A tailored course, built for your situation
Audit-Tested AI Vendor Risk Assessment for Risk-Adverse Boards
Master governance-grade AI vendor evaluation with confidence and precision
$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.
Even robust organizations struggle to prove AI vendor due diligence under auditor scrutiny
The situation this course is for
AI procurement moves fast, but audit cycles don’t bend. Without standardized, defensible risk assessment, teams face delays, escalated review costs, and last-minute renegotiations. The gap isn’t effort, it’s methodological rigor aligned to compliance expectations.
Who this is for
Compliance leads, risk officers, procurement strategists, and senior technologists accountable for AI vendor oversight in regulated or high-trust environments
Who this is not for
This is not for developers seeking technical AI safety controls or consultants wanting sales frameworks
What you walk away with
- Apply a repeatable, auditor-validated framework to assess AI vendors
- Structure documentation that satisfies internal and external review
- Communicate risk posture clearly to board-level stakeholders
- Reduce time-to-approval for critical AI vendor contracts
- Build organizational capacity for consistent, defensible vendor evaluation
The 12 modules (with all 144 chapters)
Module 1. Foundations of AI Vendor Risk
Establish core terminology, regulatory touchpoints, and the evolution of board expectations
12 chapters in this module
- Defining AI vendor risk in context
- Regulatory drivers shaping due diligence
- Board-level expectations today
- Lifecycle of AI procurement
- Common misconceptions in vendor assessment
- Risk maturity models
- Compliance vs. operational risk
- The role of third-party audits
- Vendor classification frameworks
- Mapping internal stakeholders
- Thresholds for escalation
- Documenting initial scoping
Module 2. Audit-Ready Framework Design
Build assessment structures that survive external review
12 chapters in this module
- Designing for traceability
- Evidence-based evaluation criteria
- Version control for assessments
- Standardizing risk ratings
- Aligning with ISO and NIST references
- Creating defensible decision trails
- Avoiding common documentation gaps
- Integrating legal and technical inputs
- Maintaining neutrality under pressure
- Scoring consistency across teams
- Justifying exceptions transparently
- Preparing for auditor Q&A
Module 3. Data Governance and Provenance
Evaluate vendor data practices with precision
12 chapters in this module
- Assessing training data lineage
- Provenance documentation standards
- Bias mitigation evidence review
- Data retention commitments
- Cross-border data flow policies
- Subprocessor transparency
- Right-to-delete implementation
- Data augmentation disclosures
- Synthetic data use cases
- Labeling process integrity
- Data refresh cycles
- Incident response for data issues
Module 4. Model Transparency and Explainability
Demand clarity without overstepping vendor IP
12 chapters in this module
- Right level of model disclosure
- Performance benchmarking requirements
- Accuracy under distribution shift
- Explainability methodologies
- Counterfactual analysis access
- Model drift detection protocols
- Version rollback capabilities
- Human-in-the-loop requirements
- Confidence threshold reporting
- Error mode documentation
- Model card completeness
- Third-party model audits
Module 5. Security and Access Controls
Verify infrastructure and identity safeguards
12 chapters in this module
- Authentication mechanisms
- Role-based access design
- Encryption in transit and at rest
- Penetration testing evidence
- SOC 2 Type II review points
- Incident response timelines
- Breach notification commitments
- API security standards
- Credential lifecycle management
- Zero-trust alignment
- Privileged access oversight
- Security patching SLAs
Module 6. Ethical AI and Fairness Assurance
Evaluate fairness claims beyond marketing
12 chapters in this module
- Fairness metric selection
- Disaggregated performance reporting
- Bias detection workflows
- Red teaming practices
- Ethics board involvement
- Community impact disclosures
- Grievance mechanisms
- Use case restriction policies
- Human oversight requirements
- Model withdrawal triggers
- Fairness testing frequency
- Stakeholder feedback loops
Module 7. Legal and Contractual Alignment
Bridge assessment outcomes to binding terms
12 chapters in this module
- Translating risk findings to contract clauses
- Liability allocation frameworks
- Indemnification scope
- Insurance requirements
- Termination triggers
- Audit rights negotiation
- IP ownership clarity
- Change control procedures
- Subcontractor approval
- Dispute resolution mechanisms
- Jurisdiction considerations
- Force majeure for AI failures
Module 8. Board-Level Communication Strategy
Present risk in language that enables decisions
12 chapters in this module
- Distilling technical findings
- Risk appetite alignment
- Scenario-based briefing
- Visualizing risk exposure
- Confidence level reporting
- Escalation thresholds
- Past incident context
- Vendor comparison frameworks
- Recommendation clarity
- Q&A preparation
- Follow-up action tracking
- Updating as conditions change
Module 9. Third-Party Audit Preparation
Ensure readiness for external validation
12 chapters in this module
- Common auditor request list
- Document organization standards
- Evidence packaging
- Cross-functional coordination
- Mock audit exercises
- Gap remediation workflow
- Timeline management
- Stakeholder briefing for auditors
- Response drafting templates
- Follow-up item tracking
- Corrective action plans
- Audit outcome reporting
Module 10. Ongoing Monitoring and Reassessment
Maintain vigilance post-contract
12 chapters in this module
- Performance tracking metrics
- Change notification requirements
- Quarterly review protocols
- Incident follow-up procedures
- Renewal risk reassessment
- Market shift monitoring
- Benchmark updates
- Stakeholder feedback integration
- Escalation workflows
- Corrective action tracking
- Vendor health scoring
- Exit readiness planning
Module 11. Cross-Functional Team Enablement
Scale assessment capacity across departments
12 chapters in this module
- Training non-specialists
- Role-specific playbooks
- Centralized knowledge base design
- Assessment workflow tools
- Approval routing setup
- Feedback integration
- Common mistake prevention
- Mentorship structures
- Onboarding new team members
- Maintaining consistency
- Updating team on changes
- Celebrating risk-avoided outcomes
Module 12. Implementation and Institutionalization
Embed the framework into organizational practice
12 chapters in this module
- Pilot program design
- Stakeholder buy-in strategies
- Process integration points
- Tooling requirements
- Success metrics definition
- Change management approach
- Leadership reporting rhythm
- Continuous improvement cycle
- Lessons learned capture
- Scaling across vendor types
- External recognition opportunities
- Maturity progression roadmap
How this maps to your situation
- Preparing for first AI vendor audit
- Scaling AI procurement under scrutiny
- Responding to board-level risk inquiries
- Building internal assessment capability
Before vs. after
Before
AI vendor risk assessments are inconsistent, reactive, and struggle under auditor review
After
Your team produces standardized, audit-ready evaluations that boards trust and procurement teams rely on
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 professionals to complete at their own pace within a 90-day window
If nothing changes
Organizations without formalized AI vendor risk practices face longer approval cycles, higher compliance costs, and increased exposure to reputational and operational incidents that erode stakeholder trust
How this compares to the alternatives
Unlike generic AI ethics guides or high-level risk summaries, this course provides implementation-grade templates, audit-tested frameworks, and board-communication strategies used by leading organizations managing complex AI vendor portfolios
Frequently asked
Who is this course designed for?
Compliance officers, risk leads, procurement strategists, and senior technology leaders accountable for AI vendor oversight in regulated or high-trust environments.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is there a hands-on component?
Yes, each module includes downloadable templates and worked examples, plus a hand-built implementation playbook to guide real-world application.
$199 one-time. Approximately 3-4 hours per module, designed for professionals to complete at their own pace within a 90-day window.
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