A tailored course, built for your situation
Risk-Managed AI Vendor Risk Assessment for Senior Leaders
A structured, implementation-grade path for leadership to govern AI vendor ecosystems with clarity and control
$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.
Unclear accountability in AI vendor oversight
The situation this course is for
As AI vendors multiply across functions, leaders face mounting pressure to ensure compliance, ethical use, and operational resilience, without slowing innovation. Traditional risk frameworks fall short when applied to fast-evolving AI services, creating gaps in visibility, control, and board-level reporting.
Who this is for
Senior business and technology leaders responsible for AI governance, vendor oversight, compliance, or strategic risk management
Who this is not for
Individual contributors without decision authority, technical implementers without leadership scope, or teams seeking only developer-level AI training
What you walk away with
- Apply a consistent framework to evaluate AI vendor risk across departments
- Govern AI procurement with clear decision thresholds and escalation paths
- Build board-ready risk summaries that align technical detail with strategic exposure
- Implement monitoring systems that detect risk drift in live AI environments
- Lead cross-functional teams with a shared language for AI risk and value
The 12 modules (with all 144 chapters)
Module 1. Foundations of AI Vendor Risk
Define core risk categories, governance models, and leadership responsibilities in AI vendor ecosystems
12 chapters in this module
- Understanding AI vendor risk domains
- Mapping vendor types to risk profiles
- Governance vs. management roles
- Regulatory touchpoints in AI procurement
- Ethical risk dimensions
- Vendor lifecycle stages
- Internal stakeholder alignment
- Risk appetite frameworks
- Decision authority models
- Board engagement strategies
- Risk communication protocols
- Baseline assessment tools
Module 2. Strategic Risk Scoping
Identify and prioritize risk exposure across AI use cases and vendor relationships
12 chapters in this module
- Use case classification by risk level
- Data sensitivity mapping
- Third-party dependency analysis
- Impact assessment methodologies
- Vendor concentration risk
- Geopolitical exposure factors
- Supply chain transparency
- Contractual risk levers
- Service-level implications
- Exit strategy considerations
- Risk heat mapping
- Scenario planning templates
Module 3. Due Diligence Frameworks
Implement standardized evaluation processes for AI vendor selection and onboarding
12 chapters in this module
- Pre-vendor assessment checklist
- Security posture evaluation
- Model transparency requirements
- Data handling compliance
- AI bias audit protocols
- Explainability standards
- Performance validation methods
- Third-party audit rights
- Reference and case studies review
- Financial and operational stability
- Reputation and media scan
- Due diligence scoring model
Module 4. Contract Design for AI Risk
Structure agreements that enforce accountability, performance, and risk mitigation
12 chapters in this module
- Risk-aligned contract clauses
- Data ownership terms
- Model update controls
- Performance guarantees
- Audit and inspection rights
- Liability and indemnification
- Termination triggers
- Subcontractor oversight
- IP ownership clarity
- Change management protocols
- Dispute resolution frameworks
- Compliance enforcement mechanisms
Module 5. Governance Operating Model
Establish cross-functional teams, roles, and cadence for ongoing vendor oversight
12 chapters in this module
- Governance committee design
- Risk escalation paths
- Cross-departmental coordination
- Reporting cadence and format
- Decision gate frameworks
- Vendor performance dashboards
- Risk threshold definitions
- Incident response planning
- Stakeholder communication plan
- Board reporting templates
- Oversight automation tools
- Continuous improvement cycle
Module 6. AI Risk Monitoring Systems
Deploy operational systems to track vendor risk in real time
12 chapters in this module
- Key risk indicators for AI vendors
- Model drift detection
- Data integrity monitoring
- API and service uptime tracking
- Compliance change alerts
- Sentiment and media monitoring
- Third-party risk feeds
- Automated audit triggers
- Vendor self-reporting standards
- Anomaly detection frameworks
- Incident logging systems
- Risk scoring recalibration
Module 7. Incident Response for AI Vendors
Prepare for and respond to breaches, bias incidents, or service failures
12 chapters in this module
- Incident classification framework
- Escalation protocols
- Vendor notification requirements
- Internal response team roles
- Legal and regulatory reporting
- Public statement templates
- Forensic investigation process
- Model rollback procedures
- Customer impact mitigation
- Reputation recovery plan
- Post-mortem review process
- Insurance and liability claims
Module 8. Ethical AI Oversight
Embed ethical principles into vendor selection, monitoring, and reporting
12 chapters in this module
- Ethical AI principles framework
- Bias and fairness assessment
- Transparency requirements
- Human-in-the-loop standards
- Stakeholder impact analysis
- Community engagement expectations
- Ethics audit protocols
- Red teaming for AI systems
- Whistleblower mechanisms
- Ethics training for vendors
- Ethical incident response
- Board-level ethics reporting
Module 9. Regulatory Alignment
Ensure compliance with evolving AI, data, and sector-specific regulations
12 chapters in this module
- Global AI regulation trends
- Sector-specific compliance (finance, health, etc.)
- Data privacy alignment
- Algorithmic accountability laws
- Transparency mandates
- Certification and audit readiness
- Cross-border data flow rules
- Regulatory engagement strategies
- Compliance documentation standards
- Regulatory change monitoring
- Audit preparation process
- Vendor compliance validation
Module 10. AI Vendor Performance Management
Measure and improve vendor performance against risk and value metrics
12 chapters in this module
- Performance KPIs for AI vendors
- Service level agreement tracking
- Risk-adjusted performance scoring
- Value realization measurement
- Innovation delivery tracking
- Customer satisfaction metrics
- Vendor maturity assessments
- Benchmarking against peers
- Continuous feedback loops
- Renewal decision frameworks
- Vendor improvement plans
- Exit readiness scoring
Module 11. Scaling AI Vendor Governance
Expand governance frameworks across portfolios, regions, and business units
12 chapters in this module
- Centralized vs. decentralized models
- Governance automation tools
- Standardized templates and playbooks
- Training for regional teams
- Consolidated risk dashboards
- Vendor master list management
- Cross-functional alignment
- Change management for governance
- Technology stack integration
- Scalability testing
- Global coordination challenges
- Continuous governance improvement
Module 12. Leadership Integration
Embed AI vendor risk practices into executive decision-making and strategy
12 chapters in this module
- Executive risk literacy
- Board engagement models
- Strategic risk integration
- Budgeting for risk controls
- Talent and skills planning
- Vendor risk in M&A due diligence
- Risk culture development
- Long-term AI strategy alignment
- Succession planning for oversight
- Public disclosures and ESG
- Stakeholder trust metrics
- Future-proofing governance
How this maps to your situation
- AI vendor onboarding
- Ongoing vendor oversight
- Incident response and recovery
- Board-level risk reporting
Before vs. after
Before
Unclear ownership, inconsistent evaluations, reactive oversight, and fragmented reporting
After
Structured governance, proactive risk detection, board-ready insights, and repeatable decision frameworks
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 executive pacing with bookmarking and self-directed progress tracking
If nothing changes
Without a formalized approach, organizations risk compliance failures, reputational harm, and loss of stakeholder trust due to undetected AI vendor issues
How this compares to the alternatives
Unlike generic AI ethics courses or technical risk frameworks, this program is tailored for senior leaders who must balance innovation with governance. It provides actionable decision tools, not just theory, and integrates seamlessly with existing compliance and vendor management systems.
Frequently asked
Who is this course designed for?
Senior leaders in business and technology roles responsible for AI governance, vendor oversight, compliance, or strategic risk management.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is there hands-on work included?
Yes, every module includes downloadable templates, worked examples, and integration guidance for immediate application.
$199 one-time. Approximately 3-4 hours per module, designed for executive pacing with bookmarking and self-directed progress tracking.
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