A tailored course, built for your situation
Go to person status on AI Act implementation
Become the recognized internal expert on AI Act compliance through structured, actionable mastery
$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 product and compliance practitioners in tech firms navigating emerging AI regulation
Who this is not for
Individuals seeking introductory AI literacy or general awareness of EU regulation without implementation focus
What you walk away with
- First internal reference for AI Act interpretation within product teams
- Documented decision framework for AI risk classification aligned to AI Act tiers
- Pre-vetted language and examples for stakeholder alignment on compliance tradeoffs
- Internal credibility as the practitioner who ships compliant AI features faster
- Recognition as the product leader who balances innovation with regulatory readiness
The 12 modules (with all 144 chapters)
Module 1. AI Act scope and applicability mapping
Clarify which products and features fall under AI Act obligations based on risk tier and deployment context. Build a decision tree that speeds up classification for new initiatives.
12 chapters in this module
- Risk-based product categorization
- Establishing high-risk AI criteria
- Exemptions and edge cases
- Intended use definition
- Third-party model reliance
- Provider vs deployer obligations
- Real-time classification workflow
- Product boundary decisions
- Handling generative AI disclosures
- Dynamic updates to classification
- Internal alignment on scope
- Template: AI Act applicability checklist
Module 2. Data governance under Title III
Align training data practices with AI Act transparency and quality mandates. Focus on traceability, bias mitigation, and documentation needed for audits.
12 chapters in this module
- Data lineage for AI systems
- Bias assessment protocols
- Representativeness benchmarks
- Documentation standards
- Data subject rights integration
- Synthetic data disclosure
- Version-controlled datasets
- Data retention policies
- Labeling accuracy audits
- Third-party data sourcing
- Data quality reporting
- Template: Data governance matrix
Module 3. Technical documentation for conformity
Build comprehensive technical files that satisfy AI Act Article 11 requirements. Focus on clarity, completeness, and usability across product and compliance stakeholders.
12 chapters in this module
- System description structure
- Purpose and intended use statement
- Risk assessment integration
- Architecture diagrams
- Input output specifications
- Performance metrics definition
- Version control logging
- Change history tracking
- Human oversight mechanisms
- Fail-safe procedures
- Update protocols
- Template: Conformity documentation pack
Module 4. Record keeping and audit readiness
Design automated logging and storage systems that meet AI Act Article 12 requirements. Ensure records are complete, accessible, and defensible.
12 chapters in this module
- Logging system design
- Event types to capture
- Retention period alignment
- Access control policies
- Immutable storage options
- Log retrieval workflows
- Cross-border data flow
- Audit trail completeness
- Timestamp accuracy
- System downtime handling
- Backup validation
- Template: Audit readiness checklist
Module 5. Transparency for end-users
Implement clear, effective user-facing disclosures required under Article 13. Design notifications that meet legal standards without degrading UX.
12 chapters in this module
- High-risk system notification
- Generative AI disclosure
- Deepfake labeling standards
- Multilingual requirements
- Timing of disclosure
- Accessibility compliance
- User consent models
- Interaction logging notice
- Model capability limits
- Provider identification
- Enforcement monitoring
- Template: User transparency statement
Module 6. Human oversight design
Integrate meaningful human oversight into high-risk AI systems. Define roles, escalation paths, and decision authority to meet Article 14 requirements.
12 chapters in this module
- Human-in-the-loop definition
- Override capability design
- Monitoring frequency
- Escalation protocols
- Training for supervisors
- Decision logging
- Intervention timing
- Performance review cycles
- Fallback procedures
- Error reporting integration
- Accountability mapping
- Template: Oversight framework
Module 7. Accuracy and robustness standards
Establish performance benchmarks and testing regimens that meet AI Act reliability expectations. Focus on real-world resilience and edge-case handling.
12 chapters in this module
- Performance metric selection
- Stress testing methods
- Edge-case identification
- Drift detection systems
- Model recalibration rules
- Failure mode analysis
- Security testing
- Adversarial robustness
- Bias shift monitoring
- Third-party validation
- Reporting thresholds
- Template: Robustness test plan
Module 8. Conformity assessment paths
Navigate the EU's conformity routes for high-risk AI systems. Understand internal vs notified body processes and prepare for scrutiny.
12 chapters in this module
- Self-assessment criteria
- Notified body selection
- Third-party audit prep
- Quality management systems
- Technical file submission
- Surveillance requirements
- Certification timelines
- Post-market monitoring
- Non-compliance response
- Corrective action planning
- Update governance
- Template: Conformity roadmap
Module 9. Post-market monitoring systems
Design feedback loops and performance tracking that meet ongoing compliance requirements. Turn real-world data into proactive risk management.
12 chapters in this module
- Performance degradation alerts
- User feedback channels
- Incident logging
- Root cause analysis
- Remediation workflows
- Version recall protocols
- Model drift thresholds
- Bias emergence detection
- Security incident response
- Reporting to authorities
- Public disclosure rules
- Template: Monitoring dashboard
Module 10. AI Act and product lifecycle
Integrate AI Act compliance into product development workflows. Align roadmap planning, design sprints, and release cycles with regulatory requirements.
12 chapters in this module
- Compliance gating
- Risk tier assessment timing
- Design phase integration
- Review board structure
- Stakeholder alignment
- Compliance debt tracking
- Feature deprecation
- Legacy system review
- Change impact analysis
- Cross-functional handoffs
- Release sign-off process
- Template: Product-compliance workflow
Module 11. Cross-functional influence
Lead alignment between product, legal, engineering, and compliance teams. Use AI Act implementation as a platform for broader organizational impact.
12 chapters in this module
- Stakeholder mapping
- Influence strategies
- Compliance storytelling
- Executive summary drafting
- Escalation framework
- Resource allocation case
- Cross-team workshops
- Knowledge transfer plans
- Feedback integration
- Conflict resolution
- Success metrics definition
- Template: Influence playbook
Module 12. Maintaining go to person status
Turn initial success into sustained recognition. Build systems to maintain expertise, visibility, and trust as the internal reference for AI Act compliance.
12 chapters in this module
- Knowledge documentation
- Internal training design
- Office hours setup
- FAQ maintenance
- Trend monitoring
- Regulatory change alerts
- Version update process
- Mentorship opportunities
- Speaking opportunities
- Cross-team visibility
- Feedback collection
- Template: Expertise maintenance plan
How this maps to your situation
- Preparing a new AI product for EU launch
- Responding to internal audit requests
- Aligning with legal and compliance stakeholders
- Leading cross-functional AI governance working group
Before vs. after
Before
Navigating AI Act requirements informally, reacting to questions, relying on fragmented documentation and ad hoc decisions.
After
Leading with structured, repeatable processes, recognized as the internal authority on AI Act implementation, consistently shaping compliant product outcomes.
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 into real work cycles.
How this compares to the alternatives
Unlike generic compliance courses, this program delivers role-specific, implementation-ready frameworks tailored to product leaders. No other resource combines AI Act mastery with practical product integration and peer-tested templates.
Frequently asked
Is this course focused on legal interpretation?
No. It’s designed for practitioners who need to implement compliance decisions, not provide legal advice. The focus is on actionable frameworks, not legal opinions.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me gain visibility in my organization?
Yes. The course builds recognizable expertise and provides tools to establish yourself as the go to person on AI Act implementation.
$199 one-time. Approximately 3 hours per module, designed for integration into real work cycles..
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