A tailored course, built for your situation
Deeper command of the AI governance frameworks shaping federal tech delivery
Master the standards, controls, and compliance architectures defining responsible AI in national security contexts
$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.
The situation this course is for
Who this is for
Senior technologist in federal consulting or defense contracting who operates at the boundary of technical implementation and regulatory compliance, influencing architecture decisions with policy-aware reasoning
Who this is not for
Entry-level compliance staff, commercial-sector AI developers, or practitioners focused solely on model performance without governance integration
What you walk away with
- Navigate NIST AI RMF and EO 14110 requirements with confidence, not consultation
- Map governance controls directly to system design choices without intermediary translation
- Produce compliance-ready documentation that passes internal review on first submission
- Anticipate audit questions using pre-built logic trees from recent federal engagements
- Lead cross-functional alignment using standardised terminology and artefact templates
The 12 modules (with all 144 chapters)
Module 1. Core structure of NIST AI RMF
Break down the four functions and cross-sector categories into actionable components for federal system design.
12 chapters in this module
- Overview of Govern, Map, Measure, Manage
- Function 1: Govern leadership roles
- Function 2: Map risk contexts
- Function 3: Measure performance gaps
- Function 4: Manage mitigation paths
- Integration with existing RMF workflows
- Mapping to DoD AI Ethics Principles
- Using the profile builder worksheet
- Tailoring for classified environments
- Case example: IC drone analytics project
- Linking to procurement language
- Maintaining version control
Module 2. Executive Order 14110 requirements
Translate high-level mandates into technical guardrails and validation thresholds for deployment readiness.
12 chapters in this module
- Section-by-section breakdown
- Red-teaming mandate scope
- Dual-use foundation model rules
- Agency reporting timelines
- Safety testbench expectations
- Incident sharing protocols
- Watermarking requirements
- Federated evaluation design
- Compliance checklist for vendors
- Internal audit preparation steps
- Handling classified model variants
- Mapping to existing security controls
Module 3. FedRAMP-aligned AI controls
Adapt cloud security baselines to AI-specific risks with pre-validated control mappings and evidence packages.
12 chapters in this module
- Control families affected by AI
- AC-02: Account management for AI agents
- AU-06: Audit logging for model decisions
- CM-08: Configuration settings for LLMs
- SI-11: AI-generated content filters
- SC-15: Interactive AI system protections
- RA-10: Adversarial testing frequency
- PM-31: AI use case inventories
- Custom control supplements
- Evidence collection templates
- Third-party assessment pathways
- Continuous monitoring integration
Module 4. Framework alignment patterns
Use decision matrices to align NIST, EO, and agency-specific requirements into a single coherent implementation path.
12 chapters in this module
- Identifying overlapping controls
- Resolving conflicting thresholds
- Prioritising high-impact items
- Using the harmonisation scorecard
- Decision log for leadership review
- Handling classified data flows
- Cross-walk with CMMC requirements
- Mapping to internal governance boards
- Versioning multi-framework policies
- Change management for updates
- Stakeholder communication plan
- Integration with DevSecOps pipeline
Module 5. Compliance artefact design
Build audit-ready documentation packages that reflect technical accuracy and policy alignment from the start.
12 chapters in this module
- SoA drafting with AI-specific sections
- POA&M entries for model risks
- Security plan integration points
- Control implementation narratives
- Evidence package organisation
- Template reuse across engagements
- Version control for artefacts
- Review cycle reduction tactics
- Pre-submission validation checklist
- Collaboration with legal teams
- Handling classification markings
- Delivery formats for different agencies
Module 6. Audit anticipation logic
Apply decision trees from past federal audits to predict questions and prepare responses in advance.
12 chapters in this module
- Common findings in AI reviews
- Root cause analysis of failed controls
- Evidence sufficiency thresholds
- Interview preparation framework
- Document trail completeness test
- Model card inspection points
- Training data provenance checks
- Bias assessment methodology review
- Incident response plan validation
- Red team report expectations
- Chain of custody documentation
- Lessons from recent ATO denials
Module 7. Technical specification translation
Turn governance mandates into system requirements with unambiguous implementation criteria.
12 chapters in this module
- Parsing policy language into constraints
- Defining measurable thresholds
- Setting logging granularity levels
- Specifying model monitoring intervals
- Input validation rules for prompts
- Output filtering configurations
- Human-in-the-loop integration points
- Fail-safe behaviour definitions
- Drift detection parameters
- Retraining triggers and thresholds
- Version rollback procedures
- Integration with existing spec templates
Module 8. Cross-functional alignment tools
Lead consensus across engineering, legal, and compliance teams using shared terminology and structured decision logs.
12 chapters in this module
- Glossary of standardised terms
- Risk tier definition framework
- Decision impact assessment matrix
- Stakeholder alignment checklist
- Conflict resolution playbook
- Meeting facilitation templates
- Escalation path definitions
- Change approval workflows
- Documentation ownership rules
- Version control for decisions
- Feedback loop design
- Conflict tracking log
Module 9. Governance automation patterns
Embed compliance checks into CI/CD pipelines and model deployment workflows using reusable logic blocks.
12 chapters in this module
- Pre-commit hooks for policy checks
- Model card generation automation
- Data provenance tagging scripts
- Bias detection in training pipelines
- Logging configuration validators
- Drift monitoring integration
- Compliance gate design
- Automated SoA updates
- Version comparison tools
- Policy change impact analysis
- Integration with GitOps tools
- Validation against control baselines
Module 10. Vendor oversight frameworks
Structure third-party evaluations and contractual terms to enforce adherence to internal and federal standards.
12 chapters in this module
- RFP language for AI compliance
- Third-party audit rights definition
- Model transparency requirements
- Right-to-explain clauses
- Penalties for non-compliance
- Ongoing monitoring expectations
- Subcontractor flow-down rules
- Security assessment coordination
- Incident notification timelines
- Access to training data logs
- Model update approval process
- Exit strategy and data return
Module 11. Classification and handling rules
Apply appropriate data and system handling protocols when AI systems process sensitive or classified information.
12 chapters in this module
- Derivative classification triggers
- AI-generated classified content
- Handling multi-level data inputs
- Secure prompt design principles
- Output sanitisation procedures
- Air-gapped model training
- Personnel clearance requirements
- Facility accreditation considerations
- Transmission protection methods
- Storage segmentation rules
- Declassification pathways
- Incident reporting for leaks
Module 12. Future-proofing against updates
Build adaptable governance structures that can absorb new directives without system redesign.
12 chapters in this module
- Monitoring for new guidance
- Change impact scoring system
- Policy version compatibility matrix
- Control substitution rules
- Modular architecture design
- Grace period planning
- Stakeholder notification templates
- Legacy system integration
- Transition period documentation
- Phased rollout planning
- Backward compatibility testing
- Decommissioning legacy controls
How this maps to your situation
- When standing up a new AI system under federal oversight
- During pre-audit preparation for ATO submission
- While drafting technical specifications for an AI capability
- When aligning cross-functional teams on governance expectations
Before vs. after
Before
Relying on ad hoc interpretations of AI governance requirements and reactive responses to audit feedback.
After
Applying structured, repeatable methods to implement and demonstrate compliance with confidence and consistency.
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, designed for completion over 6-8 weeks with real-world application between sections.
How this compares to the alternatives
Unlike generic AI ethics courses or broad compliance overviews, this program focuses exclusively on the operationalisation of current federal AI governance mandates into technical implementation decisions used in active DoD and intelligence community programs.
Frequently asked
Is this focused on commercial AI use cases or federal compliance?
This course is designed specifically for federal technology programs, with emphasis on NIST AI RMF, EO 14110, and agency-specific implementation patterns in national security contexts.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Are the templates suitable for classified environments?
Yes, all templates are designed with classification handling in mind and include guidance on applying appropriate markings and controls.
$199 one-time. Approximately 3-4 hours per module, designed for completion over 6-8 weeks with real-world application between sections..
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