Procurement Guide
AI Vendor Selection Scorecard (2026) - Procurement Evaluation
Vendor selection needs objective scoring across capability, pricing, security, and support. This scorecard provides weighted criteria and comparison framework for procurement teams.
Guide toolkit
Copy or download the checklist
Turn this guide into a working brief for AI Vendor Shortlist Scorecard.
Implementation Steps
- Define scoring criteria: capability (40%), pricing (25%), security (20%), support (15%).
- Rate each vendor on model quality, latency, throughput, and feature coverage.
- Compare pricing: per-token rates, volume discounts, commitment tiers, and hidden costs.
- Evaluate security: SOC 2 compliance, data handling, access controls, and incident response.
Frequently Asked Questions
What criteria should AI vendor selection use?
AI vendor selection criteria: model capability (quality, latency, throughput), pricing transparency (per-token, volume discounts), security compliance (SOC 2, GDPR), support SLA (response time, escalation), and roadmap alignment.
How to compare AI vendor pricing models?
Compare AI pricing by: per-token rates across models, volume discount tiers, commitment minimums, SLA credit provisions, inference vs training costs, and hidden fees like API overhead or minimum usage.
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- Provider and model split recommendations
- Budget guardrail design by traffic stage
- KPI plan for spend, quality, and conversion