A tailored course, built for your situation
Board-Level AI Vendor Risk Assessment for Established Enterprises
Implementation-grade mastery for technology and business leaders navigating AI governance at scale
$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.
Navigating AI vendor decisions without clear, board-ready risk frameworks
The situation this course is for
Leaders are expected to make confident AI procurement and oversight decisions, yet lack structured, repeatable methods to assess vendor integrity, compliance alignment, and operational resilience. This gap slows innovation and increases exposure to downstream escalations.
Who this is for
Technology executives, risk officers, compliance leads, and senior product or operations managers in established organizations adopting AI at scale
Who this is not for
Individuals seeking introductory AI literacy, developers focused on model tuning, or teams using AI in non-enterprise contexts
What you walk away with
- Apply a standardized assessment framework to any AI vendor engagement
- Translate technical risk factors into board-appropriate insights
- Design vendor onboarding workflows with built-in compliance checkpoints
- Leverage playbooks for contract negotiation, audit readiness, and exit planning
- Lead cross-functional reviews with confidence using proven evaluation templates
The 12 modules (with all 144 chapters)
Module 1. Foundations of Board-Level AI Oversight
Establish the governance context for AI vendor risk in enterprise settings
12 chapters in this module
- Defining board accountability in AI procurement
- Mapping regulatory expectations across jurisdictions
- Aligning AI risk with enterprise risk appetite
- Key roles in vendor oversight: legal, IT, compliance, and executive
- Case study: Board response to AI vendor incident
- From innovation mandate to risk boundary setting
- Stakeholder communication protocols
- Integrating AI risk into existing ERM frameworks
- Benchmarking readiness: self-assessment tool
- Common pitfalls in early-stage AI governance
- Building cross-functional alignment
- Developing executive dashboards for AI risk
Module 2. Vendor Due Diligence Frameworks
Structured evaluation of AI vendors pre-contract
12 chapters in this module
- Assessment scope definition
- Data provenance and lineage requirements
- Model transparency expectations
- Third-party audit readiness
- Security posture evaluation
- Compliance certification mapping
- Ethical AI principles alignment
- Workforce and training verification
- Incident response preparedness
- Financial and operational stability checks
- Reference and case validation
- Scoring and weighting methodologies
Module 3. Contractual Risk Mitigation
Designing agreements that enforce compliance and accountability
12 chapters in this module
- Service level agreements for AI systems
- Performance benchmarking clauses
- Data handling and retention terms
- Audit rights and access provisions
- Liability and indemnification structures
- Exit strategy and data portability terms
- Subcontractor oversight requirements
- IP ownership and usage rights
- Change management protocols
- Penalty and escalation mechanisms
- Dispute resolution frameworks
- Renewal and termination triggers
Module 4. AI Model Lifecycle Governance
Oversight across development, deployment, and monitoring
12 chapters in this module
- Model development standards
- Training data provenance tracking
- Bias detection and mitigation protocols
- Model validation techniques
- Version control and change logging
- Monitoring for drift and degradation
- Human-in-the-loop requirements
- Explainability expectations
- Model retirement procedures
- Third-party model integration risks
- Scoring model reliability
- Documentation completeness checks
Module 5. Data Security and Privacy Integration
Ensuring vendor practices meet enterprise data standards
12 chapters in this module
- Data classification alignment
- Encryption in transit and at rest
- Access control models
- Data residency and sovereignty
- PII handling protocols
- Breach notification timelines
- Third-party data sharing restrictions
- Consent management integration
- Data minimization enforcement
- Audit trail requirements
- Vendor penetration testing results
- Incident response coordination
Module 6. Compliance and Regulatory Alignment
Mapping vendor practices to current compliance obligations
12 chapters in this module
- GDPR alignment assessment
- CCPA and state privacy law mapping
- Industry-specific regulations (HIPAA, FINRA, etc)
- Algorithmic accountability laws
- Recordkeeping obligations
- Cross-border data transfer mechanisms
- Regulatory change monitoring
- Compliance audit preparation
- Documentation standards
- Regulator engagement protocols
- Self-reporting triggers
- Compliance scoring system
Module 7. Operational Resilience Planning
Ensuring business continuity with AI vendor dependencies
12 chapters in this module
- Vendor uptime and availability SLAs
- Disaster recovery readiness
- Failover and redundancy planning
- Monitoring and alerting integration
- Incident escalation paths
- Business impact analysis
- Dependency mapping techniques
- Stress testing vendor systems
- Crisis communication planning
- Redundant capability development
- Vendor lock-in mitigation
- Contingency resource planning
Module 8. Ethical AI and Social Impact
Evaluating vendor alignment with ethical principles
12 chapters in this module
- Fairness and bias mitigation
- Transparency in algorithmic decisions
- Human oversight requirements
- Community impact assessments
- Environmental sustainability
- Labor practices review
- AI for social good alignment
- Reputational risk factors
- Stakeholder feedback loops
- Ethics review board integration
- Public trust metrics
- Whistleblower protection
Module 9. Executive Reporting and Board Communication
Translating technical risk into strategic insight
12 chapters in this module
- Risk reporting frameworks
- Key risk indicators selection
- Dashboard design principles
- Board-level summary templates
- Escalation protocols
- Scenario planning narratives
- Benchmarking performance
- Trend analysis techniques
- Strategic opportunity framing
- Risk tolerance alignment
- Q&A preparation
- Presentation best practices
Module 10. Vendor Performance Monitoring
Ongoing assessment post-contract
12 chapters in this module
- Performance metric selection
- Monthly review processes
- Audit execution planning
- Compliance spot checks
- User feedback integration
- Incident trend analysis
- Remediation tracking
- Scorecard development
- Stakeholder interviews
- Continuous improvement planning
- Benchmarking against peers
- Contract renewal assessment
Module 11. Cross-Functional Collaboration Models
Aligning legal, IT, compliance, and business units
12 chapters in this module
- Stakeholder identification
- Governance committee design
- Meeting cadence planning
- Decision rights mapping
- Conflict resolution protocols
- Information sharing standards
- Joint assessment techniques
- Change approval workflows
- Training alignment
- Resource allocation models
- Accountability frameworks
- Success metric alignment
Module 12. Scaling AI Governance Across the Enterprise
Extending vendor risk practices across multiple initiatives
12 chapters in this module
- Centralized governance models
- Local delegation frameworks
- Standardized assessment templates
- Vendor registry development
- Knowledge sharing systems
- Training program design
- Maturity model progression
- Lessons learned integration
- External benchmarking
- Innovation pipeline alignment
- Board reporting integration
- Continuous refinement cycles
How this maps to your situation
- Board readiness for AI vendor oversight
- Enterprise-wide AI procurement governance
- Third-party risk integration into ERM
- Executive-level reporting on AI risk posture
Before vs. after
Before
Uncertain about how to assess AI vendors with board-level rigor
After
Confidently lead AI vendor risk assessments using proven frameworks and executive-ready reporting tools
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 over 6, 8 weeks with flexible pacing
If nothing changes
Without a structured approach, organizations face increased exposure to compliance incidents, reputational harm, and board-level escalations due to unvetted AI vendor dependencies.
How this compares to the alternatives
Unlike generic AI ethics courses or high-level overviews, this program provides implementation-grade detail tailored to enterprise-scale vendor assessment, with actionable templates and board-focused communication frameworks not found in open-source or conference-based content.
Frequently asked
Who is this course designed for?
It's built for technology executives, compliance officers, risk leaders, and senior product or operations managers in established organizations adopting AI at scale.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is there a money-back guarantee?
Yes, there's a 30-day money-back guarantee if the course doesn’t meet your expectations.
$199 one-time. Approximately 45, 60 minutes per module, designed for completion over 6, 8 weeks with flexible pacing.
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