AI Vendor Evaluation Template

Choosing the right AI vendor is one of the highest-stakes decisions in your AI journey. Get it wrong and you waste months, blow budgets, and erode organizational trust in AI. This template provides a structured approach to evaluating vendors so you can make confident, defensible decisions.

Evaluation Category 1: Core Capabilities

Does the vendor actually solve your problem? Evaluate feature completeness, accuracy benchmarks, and whether the solution handles your specific use case out of the box or requires extensive customization. Ask for live demos with your data, not canned presentations.

• Feature alignment with your requirements
• Accuracy and performance benchmarks
• Customization vs. out-of-the-box readiness
• Model transparency and explainability

Evaluation Category 2: Security & Compliance

Your data is your most sensitive asset. Evaluate the vendor's data handling practices, encryption standards, SOC 2 compliance, and whether your data is used for model training. This is non-negotiable, especially in regulated industries.

• SOC 2 Type II certification
• Data residency and encryption policies
• Opt-out of model training with your data
• Industry-specific compliance (HIPAA, GDPR, etc.)

Evaluation Category 3: Integration & Support

The best AI tool in the world is worthless if it does not integrate with your existing stack. Evaluate API quality, existing integrations, implementation timeline, and the vendor's support model. Ask about dedicated customer success resources.

Evaluation Category 4: Pricing & Total Cost

Look beyond the per-seat price. Calculate total cost of ownership including implementation, training, ongoing support, and potential lock-in costs. Ask about volume discounts and how pricing scales as usage grows.

Evaluation Category 5: Vendor Viability

AI is a fast-moving space. Evaluate the vendor's financial stability, funding, customer base, and product roadmap. You need confidence they will still be around and innovating in 2-3 years.