AI Act requirements for training, validation, and monitoring datasets.
12 chapters in this module
- Data quality benchmarks
- Bias detection protocol
- Dataset documentation
- Representativeness checks
- Data lineage mapping
- Preprocessing transparency
- Monitoring dataset creation
- Data retention rules
- Third-party data use
- Labeling accuracy standards
- Model drift detection
- Human oversight in labeling
Module 6. Transparency and documentation design
Create clear, audit-ready documentation that satisfies AI Act transparency mandates for internal and external reviewers.
12 chapters in this module
- Technical documentation structure
- System overview drafting
- Intended purpose statements
- Performance metrics inclusion
- Limitations disclosure
- User instructions drafting
- API documentation rules
- Version control logging
- Change tracking systems
- Access control notes
- Update notification protocol
- Archival requirements
Module 7. Human oversight mechanisms
Design effective human-in-the-loop processes that satisfy AI Act requirements for meaningful control over AI decisions.
12 chapters in this module
- Human oversight definition
- Intervention points design
- Override capability rules
- Monitoring frequency
- Alert threshold setting
- Training for human reviewers
- Escalation path clarity
- Decision logging
- Fallback procedures
- Role assignment logic
- Performance review cycles
- Oversight audit trail
Module 8. Robustness and accuracy validation
Establish practices to ensure AI systems perform reliably and safely under real-world conditions.
12 chapters in this module
- Accuracy testing protocol
- Stress testing design
- Adversarial attack resistance
- System resilience checks
- Failure mode analysis
- Security testing scope
- Model drift detection
- Input perturbation testing
- Confidence threshold rules
- Uncertainty quantification
- Regular recalibration
- Performance degradation alerts
Module 9. Monitoring and post-deployment controls
Implement continuous oversight practices for AI systems after deployment to maintain compliance.
12 chapters in this module
- Performance monitoring design
- Model behavior tracking
- Drift detection systems
- Incident logging
- User feedback loop
- Complaint handling process
- Model update procedures
- Version control rules
- Decommissioning protocol
- Incident response plan
- Regulatory reporting
- Internal audit readiness
Module 10. Third-party AI system governance
Manage compliance obligations when using or integrating externally developed AI systems.
12 chapters in this module
- Vendor due diligence
- Contractual obligations
- Subsidiary liability
- Integration risk rules
- Compliance verification
- Audit rights negotiation
- Transparency requirements
- Performance guarantees
- Liability allocation
- Exit strategy planning
- Vendor lock-in risks
- Transition readiness
Module 11. Internal policy alignment
Align organizational workflows and governance structures with AI Act requirements.
12 chapters in this module
- Policy drafting process
- Legal alignment steps
- Product team coordination
- HR policy updates
- Training program design
- Cross-functional review
- Executive sign-off
- Policy version control
- Compliance tracking
- Audit preparation
- Incident response plan
- Continuous improvement
Module 12. Cross-functional communication strategy
Lead effective engagement across legal, product, engineering, and compliance teams on AI Act implementation.
12 chapters in this module
- Stakeholder mapping
- Message tailoring
- Glossary development
- Meeting facilitation
- Escalation protocols
- Decision logging
- Feedback incorporation
- Progress reporting
- Conflict resolution
- Consensus building
- Documentation sharing
- Follow-up tracking
How this maps to your situation
- Preparing for first internal AI Act readiness review
- Responding to legal team inquiry on AI compliance scope
- Aligning product roadmap with upcoming regulatory deadlines
- Fielding questions from engineering teams on compliance requirements
Before vs. after
Before
Compliance conversations are reactive, fragmented, and require repeated clarification across teams.
After
You lead consistent, confident AI Act interpretations that become the default reference point across departments.
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 completion over 4-6 weeks with practical application between modules.
If nothing changes
Without clear internal reference, compliance efforts remain siloed and prone to rework, increasing exposure to regulatory scrutiny and operational delays.
How this compares to the alternatives
Unlike generic AI ethics courses or broad compliance overviews, this course delivers actionable, AI Act-specific interpretation frameworks tailored to operational roles in AI-driven organizations.
Frequently asked
How is this different from general AI ethics training?
This course focuses exclusively on regulatory compliance under the AI Act, with emphasis on operational implementation, documentation, and cross-functional coordination.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is this relevant if we're not based in the EU?
Yes. The AI Act is becoming the global benchmark for AI regulation, and multinational firms are aligning internal policies to its standards regardless of jurisdiction.
$199 one-time. Approximately 3 hours per module, designed for completion over 4-6 weeks with practical application between modules..
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