AI Vendor Evaluation Scorecard

Overview

Traditional vendor evaluation focuses on features, price, and support. AI vendor evaluation requires additional dimensions: how they handle your data, whether they test for bias, how they explain AI outputs, and what happens when models fail. Missing these factors in evaluation creates risks that surface after contracts are signed.

This scorecard provides a complete AI vendor evaluation framework. It covers both traditional vendor criteria and AI-specific requirements, with weighted scoring that reflects the relative importance of each factor.

What's Inside

Sheet 1: Vendor Scorecard

• Vendor information capture
• 7 evaluation categories with weighted criteria:
  • Technical Capabilities (37 points): Performance, scalability, integration, customization, updates
  • Security & Privacy (43 points): Encryption, certifications, residency, access controls, pen testing
  • AI Governance (40 points): Transparency, explainability, bias testing, human oversight, version control
  • Data Handling (40 points): Data usage policies, training restrictions, retention, deletion
  • Compliance & Legal (36 points): Regulatory compliance, AI regulations, IP ownership, indemnification
  • Support & Service (32 points): SLAs, documentation, training, escalation
  • Commercial (31 points): Pricing, flexibility, contract terms, exit provisions
• Auto-calculated weighted scores
• Notes/evidence column for documentation

Sheet 2: Vendor Comparison

• Side-by-side comparison of up to 3 vendors
• Category scores transferred from individual scorecards
• Auto-determined winner by category
• Overall score comparison
• Clear visual of strengths/weaknesses

Sheet 3: Scoring Guide

• Score definitions (1-5) with descriptions
• 5 = Excellent: Exceeds requirements, best-in-class
• 4 = Good: Fully meets requirements
• 3 = Acceptable: Meets minimum, some gaps
• 2 = Below Standard: Significant gaps
• 1 = Unacceptable: Does not meet requirements
• Approval thresholds: 4.0+ (Approve), 3.0-3.9 (Conditional), 2.0-2.9 (Caution), <2.0 (Reject)

Who This Is For

• Procurement Teams selecting AI vendors
• IT/Technology Leaders evaluating AI tools
• Security Teams assessing vendor security
• Legal/Compliance reviewing AI vendor terms
• AI Governance Teams ensuring vendor oversight

Why This Resource

Feature comparisons miss what matters for AI. This scorecard ensures you evaluate AI-specific factors (data usage, bias testing, explainability) alongside traditional criteria. Weighted scoring reflects that security and governance matter more than commercial terms for AI vendors.

The comparison matrix enables objective vendor selection conversations backed by documented scores.

FAQ

Q: Can we adjust the weights?

A: Yes. Weights reflect general AI vendor priorities, but your organization may weight certain factors differently (e.g., heavily regulated industries may increase Compliance weight). Adjust to match your risk tolerance.

Q: Who should complete the evaluation?

A: Cross-functional input produces better evaluations: IT/Engineering for Technical, Security team for Security & Privacy, Legal for Compliance, Procurement for Commercial. Consolidate scores with discussion where evaluators disagree.

Q: What about vendors who won't answer questions?

A: Unwillingness to provide information is itself informative. Score "Unable to verify" as 2 (below standard) and document in notes. Significant gaps in transparency should raise concerns.