A tailored course, built for your situation
Audit-Tested AI Vendor Risk Assessment for High-Growth Organizations
A 12-module implementation-grade course for business and technology leaders advancing responsible AI adoption
The situation this course is for
Teams face mounting pressure to adopt AI tools quickly while ensuring security, regulatory alignment, and operational integrity. Without a standardized, audit-ready approach, organizations risk delays, inconsistent evaluations, and reactive scrambles during reviews.
Who this is for
Compliance leads, risk officers, IT governance professionals, and technology executives in high-growth organizations evaluating or deploying third-party AI solutions.
Who this is not for
This course is not for individuals seeking introductory AI awareness or technical model auditing. It assumes foundational knowledge and focuses on vendor risk lifecycle management.
What you walk away with
- Apply a proven, audit-tested framework to evaluate AI vendors systematically
- Reduce assessment cycle time with reusable templates and checklists
- Align legal, security, and operational stakeholders around a unified risk taxonomy
- Demonstrate compliance readiness during internal or external audits
- Build stakeholder confidence in AI procurement decisions
The 12 modules (with all 144 chapters)
- Defining AI vendor risk in modern procurement
- Key differences from traditional software risk
- Growth-stage challenges and scaling implications
- Stakeholder mapping across functions
- Regulatory landscape overview
- Emerging standards and frameworks
- Risk appetite and tolerance alignment
- Board and executive expectations
- Case study: Early-stage missteps
- Case study: Scaling with structure
- Common pitfalls and how to avoid them
- Module 1 action plan
- Principles of risk-based segmentation
- Data classification and handling rules
- Autonomy and decision-making authority
- Impact on business operations
- Third-party dependencies and supply chain
- Reputation and brand exposure
- Developing a scoring model
- Weighting criteria by organizational priority
- Validating categorization with stakeholders
- Automating tier assignment
- Maintaining consistency across teams
- Module 2 action plan
- Phases of due diligence
- Pre-engagement scoping
- Request for Information (RFI) design
- Security questionnaire best practices
- Compliance checklist integration
- Technical validation requirements
- Human oversight points
- Cross-functional review gates
- Timeline management
- Vendor response evaluation
- Escalation protocols
- Module 3 action plan
- Types of evidence: attestation vs. observation
- Reviewing SOC 2, ISO, and other reports
- Conducting vendor interviews
- Onsite vs. remote assessments
- Testing control effectiveness
- Sampling strategies
- Handling incomplete or missing evidence
- Third-party audit reliance
- Evidence storage and retention
- Preparing for auditor inquiries
- Continuous monitoring setup
- Module 4 action plan
- Designing a risk scoring matrix
- Calibrating thresholds
- Incorporating qualitative insights
- Weighting by business criticality
- Scenario analysis for high-risk vendors
- Compensating controls evaluation
- Risk treatment options
- Approval workflows
- Documenting rationale
- Managing exceptions
- Stakeholder communication templates
- Module 5 action plan
- Identifying key decision-makers
- Aligning on definitions and priorities
- Integrating with procurement lifecycle
- Legal and contract considerations
- Security team collaboration
- Finance and budget alignment
- Change management for new processes
- Training stakeholders
- Feedback loops and iteration
- Conflict resolution tactics
- Executive reporting formats
- Module 6 action plan
- Right-to-audit clauses
- Data ownership and portability
- AI model transparency requirements
- Performance guarantees
- Liability and indemnification
- Incident response obligations
- Subprocessor governance
- Termination rights
- Compliance certification commitments
- Update and patch management
- Dispute resolution mechanisms
- Module 7 action plan
- Continuous monitoring tools
- Key risk indicators (KRIs)
- Scheduled reassessment cadence
- Trigger-based reviews
- Vendor incident tracking
- Regulatory change alerts
- Performance deviation analysis
- Relationship health checks
- Exit planning and data recovery
- Updating risk profiles
- Reporting to oversight committees
- Module 8 action plan
- Audit scope and objectives
- Document retention policies
- Creating an audit package
- Version control for assessments
- Handling auditor requests
- Demonstrating consistency
- Gap identification and remediation
- Follow-up tracking
- Lessons learned integration
- Stakeholder preparation
- Post-audit improvement planning
- Module 9 action plan
- Centralized vs. decentralized models
- Center of excellence design
- Tooling and platform selection
- Process standardization
- Training and certification
- Metrics and KPIs
- Continuous improvement loop
- Change management at scale
- Executive sponsorship
- Integration with ERM
- Benchmarking against peers
- Module 10 action plan
- Algorithmic bias detection
- Fairness and equity assessments
- Explainability requirements
- Intellectual property ownership
- Training data provenance
- Model drift monitoring
- Adversarial attack resilience
- Prompt injection and manipulation
- Generative AI content risks
- Hallucination management
- Ethical use policies
- Module 11 action plan
- Getting started checklist
- Customizing templates
- Stakeholder onboarding plan
- Pilot program design
- Feedback collection strategy
- Iteration roadmap
- Success metrics definition
- Common blockers and solutions
- Vendor communication templates
- Training materials
- Scaling checklist
- Module 12 action plan
How this maps to your situation
- Assessing first AI vendor
- Scaling AI adoption across departments
- Preparing for external audit
- Responding to board-level inquiry
Before vs. after
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 4-6 hours per module, designed for flexible, self-paced learning.
How this compares to the alternatives
Unlike generic risk courses, this program focuses exclusively on AI vendor risk with implementation-grade detail, real-world templates, and a tailored playbook for immediate deployment.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.