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Audit-Tested AI Vendor Risk Assessment for Compliance Officers

$199.00
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A tailored course, built for your situation

Audit-Tested AI Vendor Risk Assessment for Compliance Officers

A 12-module implementation-grade course for professionals leading AI governance in regulated environments

$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.
Manual, inconsistent AI vendor reviews that don’t survive audit scrutiny

The situation this course is for

Compliance teams face increasing pressure to assess AI vendors with precision, yet most rely on ad-hoc checklists that lack audit durability. Without a structured, repeatable framework, teams risk delays, findings, or last-minute remediation during high-stakes reviews.

Who this is for

Compliance officers, risk leads, and governance professionals in regulated industries responsible for third-party AI oversight

Who this is not for

Individuals looking for introductory AI awareness content or generic vendor management templates not specific to AI systems

What you walk away with

  • Apply an audit-tested framework to assess any AI vendor confidently
  • Document risk decisions in a way that satisfies internal and external auditors
  • Reduce review cycle time by 50% using standardized evaluation workflows
  • Identify high-risk AI vendor practices before contract finalization
  • Build board-ready summaries of AI vendor risk posture

The 12 modules (with all 144 chapters)

Module 1. Foundations of AI Vendor Risk in Compliance
Establish the core principles of AI-specific vendor risk and how they differ from traditional IT assessments.
12 chapters in this module
  1. Defining AI vendor risk in a compliance context
  2. Regulatory expectations for third-party AI use
  3. Key differences: AI vs. traditional software vendors
  4. The compliance officer’s evolving role in AI governance
  5. Mapping AI risk to existing control frameworks
  6. Common misconceptions about AI audit readiness
  7. Stakeholder alignment: Legal, IT, and Risk
  8. When to escalate AI vendor concerns
  9. Building your AI risk lexicon
  10. Case study: Financial services vendor assessment
  11. Pre-assessment checklist setup
  12. Module implementation exercise
Module 2. Audit Triggers and Evidence Requirements
Learn what auditors look for and how to prepare evidence that passes scrutiny.
12 chapters in this module
  1. Top 10 audit findings in AI vendor reviews
  2. Evidence types that satisfy internal and external auditors
  3. Documentation standards for AI risk decisions
  4. Version control and change tracking for AI systems
  5. Proving due diligence in vendor selection
  6. How to structure an audit-ready assessment file
  7. Common gaps in AI vendor documentation
  8. Preparing for surprise audit requests
  9. Working with external audit firms
  10. Case study: Healthcare AI vendor audit
  11. Audit evidence mapping template
  12. Module implementation exercise
Module 3. AI-Specific Risk Domains
Break down the unique risk areas in AI systems that require specialized assessment.
12 chapters in this module
  1. Model transparency and explainability requirements
  2. Data provenance and bias mitigation practices
  3. Training data lineage and consent verification
  4. Model drift and performance degradation monitoring
  5. Adversarial attack surface in deployed models
  6. Human-in-the-loop and override mechanisms
  7. Automated decision-making impact assessments
  8. Third-party model dependency risks
  9. API security for AI services
  10. Case study: Credit scoring model vendor
  11. AI risk domain scoring worksheet
  12. Module implementation exercise
Module 4. Vendor Evaluation Framework Design
Build a customizable, repeatable framework for assessing AI vendors at scale.
12 chapters in this module
  1. Core components of an AI vendor assessment framework
  2. Risk tiering: Low, Medium, High, Critical
  3. Weighted scoring models for objective comparison
  4. Standardizing question design for consistency
  5. Automating initial screening workflows
  6. Integrating framework into procurement
  7. Calibration sessions with cross-functional teams
  8. Maintaining framework version control
  9. Benchmarking against industry standards
  10. Case study: Insurance claims automation vendor
  11. Framework configuration template
  12. Module implementation exercise
Module 5. Questionnaire Development and Deployment
Craft precise, audit-ready questionnaires that extract meaningful vendor responses.
12 chapters in this module
  1. Principles of effective AI vendor questioning
  2. Avoiding vague or leading questions
  3. Required disclosures for model development
  4. Questions to uncover hidden AI dependencies
  5. Probing for model monitoring practices
  6. Handling evasive or incomplete answers
  7. Follow-up protocols for clarification
  8. Scoring responses objectively
  9. Red flags in vendor documentation
  10. Case study: HR screening tool vendor
  11. Questionnaire builder toolkit
  12. Module implementation exercise
Module 6. Technical Validation Without Being Technical
Enable non-engineers to validate technical claims using structured verification techniques.
12 chapters in this module
  1. Understanding vendor technical documentation
  2. Key artifacts to request from AI vendors
  3. Validating model performance claims
  4. Assessing testing and validation processes
  5. Reviewing model cards and data sheets
  6. Interpreting third-party audit reports
  7. Working effectively with your data science team
  8. Translating technical findings into risk language
  9. When to require a technical review
  10. Case study: Fraud detection model vendor
  11. Technical validation checklist
  12. Module implementation exercise
Module 7. Contractual Risk Mitigation
Incorporate AI-specific protections into vendor agreements.
12 chapters in this module
  1. Essential AI clauses for vendor contracts
  2. Model performance guarantees and SLAs
  3. Right-to-audit provisions for AI systems
  4. Data ownership and usage rights
  5. Model update and version change protocols
  6. Incident reporting requirements for AI failures
  7. Exit strategies and model portability
  8. Liability for automated decision errors
  9. Insurance requirements for AI vendors
  10. Case study: Legal tech contract review
  11. Contract clause library
  12. Module implementation exercise
Module 8. Ongoing Monitoring and Reassessment
Establish a continuous oversight process for AI vendors post-contract.
12 chapters in this module
  1. Designing a continuous monitoring program
  2. Key risk indicators for AI vendor performance
  3. Quarterly review meeting structure
  4. Trigger-based reassessment protocols
  5. Handling model updates and retraining
  6. Monitoring for regulatory changes
  7. Vendor incident response coordination
  8. Updating risk ratings over time
  9. Documentation retention for audits
  10. Case study: Marketing personalization vendor
  11. Monitoring calendar template
  12. Module implementation exercise
Module 9. Cross-Functional Alignment
Lead alignment between compliance, legal, IT, and business units on AI vendor risk.
12 chapters in this module
  1. Building a shared AI risk language
  2. Facilitating risk review meetings
  3. Escalation paths for unresolved issues
  4. Role clarity in vendor assessments
  5. Communicating risk to non-experts
  6. Managing conflicting priorities
  7. Creating a centralized vendor risk register
  8. Training stakeholders on AI risk basics
  9. Reporting to executive leadership
  10. Case study: Cross-functional AI governance team
  11. Alignment workshop agenda
  12. Module implementation exercise
Module 10. Audit Preparation and Response
Prepare for and respond to audits with confidence using proven documentation strategies.
12 chapters in this module
  1. Anticipating auditor questions on AI vendors
  2. Assembling the audit response package
  3. Conducting pre-audit readiness checks
  4. Mock audit simulations
  5. Responding to findings and recommendations
  6. Negotiating audit outcomes
  7. Tracking remediation actions
  8. Post-audit review and improvement
  9. Maintaining audit trail integrity
  10. Case study: Regulatory examination response
  11. Audit response playbook
  12. Module implementation exercise
Module 11. Scaling AI Vendor Oversight
Expand your capabilities to manage multiple AI vendors efficiently.
12 chapters in this module
  1. Prioritizing vendors for assessment
  2. Tiered review intensity models
  3. Automation opportunities in vendor review
  4. Building a vendor risk management team
  5. Knowledge transfer and training
  6. Integrating with GRC platforms
  7. Benchmarking program maturity
  8. Continuous improvement cycle
  9. Managing vendor due diligence at scale
  10. Case study: Enterprise-wide AI vendor program
  11. Maturity assessment tool
  12. Module implementation exercise
Module 12. Future-Proofing Your AI Risk Practice
Stay ahead of emerging trends and evolving expectations in AI governance.
12 chapters in this module
  1. Tracking regulatory developments in AI
  2. Emerging standards and certifications
  3. Anticipating next-generation AI risks
  4. Preparing for AI-specific regulations
  5. Building organizational AI literacy
  6. Thought leadership opportunities
  7. Contributing to industry best practices
  8. Developing internal training programs
  9. Succession planning for AI risk roles
  10. Case study: Proactive compliance function
  11. Future trends briefing document
  12. Module implementation exercise

How this maps to your situation

  • Assessing first AI vendor engagement
  • Responding to audit findings on vendor risk
  • Designing a repeatable AI vendor review process
  • Scaling oversight across multiple departments

Before vs. after

Before
Reactive, inconsistent AI vendor assessments that lack audit durability and stakeholder alignment
After
A structured, repeatable, and audit-tested approach to AI vendor risk that positions you as a trusted governance leader

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 steady implementation alongside regular responsibilities.

If nothing changes
Without a formalized approach, organizations risk audit findings, delayed deployments, and reputational exposure when AI vendor issues arise.

How this compares to the alternatives

Unlike generic vendor risk courses, this program focuses exclusively on AI-specific risks, audit evidence standards, and implementation-grade tools tailored to compliance officers in regulated environments.

Frequently asked

Who is this course designed for?
Compliance officers, risk managers, and governance professionals responsible for assessing AI vendors in regulated industries.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is technical expertise required?
No. The course is designed for compliance professionals and includes methods to validate technical claims without needing to be an engineer.
$199 one-time. Approximately 3-4 hours per module, designed for steady implementation alongside regular responsibilities..

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
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