A tailored course, built for your situation
Risk-Managed AI Vendor Risk Assessment for Public-Sector Programs
Implementation-grade assessment frameworks for AI procurement 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.
AI adoption in public-sector programs is accelerating, but vendor risk gaps can delay deployment, increase compliance costs, and erode stakeholder trust.
The situation this course is for
Organizations are moving fast to adopt AI-powered solutions, but procurement teams lack standardized, defensible methods to evaluate vendor risk across technical, ethical, and regulatory dimensions. This leads to inconsistent assessments, rework, and exposure to downstream compliance challenges, especially in highly audited environments.
Who this is for
Business and technology professionals leading AI procurement, risk governance, compliance, or digital transformation in public-sector or regulated environments.
Who this is not for
This is not for developers focused only on model tuning or engineers building internal AI tools without vendor integration. It’s not for consultants offering generic risk frameworks without public-sector context.
What you walk away with
- Apply a structured, repeatable framework to assess AI vendor risk across 12 critical dimensions
- Align vendor evaluations with current compliance expectations from major standards bodies
- Reduce procurement cycle time by using pre-built assessment templates and scoring rubrics
- Anticipate regulatory scrutiny by embedding audit-ready documentation into vendor onboarding
- Lead cross-functional evaluations with confidence using implementation-grade tooling
The 12 modules (with all 144 chapters)
Module 1. Foundations of AI Vendor Risk in Public-Sector Contexts
Establish core principles and regulatory drivers shaping AI procurement in government and public programs.
12 chapters in this module
- Defining AI vendor risk in public-sector delivery
- Regulatory landscape shaping procurement decisions
- Key differences: commercial vs. public-sector AI adoption
- Role of procurement officers in risk governance
- Ethical frameworks adopted by major agencies
- Lifecycle view of AI vendor engagement
- Common failure modes in early-stage assessments
- Stakeholder mapping for cross-functional alignment
- Overview of compliance benchmarks (NIST, ISO, EU AI Act)
- Risk tolerance thresholds in public programs
- Balancing innovation speed with due diligence
- Course navigation and implementation roadmap
Module 2. Vendor Due Diligence: Technical Readiness Assessment
Evaluate AI vendors on technical robustness, model transparency, and operational resilience.
12 chapters in this module
- Assessing model explainability and documentation quality
- Reviewing training data provenance and bias mitigation
- Infrastructure resilience and uptime commitments
- API security and data handling protocols
- Model versioning and update management
- Performance benchmarking under public-sector loads
- Third-party dependency analysis
- Red teaming vendor claims: stress-testing capabilities
- Evaluating MLOps maturity
- Incident response and model rollback procedures
- Integration complexity scoring
- Technical debt assessment in vendor offerings
Module 3. Compliance and Regulatory Alignment
Map vendor practices to current compliance expectations across jurisdictions and agencies.
12 chapters in this module
- NIST AI Risk Management Framework alignment
- EU AI Act classification and obligations
- FIPS and data sovereignty requirements
- Accessibility standards for public-facing AI
- Privacy-by-design in AI workflows
- Data retention and deletion obligations
- Cross-border data transfer mechanisms
- Audit trail requirements for AI decisions
- Human-in-the-loop mandates
- Sector-specific rules (health, education, justice)
- Certification readiness: SOC2, ISO, etc.
- Regulatory change monitoring protocols
Module 4. Ethical Governance and Bias Mitigation
Implement structured review processes for fairness, equity, and societal impact.
12 chapters in this module
- Bias detection across demographic cohorts
- Fairness metrics and threshold setting
- Stakeholder impact assessments
- Community engagement expectations
- Algorithmic accountability frameworks
- Bias mitigation techniques in training and inference
- Third-party audit readiness
- Transparency reporting requirements
- Redress mechanisms for affected parties
- Oversight board engagement models
- Bias testing across edge cases
- Ethical escalation pathways
Module 5. Contractual and Legal Safeguards
Structure agreements to enforce risk management commitments and service expectations.
12 chapters in this module
- Liability allocation for AI-generated outcomes
- Warranty clauses for model performance
- Indemnification for compliance failures
- Data ownership and reuse restrictions
- Subprocessor transparency requirements
- Right-to-audit clauses
- Termination triggers for ethical breaches
- Insurance and financial backing review
- Change management protocols
- Dispute resolution mechanisms
- Exit strategy and data portability
- Penalty frameworks for non-compliance
Module 6. Financial and Operational Sustainability
Assess vendor stability, funding model, and long-term support capacity.
12 chapters in this module
- Vendor funding stage and runway analysis
- Revenue model sustainability
- Customer support SLAs and responsiveness
- Roadmap transparency and co-development options
- Staff turnover and key person risk
- Geographic coverage and local presence
- Scalability under public-sector demand
- Multi-tenancy and isolation guarantees
- Disaster recovery and business continuity
- Third-party dependency risks
- Open-source component governance
- Exit impact assessment
Module 7. Implementation Playbook: Assessment Workflow
Deploy a standardized, team-friendly process for end-to-end vendor evaluation.
12 chapters in this module
- Assessment initiation and scoping
- Stakeholder onboarding checklist
- Document collection templates
- Scoring rubric customization
- Cross-functional review coordination
- Evidence compilation standards
- Draft report generation
- Review cycle management
- Risk tiering and escalation paths
- Final approval workflows
- Post-signature monitoring triggers
- Knowledge transfer to operations teams
Module 8. Risk Scoring and Tiering Methodology
Apply a calibrated scoring system to prioritize risk remediation and oversight.
12 chapters in this module
- Risk dimension weighting strategies
- Scoring consistency across evaluators
- High-risk indicator flags
- Automated scoring support tools
- Threshold-based decision gates
- Risk aggregation across domains
- Dynamic re-scoring over time
- Benchmarking against peer vendors
- Transparency in scoring rationale
- Appeals and reconsideration process
- Audit trail for scoring changes
- Reporting risk posture to leadership
Module 9. Stakeholder Communication and Alignment
Engage legal, compliance, technical, and program teams with tailored messaging.
12 chapters in this module
- Messaging for procurement teams
- Compliance officer briefing templates
- Technical deep dive facilitation
- Executive summary frameworks
- Program manager integration guidance
- Public affairs and transparency prep
- Inter-agency collaboration models
- Vendor negotiation support materials
- Oversight body reporting formats
- Media inquiry preparedness
- Community update templates
- Internal training modules
Module 10. Post-Implementation Monitoring and Oversight
Establish ongoing review practices to maintain risk alignment after contract signing.
12 chapters in this module
- Performance monitoring dashboards
- Compliance drift detection
- Model update impact assessment
- Incident reporting protocols
- Annual reassessment cycles
- Stakeholder feedback loops
- Regulatory change alerts
- Penetration testing coordination
- Third-party audit scheduling
- Remediation tracking system
- Escalation to termination pathways
- Lessons learned integration
Module 11. Cross-Jurisdictional and Multi-Agency Programs
Adapt assessment frameworks for collaborative, multi-entity initiatives.
12 chapters in this module
- Harmonizing risk criteria across agencies
- Lead evaluator coordination models
- Shared playbook deployment
- Centralized vs. decentralized oversight
- Interoperability requirements
- Data sharing governance
- Joint audit preparation
- Conflict resolution frameworks
- Standardized reporting formats
- Funding alignment across partners
- Change management in federated environments
- Exit coordination for multi-party contracts
Module 12. Building Internal Capacity and Playbook Evolution
Scale capability across teams and keep assessment practices current.
12 chapters in this module
- Training new evaluators
- Mentorship and certification paths
- Lessons learned integration
- Playbook version control
- Feedback from failed bids
- Benchmarking against industry leaders
- Regulatory horizon scanning
- Innovation pilot integration
- Cross-sector adaptation strategies
- Knowledge management systems
- Updating templates and tooling
- Leadership reporting on program maturity
How this maps to your situation
- Assessing a new AI vendor for a federal health initiative
- Re-evaluating an existing vendor after a regulatory update
- Leading a cross-agency procurement effort
- Responding to oversight body inquiries about AI use
Before vs. after
Before
Unstructured evaluations, inconsistent scoring, and reactive compliance responses slow procurement and increase exposure.
After
A repeatable, audit-ready process for assessing AI vendors that accelerates decisions while strengthening governance.
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 36 hours total, designed for completion over six weeks with two 90-minute sessions per week.
If nothing changes
Continuing with ad-hoc assessments risks non-compliance, rework, and loss of stakeholder trust in AI-driven programs.
How this compares to the alternatives
Unlike generic AI ethics courses or academic overviews, this course delivers implementation-grade tooling specifically for public-sector procurement teams, combining regulatory awareness, technical due diligence, and operational playbooks used in real programs.
Frequently asked
Who is this course designed for?
Business and technology professionals responsible for AI procurement, risk governance, compliance, or digital transformation in public-sector or regulated environments.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is there a money-back guarantee?
Yes, 30-day money-back guarantee if the course does not meet your expectations.
$199 one-time. Approximately 36 hours total, designed for completion over six weeks with two 90-minute sessions per week..
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