A tailored course, built for your situation
Mastering PCI DSS for Agentic AI and Gen AI Leaders
Build trusted, regulator-ready AI systems with documented control ownership
$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.
Most AI leaders inherit fragmented compliance responsibility, yours is proactive and anchored in verifiable control.
The situation this course is for
AI initiatives stall when compliance ownership is diffuse. Without clear control mapping to standards like PCI DSS, even high-potential projects face rework, delayed sign-off, or regulator scrutiny. The gap isn’t technical skill, it’s documented authority over control ownership in complex, payment-adjacent AI systems.
Who this is for
Senior AI leader operating across Gen AI and agentic systems, with demonstrated influence in technical training and cross-functional delivery. Works at the boundary of innovation and regulated infrastructure. Owns or advises on control implications of AI deployment in financial services.
Who this is not for
Individual contributors focused only on model accuracy, compliance analysts without AI deployment experience, or leaders whose scope does not include payment systems or data governance under PCI DSS.
What you walk away with
- Own end-to-end PCI DSS control mapping for AI components that process or store cardholder data
- Produce regulator-ready documentation for AI-driven transaction workflows
- Lead escalation paths during M&A technical due diligence involving AI systems
- Serve as the internal reference on PCI DSS applicability to agentic AI agents
- Deploy reusable control templates that accelerate future AI compliance cycles
The 12 modules (with all 144 chapters)
Module 1. PCI DSS Scope in AI Systems
Define what parts of agentic AI workflows fall under PCI DSS requirements, focusing on data flow, storage, and access in payment-adjacent environments.
12 chapters in this module
- Cardholder data lifecycle in AI pipelines
- Agent-initiated transactions and scope
- Tokenization boundaries in LLM outputs
- Data segmentation for AI training sets
- Third-party agent integrations
- Logging requirements for AI actors
- Encryption standards for model weights
- Session management in autonomous flows
- API call scope under DSS 12.9
- Non-public network definitions
- AI edge device compliance
- Scope validation checklist
Module 2. Control Ownership Models
Establish clear ownership frameworks for distributed AI teams, defining when compliance responsibility shifts from developers to governance leads.
12 chapters in this module
- Shared control matrices for AI
- RACI for model deployment
- Escalation paths during audits
- Version-controlled policy updates
- Sign-off delegation protocols
- Cross-team accountability models
- Documentation ownership
- Change advisory for AI agents
- Peer review thresholds
- Audit trail preservation
- Regulator-facing roles
- Control handover templates
Module 3. Regulator-Ready Documentation
Produce assessment-ready artefacts that stand up to FFIEC and GLBA-aligned reviews, with emphasis on AI-specific controls.
12 chapters in this module
- ROC reporting for AI modules
- AOC with AI justification
- Attestation of compliance prep
- Evidence collection workflows
- Versioned control narratives
- AI exception reporting
- Cross-standard harmonization
- Regulator Q&A preparation
- Control testing timelines
- Automated evidence pipelines
- Peer review coordination
- Final sign-off protocols
Module 4. M&A Technical Due Diligence
Lead AI compliance assessments during acquisitions, focusing on PCI DSS exposure in inherited systems.
12 chapters in this module
- AI debt assessment framework
- Agent behavior mapping
- Data provenance in training sets
- Model licensing audits
- Third-party agent risk
- Control gap analysis
- Integration risk scoring
- Legacy system interface risks
- Vendor AI compliance status
- Migration control plans
- Post-merger validation
- Due diligence reporting
Module 5. AI in CDE Environments
Architect AI components that operate safely within cardholder data environments while maintaining model efficacy.
12 chapters in this module
- LLM prompt filtering rules
- Real-time PII detection
- Output sanitization pipelines
- Access control for AI agents
- Prompt logging compliance
- Model fine-tuning safeguards
- Data masking in inference
- Audit trail generation
- Incident response for AI
- Model drift detection
- Agent behavior baselines
- CDE boundary enforcement
Module 6. Control Automation Techniques
Implement automated checks for continuous PCI DSS compliance in dynamic AI environments.
12 chapters in this module
- Policy-as-code for AI
- Automated drift detection
- Control validation pipelines
- Scheduled compliance checks
- AI-generated control reports
- Integration with SIEM
- Alert triage workflows
- Auto-remediation thresholds
- Version rollback triggers
- Change detection in agents
- Model registry controls
- Automated audit trails
Module 7. Third-Party Agent Governance
Manage compliance risk when using external AI agents in PCI-scoped systems.
12 chapters in this module
- Vendor AI risk assessment
- Agent behavior SLAs
- Data handling attestation
- Third-party audit rights
- API security requirements
- Agent monitoring protocols
- Incident response coordination
- Contractual control clauses
- Right-to-audit negotiation
- Subprocessor transparency
- Exit strategy for agents
- Compliance certification review
Module 8. Training Data Compliance
Ensure AI training datasets meet PCI DSS requirements for confidentiality and integrity.
12 chapters in this module
- Training set anonymization
- Data provenance tracking
- Synthetic data validation
- PII scrubbing pipelines
- Data retention policies
- Source documentation
- Auditability of data sets
- Data shift detection
- Labeling process compliance
- Data pipeline logging
- Third-party data risk
- Data lineage tools
Module 9. Incident Response for AI Systems
Adapt incident response plans to include AI-specific failure modes and escalation paths.
12 chapters in this module
- AI-generated fraud detection
- Model compromise scenarios
- Agent hijacking response
- Prompt injection handling
- Output integrity failure
- Bias incident protocols
- Model rollback procedures
- Forensic data capture
- Regulatory notification triggers
- Stakeholder communication
- Post-incident review
- Lessons-learned integration
Module 10. Audit Preparation Playbook
Assemble complete, consistent evidence packages for external PCI DSS audits involving AI systems.
12 chapters in this module
- Document request tracking
- Evidence collection workflow
- Cross-team coordination
- Gap identification process
- Remediation timelines
- Internal audit rehearsal
- QSA engagement prep
- Compliance scorecard
- Executive summary drafting
- Control testing validation
- Final review checklist
- Post-audit follow-up
Module 11. Cross-Standard Alignment
Map PCI DSS controls to overlapping frameworks like FFIEC, GLBA, and SOC 2 for unified governance.
12 chapters in this module
- Control overlap analysis
- Unified control templates
- Efficient evidence reuse
- Cross-audit preparation
- Regulatory expectation mapping
- Common control libraries
- Risk tiering by standard
- Efficiency gains tracking
- Inter-framework gap analysis
- Consolidated reporting
- Executive overview design
- Prioritization framework
Module 12. Sustaining Compliance at Scale
Maintain compliance integrity as AI systems grow in complexity and scale across the organization.
12 chapters in this module
- Onboarding new AI models
- Version control integration
- Change management process
- Training for new staff
- Playbook maintenance
- Leadership transition planning
- External auditor rotation
- Benchmarking against peers
- Continuous improvement cycle
- Feedback loop design
- KPI tracking for compliance
- Long-term governance roadmap
How this maps to your situation
- M&A technical due diligence
- Regulator-facing review cycles
- Board-prep documentation
- Escalations from peer AI teams
Before vs. after
Before
AI compliance initiatives rely on ad hoc coordination, with control ownership unclear and regulator-facing work distributed across teams.
After
You own documented control mappings for AI systems under PCI DSS, with escalation paths and review cycles routing to you first.
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 45, 60 minutes per module, designed for completion within 8 weeks while balancing core responsibilities.
If nothing changes
Without clear control ownership, high-impact AI projects risk rework, delayed deployment, or regulatory scrutiny, especially when integrated with payment systems. The most trusted roles on AI compliance are filled by those who can demonstrate end-to-end ownership of standards like PCI DSS.
How this compares to the alternatives
Unlike generic compliance courses, this program is tailored to AI leaders managing payment-adjacent systems. It focuses on concrete control ownership under PCI DSS, not abstract principles, so you gain artefacts and authority that compound across engagements.
Frequently asked
Is this course specific to financial services?
It’s designed for AI leaders in regulated sectors, with primary examples drawn from financial services and payment-adjacent AI systems.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does it cover other standards beyond PCI DSS?
PCI DSS is the core anchor, but modules align controls with FFIEC, GLBA, and SOC 2 where relevant.
$199 one-time. Approximately 45, 60 minutes per module, designed for completion within 8 weeks while balancing core responsibilities..
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