Skip to content

AI Vendor Evaluation Checklist

Purpose: Assess third-party AI suppliers for safety, compliance, security and standards alignment Audience: Procurement teams, IT leaders, risk managers, compliance officers | Time: 1-2 hours per vendor

Selecting the right AI vendor is critical for managing risk and ensuring safe, productive AI use. This checklist helps Australian organisations assess AI vendors against industry standards and legal requirements.

Using this evaluation process supports stronger AI governance by:

  • Reducing risks from unverified or non-compliant AI products
  • Ensuring transparency, accountability and security in AI procurement
  • Building trust with customers, regulators and partners

When to Use This Checklist

  • 🆕 Onboarding a new AI vendor
  • 🔄 Renewing or extending existing vendor contracts
  • ⬆️ Reviewing AI products that have undergone significant updates

Work through each section, seek evidence from the vendor and record your findings. Where needed, consult legal, risk, or IT experts before approving an AI vendor.

Build vs Buy: Before You Evaluate

Before evaluating vendors, confirm that buying is the right approach.

Almost always buy for first AI uses

For Australian SMEs, buying pre-built AI solutions is usually the right choice:

  • Faster to pilot: Weeks vs months to get started
  • Lower costs: $200-3,000/month subscription vs $30,000-100,000+ development
  • Easier to change: Cancel subscription vs abandon custom code
  • Vendor handles updates: Security patches, model improvements, compliance updates
  • Market proven: Other organisations have tested and refined the approach

Consider building only when:

  • Your use case is truly unique to your industry with no off-the-shelf options
  • You have existing development capability with spare capacity (not hiring contractors)
  • You've thoroughly evaluated off-the-shelf tools and they genuinely don't fit
  • You're past the pilot stage with clear, proven requirements from successful vendor tools
  • You have budget for both initial development and ongoing maintenance

Reality check: Even large organisations with substantial tech teams often buy rather than build for AI tools. The technology is evolving too quickly and maintaining custom AI systems requires significant ongoing effort.

Critical Red Flags

Stop or Proceed with Extreme Caution If a Vendor:

1. Can't explain how their AI works

Gets defensive when asked about decision-making, hides behind "proprietary algorithms," or can't explain it in plain language.

Why it matters: You need to understand AI behaviour well enough to know when to trust it and how to explain it to regulators or customers.

2. Makes unrealistic promises

Claims "100% accuracy," "fully automated from day one," "no human oversight needed," "works perfectly out of the box," or "guaranteed ROI in 30 days."

Why it matters: AI systems have limitations and require tuning. Unrealistic promises indicate the vendor doesn't understand their own technology or is being deliberately misleading.

3. Dismisses your concerns

Brushes off questions about bias, treats privacy concerns as paranoia, dismisses error rates as "not a real problem," or suggests your requirements are unreasonable.

Why it matters: If vendors won't take your concerns seriously during sales, they definitely won't during implementation or support.

4. Has no Australian customer references

Cannot provide Australian customers, especially in your sector. Only offers international references.

Why it matters: Australian regulatory environment, business practices and language nuances matter. Vendors without Australian experience may not understand local compliance requirements.

5. Is unclear about data handling

Vague about data storage location, can't explain who accesses your data, unclear about data usage (training models? sharing?), or has no clear data export/deletion process.

Why it matters: Data sovereignty, privacy compliance and vendor lock-in risks all depend on clear data handling terms.

6. Demands heavy lock-in with no trial

Requires 12+ month contracts with no trial option, high switching costs or data export fees, proprietary data formats, or no clear cancellation process.

Why it matters: You need room to learn and adjust. Long lock-in periods create risk, especially for first AI uses.

7. Lacks relevant certifications

No ISO 27001, SOC 2, or industry-specific certifications relevant to your needs.

Why it matters: These certifications indicate basic security and privacy practices are in place. For sectors like health or finance, specific certifications may be required.

AI Vendor Evaluation Checklist (Template)

Vendor Name: ____________________

Product/Service: ____________________

Date of Evaluation: ____________________

Vendor Evaluation Summary (Quick Scoring Table)

Category Score (1–5) Notes / Evidence
Vendor Information
Product/Service Description
Compliance & Certifications
Data Governance
Security Practices
Model Development & Testing
Human Oversight & Support
Incident Management
Contractual Safeguards
References & Track Record
Overall Risk Rating

Scoring guidance:

  • 1 = Very weak or not demonstrated
  • 3 = Adequate with some gaps
  • 5 = Strong evidence and fully compliant

Additional Evaluation Criteria:

Category Score (1–5) Notes / Evidence
Financial Stability
Vendor Lock-in Risk
Integration Capabilities
Total Cost of Ownership
Proof of Concept Results
Exit Strategy Feasibility

Detailed Evaluation Sections

1. Vendor Information

Record vendor details including name, ABN/ACN, headquarters, key contacts and years in operation.

Key questions:

  • How long has the vendor been operating?
  • Do they have an Australian presence or local support?
  • Who are their key executives and technical contacts?

Sources: ASIC requirements; Supplier Due Diligence Standards

2. Product/Service Description

Outline the AI products or services provided, including version numbers and intended use.

Key questions:

  • What exactly does the AI do and what are its limitations?
  • What decisions does it make and which require human review?
  • What happens when it's uncertain or makes an error?
  • Can you show us a realistic demo with our type of data?

Sources: Guardrail 1; Australian AI Ethics Principle: Transparency

3. Compliance & Certifications

List certifications (ISO/IEC 23894, ISO/IEC 42001, SOC 2) and confirm regulatory compliance.

Key questions:

  • What security and privacy certifications do you hold?
  • How does the tool comply with Australian Privacy Principles?
  • Do you have customers in [your sector] in Australia?
  • How do you handle Australian regulatory updates?

Sources: Guardrail 7; ISO/IEC 42001

4. Data Governance

Check vendor policies on data handling, privacy protection, IP safeguards and data provenance.

Key questions:

  • Where is data stored? (Australian data centres preferred for sensitive data)
  • Who can access our data?
  • How is our data used? (Training models? Shared with others?)
  • What's the data export and deletion process?
  • What happens to our data if we cancel the service?

Sources: Privacy Act 1988 (APPs); Guardrails 4 & 7

5. Security Practices

Assess cybersecurity measures, vulnerability management and penetration testing frequency.

Key questions:

  • What security measures protect our data?
  • How often do you conduct security audits and penetration testing?
  • What's your incident response process for security breaches?
  • Do you comply with Australian Cyber Security Centre guidelines?

Sources: Guardrail 5; ACSC Essential Eight

6. Model Development & Testing

Request information on training data, bias mitigation, validation and explainability features.

Key questions:

  • How was the AI model trained and on what data?
  • What testing have you done for bias, accuracy and reliability?
  • Can we audit the AI's decisions or see how it reached a conclusion?
  • How do you handle model updates? (Testing before production)

Sources: Guardrails 6 & 9; NIST AI RMF

7. Human Oversight & Support

Review the level of human oversight in operations, escalation paths and customer support availability.

Key questions:

  • What support do you offer for Australian customers? (Time zones and response times)
  • What's included in training and onboarding?
  • What human oversight is built into the system?
  • What are your escalation paths for critical issues?

Sources: Guardrail 8; Australian AI Ethics Principle: Accountability

8. Incident Management

Confirm the vendor's process for incident reporting, investigation and resolution timelines.

Key questions:

  • What's your process for reporting and resolving incidents?
  • What are typical response and resolution times?
  • How do you communicate with customers during incidents?
  • Can you provide examples of how you've handled past incidents?

Sources: Guardrail 10; ISO/IEC 27035

9. Contractual Safeguards

Review liability clauses, service-level agreements, IP ownership terms and termination rights.

Key questions:

  • What's the total cost including setup, training and ongoing fees?
  • What's the minimum contract term? Is there a trial period?
  • Can we pilot before committing to a long contract?
  • What are the exit costs or data export fees?
  • What liability do you accept for errors or failures?

Sources: Australian Consumer Law; Contract Law

10. References & Track Record

Check customer references, case studies and the vendor's history of regulatory compliance.

Key questions:

  • Can you provide Australian customer references in our sector?
  • What case studies can you share of successful implementations?
  • Have you had any regulatory violations or serious incidents?
  • What's your customer retention rate?

Sources: Supplier Risk Management Best Practice

11. Integration & Technical Capability

Evaluate the vendor's ability to integrate with your existing technology stack and assess technical documentation quality.

Key questions:

  • How does this integrate with our existing systems? (Microsoft 365, Salesforce, etc.)
  • What's the quality of your API documentation?
  • How long until we can run a pilot?
  • What visibility do we have into system performance?
  • Can we adjust the AI's behaviour or rules?

Assessment criteria:

  • API documentation quality and completeness
  • Compatibility with existing systems verified
  • Data migration requirements assessed
  • Performance benchmarks established
  • Scalability limitations understood

Sources: IT Integration Best Practice; Vendor Due Diligence Standards

12. Financial & Commercial Assessment

Verify vendor financial stability and evaluate total commercial impact of the partnership.

Key considerations:

  • Vendor financial health verified (credit check, annual reports)
  • Total cost of ownership calculated (licensing, implementation, maintenance)
  • ROI projections documented
  • Payment terms and conditions reviewed
  • Penalties for non-performance defined

Sources: Financial Due Diligence; Procurement Best Practice

13. Proof of Concept / Pilot Phase

Define success criteria and parameters for a time-limited pilot to validate vendor claims before full commitment.

Pilot checklist:

  • Pilot success criteria defined
  • Limited data set for testing prepared
  • Evaluation timeline established (typically 30–90 days)
  • Rollback plan documented
  • Cost of pilot agreed (if applicable)

Sources: Change Management Best Practice; AI Implementation Guidelines

14. Documenting & Storing Results

Maintain an audit trail and governance record for all vendor evaluation decisions.

Documentation requirements:

  • Record all responses and supporting evidence provided by the vendor
  • Capture notes on any identified risks or gaps and how they will be managed
  • Store completed checklists in a secure repository (e.g. risk register, governance system, or procurement file)
  • Review and update the checklist regularly, especially when vendors release new versions or change their business practices
  • Cross-reference this checklist with your organisation's AI Risk Assessment and Incident Reporting processes for a complete governance record

Sources: Governance and Compliance Standards; Record-Keeping Best Practice

Alignment with Australian Standards

Standards Compliance

✓ Share essential information — Sections 1-2 ("Vendor Information" and "Product/Service Description") capture essential information about external AI systems

✓ Measure and manage risks — Sections 5 and 12 ("Security Practices" and "Financial & Commercial Assessment") help measure vendor-related risks

✓ Test and monitor — Section 6 ("Model Development & Testing") asks for evidence of vendor testing and validation processes

✓ Guardrail 8 – Supply chain accountability — Entire checklist implements supply chain accountability, ensuring vendors meet safety standards

✓ Guardrail 3 – Data protection & security — Sections 4-5 ("Data Governance" and "Security Practices") verify vendors have appropriate data and security controls

✓ Guardrail 6 – Testing & assurance — Section 6 checks vendors have adequately tested models for bias, robustness and accuracy

✓ Guardrail 1 – Accountability — Section 9 ("Contractual Safeguards") ensures legal and operational accountability is defined in vendor contracts

Next Steps

Connect this evaluation to broader adoption work:

Disclaimer & Licence

Disclaimer: This template provides best practice guidance for Australian organisations. SafeAI-Aus has exercised care in preparation but does not guarantee accuracy, reliability, or completeness. Organisations should adapt to their specific context and may wish to seek advice from legal, governance, or compliance professionals before formal adoption.

Licence: Licensed under Creative Commons Attribution 4.0 (CC BY 4.0). You are free to copy, adapt and redistribute with attribution: "Source: SafeAI-Aus (safeaiaus.org)"