Why you need this
Choosing the wrong AI vendor is expensive. You waste months integrating a tool that doesn't scale, lacks critical features, or fails compliance requirements. Then you're stuck—migrating to another vendor costs even more.
The problem: Evaluating AI vendors is overwhelming. Marketing materials all promise the same capabilities. Without objective criteria, teams make emotional decisions, fall for sales pitches, or pick tools that work for competitors but not their use case.
This scorecard solves that. It provides a weighted, standardized framework for objectively evaluating and comparing AI vendors across 30+ criteria—turning vendor selection from guesswork into data-driven decision-making.
Perfect for:
- Procurement teams evaluating AI tool vendors
- IT leaders comparing LLM providers and platforms
- Product managers selecting AI features for integration
- CTOs making build vs. buy vs. partner decisions
What's inside
Comprehensive Evaluation Framework
Capability Assessment (35% weight):
- Core AI features (accuracy, speed, supported use cases)
- Model performance benchmarks
- Language and modality support
- Customization and fine-tuning options
- API capabilities and flexibility
- Integration with existing systems
- Scalability and performance under load
Security & Compliance (25% weight):
- Data privacy and encryption standards
- Compliance certifications (SOC 2, ISO 27001, GDPR, HIPAA)
- Data residency and sovereignty options
- Access controls and authentication
- Audit logging and monitoring
- Incident response and SLAs
- Vendor security practices and track record
Pricing & Commercial Terms (20% weight):
- Pricing model (per user, per token, per API call, flat rate)
- Total cost of ownership (TCO) estimation
- Volume discounts and commitment tiers
- Contract flexibility (monthly vs. annual)
- Hidden costs (implementation, training, support)
- Price predictability and stability
- Free tier or trial availability
Support & Reliability (10% weight):
- Documentation quality and completeness
- Technical support availability (hours, SLA, channels)
- Community and developer resources
- Implementation assistance
- Training and onboarding programs
- Uptime guarantees and historical reliability
- Incident communication and transparency
Vendor Viability (10% weight):
- Company financial stability
- Market position and momentum
- Product roadmap alignment with your needs
- Customer references and case studies
- Lock-in risk and exit strategy
- Innovation track record
- Partnership ecosystem
Scoring Methodology:
For Each Criterion:
- Rating scale: 1-5 (1 = Poor, 3 = Adequate, 5 = Excellent)
- Weight assignment: Customize weights based on your priorities
- Evidence required: Specific data to support each score
- Weighted score calculation: Rating × Weight = Category score
Comparison Matrix:
- Side-by-side vendor comparison
- Visual score charts
- Strengths and weaknesses summary
- Final recommendation with justification
Decision Support Tools:
Must-Have vs. Nice-to-Have:
- Criteria classification worksheet
- Deal-breaker identification
- Minimum viable requirements checklist
Risk Assessment:
- Vendor lock-in evaluation
- Migration difficulty scoring
- Compliance gap analysis
- Business continuity planning
Total Cost of Ownership Calculator:
- Direct costs (licensing, usage)
- Indirect costs (implementation, training, maintenance)
- Opportunity costs (time to value)
- 3-year TCO projection
Each Scorecard Includes:
- ✓ Pre-filled evaluation criteria
- ✓ Customizable weights
- ✓ Vendor comparison matrix
- ✓ Question templates for vendor demos
- ✓ Reference check guide
How to use it
- Requirements gathering — Define must-haves before vendor research
- Vendor demos — Use scorecard during demonstrations to evaluate objectively
- Stakeholder alignment — Share weighted criteria to build consensus
- Final decision — Present data-driven recommendation to leadership
Example evaluation
Scenario: Choosing LLM Provider for Customer Support Chatbot
Must-Have Requirements:
- GDPR compliance (healthcare customers)
- 99.9% uptime SLA
- Multi-language support (English, Spanish, French)
- Cost under $0.01 per interaction
Vendor Comparison (Sample Scores):
| Criterion | Weight | Vendor A | Vendor B | Vendor C |
|---|---|---|---|---|
| Capability | 35% | 4.2 | 4.8 | 3.9 |
| Security | 25% | 4.5 | 4.0 | 5.0 |
| Pricing | 20% | 3.0 | 4.5 | 4.0 |
| Support | 10% | 4.0 | 3.5 | 4.5 |
| Viability | 10% | 5.0 | 4.0 | 3.0 |
| Total Score | 100% | 4.1 | 4.3 | 4.2 |
Decision: Vendor B scores highest (4.3), excels in capabilities and pricing, meets all must-haves.
Concerns: Slightly lower security score—request additional compliance documentation before final decision.
Want to go deeper?
This scorecard helps you choose vendors. For broader AI decision-making:
- Resource: AI Decision Framework — When to build vs. buy
- Resource: AI Risk Assessment Template — Evaluate vendor risks
- Guide: AI at Work Basics — Understanding AI capabilities
License & Attribution
This resource is licensed under Creative Commons Attribution 4.0 (CC-BY). You're free to:
- Adapt criteria for your industry
- Share with procurement and IT teams
- Customize weights and scoring
Just include this attribution:
"AI Vendor Evaluation Scorecard" by Field Guide to AI (fieldguidetoai.com) is licensed under CC BY 4.0
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