A tailored course, built for your situation
Audit-Tested AI Vendor Risk Assessment for Public-Sector Programs
A 12-module implementation framework for compliance, governance, and technology leaders
$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.
AI adoption in government programs is outpacing risk validation capabilities
The situation this course is for
Teams are expected to deliver rigorous, auditable assessments of AI vendors, but often lack standardized, repeatable frameworks. This leads to inconsistent evaluations, compliance gaps, and delayed deployments, especially when under scrutiny.
Who this is for
Compliance officers, risk managers, and technology leads in public-sector or public-facing organizations adopting AI-powered solutions
Who this is not for
Individuals not involved in vendor assessment, AI governance, or public-sector program delivery
What you walk away with
- Build audit-ready AI vendor risk assessments from the ground up
- Align evaluations with regulatory expectations and internal policy controls
- Implement a repeatable framework across multiple vendors and use cases
- Reduce time spent on validation by 50% with structured templates and workflows
- Confidently defend assessment decisions to oversight bodies
The 12 modules (with all 144 chapters)
Module 1. Foundations of AI Vendor Risk in Public Programs
Introduces core principles, legal context, and risk taxonomy unique to public-sector AI adoption
12 chapters in this module
- Defining AI vendor risk in government contexts
- Jurisdictional compliance drivers
- Key differences from commercial AI risk
- Regulatory expectations for transparency
- Public accountability and algorithmic impact
- Risk ownership models
- Vendor lifecycle mapping
- Baseline assessment criteria
- Stakeholder alignment framework
- Documentation standards for audits
- Common pitfalls in early-stage evaluations
- Case study: First agency implementation
Module 2. Regulatory Alignment and Compliance Mapping
Covers how to align vendor assessments with current frameworks like NIST AI RMF, EO 13985, and sector-specific mandates
12 chapters in this module
- NIST AI RMF integration strategies
- Mapping controls to agency mandates
- EO 13985 compliance pathways
- Privacy and civil rights alignment
- Accessibility requirements for AI systems
- Sector-specific compliance nuances
- Crosswalk between frameworks
- Audit trail design
- Evidence collection protocols
- Compliance gap analysis
- Third-party validation readiness
- Audit response preparation
Module 3. Vendor Onboarding and Pre-Assessment Screening
Establishes a scalable process for initial vendor intake and risk triage
12 chapters in this module
- Pre-assessment questionnaire design
- Automated screening workflows
- Risk tiering by use case
- Data sensitivity classification
- Initial due diligence checklist
- Public records review methods
- Reputation and litigation screening
- Financial stability indicators
- Third-party audit report review
- Initial red flag identification
- Scoring model calibration
- Case study: Rapid onboarding at scale
Module 4. Algorithmic Transparency and Explainability
Teaches how to assess vendor claims around model interpretability and decision logic
12 chapters in this module
- Defining explainability in public-sector contexts
- Model documentation standards
- Counterfactual reasoning evaluation
- Feature importance validation
- Bias detection methodology
- Human-in-the-loop requirements
- Decision audit trail design
- Explainability testing protocols
- Vendor response validation
- Stakeholder communication templates
- Limitations disclosure frameworks
- Case study: Social services algorithm review
Module 5. Data Governance and Lifecycle Management
Covers data provenance, handling, retention, and sharing practices in AI vendor ecosystems
12 chapters in this module
- Data lineage and provenance tracking
- Training data bias assessment
- Data retention compliance
- Cross-border data transfer rules
- Data minimization validation
- Purpose limitation enforcement
- Data quality benchmarks
- Vendor data access controls
- Data breach response alignment
- Third-party data sourcing review
- Data inventory template integration
- Case study: Health data vendor audit
Module 6. Model Performance and Validation Rigor
Provides tools to evaluate vendor performance claims and testing methodologies
12 chapters in this module
- Performance metric validation
- Testing environment fidelity
- Benchmarking against public data
- Drift detection protocols
- Model versioning controls
- Accuracy across demographic groups
- Stress testing scenarios
- Validation dataset independence
- Re-testing frequency standards
- False positive/negative analysis
- Performance degradation alerts
- Case study: Fraud detection model review
Module 7. Security and Infrastructure Resilience
Guides assessment of vendor security posture, infrastructure hardening, and incident response readiness
12 chapters in this module
- Cloud security configuration review
- Penetration testing evidence review
- Access control model validation
- Encryption in transit and at rest
- Incident response plan audit
- Disaster recovery testing
- Vendor network segmentation
- Third-party dependency mapping
- Security certification alignment
- Zero-trust architecture alignment
- Breach notification timelines
- Case study: Critical infrastructure vendor review
Module 8. Ethical AI and Bias Mitigation Frameworks
Covers structured evaluation of fairness, equity, and ethical alignment in vendor offerings
12 chapters in this module
- Bias detection across protected classes
- Fairness metric selection
- Disparate impact analysis
- Ethical review board alignment
- Community impact assessment
- Bias mitigation technique validation
- Adversarial testing design
- Stakeholder feedback integration
- Redress mechanism evaluation
- Ethical AI policy alignment
- Transparency in limitations
- Case study: Hiring algorithm audit
Module 9. Contractual Controls and SLA Enforcement
Teaches how to embed risk requirements into contracts and monitor compliance
12 chapters in this module
- Risk-based SLA design
- Penalty clause structuring
- Audit rights negotiation
- Data ownership terms
- IP and model ownership clarity
- Exit strategy requirements
- Subcontractor oversight clauses
- Performance guarantee wording
- Liability limitation review
- Insurance requirement alignment
- Remediation timelines
- Case study: Multi-year contract audit
Module 10. Oversight and Continuous Monitoring
Builds a framework for post-deployment monitoring and ongoing risk management
12 chapters in this module
- Continuous monitoring design
- Automated alert threshold setting
- Quarterly review protocols
- Performance drift detection
- User feedback integration
- Compliance change tracking
- Third-party audit scheduling
- Stakeholder reporting cadence
- Risk score recalibration
- Incident escalation paths
- Dashboard design for oversight
- Case study: Real-time monitoring rollout
Module 11. Stakeholder Communication and Reporting
Equips teams to communicate risk findings clearly to non-technical decision-makers
12 chapters in this module
- Executive summary frameworks
- Risk heat map visualization
- Technical-to-policy translation
- Oversight committee reporting
- Public disclosure alignment
- Media response preparedness
- Inter-agency coordination templates
- Risk appetite communication
- Audit preparation briefings
- Vendor negotiation support materials
- Lessons learned documentation
- Case study: Cross-agency risk briefing
Module 12. Audit Readiness and Defense Preparation
Finalizes the framework with protocols to prepare for external review and scrutiny
12 chapters in this module
- Document organization for auditors
- Evidence traceability standards
- Common audit request patterns
- Response drafting workflows
- Interview preparation protocols
- Gap remediation tracking
- Corrective action planning
- Follow-up response timelines
- Lessons from past audits
- Pre-audit self-assessment
- Audit defense playbook
- Case study: Full regulatory audit response
How this maps to your situation
- New AI procurement initiative
- Existing vendor renewal under scrutiny
- Post-incident review mandate
- Regulatory audit preparation
Before vs. after
Before
Uncertain, inconsistent, or reactive AI vendor risk assessments that lack audit credibility
After
Structured, repeatable, and defensible evaluations that meet compliance and operational demands
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 busy professionals to complete at their own pace over 6-8 weeks.
If nothing changes
Without a standardized approach, organizations risk delayed deployments, compliance findings, public accountability failures, and erosion of stakeholder trust when using AI vendors in public programs.
How this compares to the alternatives
Unlike generic AI ethics courses or high-level policy summaries, this program delivers implementation-grade workflows, real-world templates, and audit-specific validation steps tailored to public-sector constraints and expectations.
Frequently asked
Who is this course designed for?
Compliance officers, risk managers, and technology leads responsible for assessing AI vendors in public-sector or public-facing programs.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is this course technical or policy-focused?
It bridges both, providing technical assessment criteria within a policy and compliance framework for real-world implementation.
$199 one-time. Approximately 3-4 hours per module, designed for busy professionals to complete at their own pace over 6-8 weeks..
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