AI Vendor Evaluation Scorecard

Summary

This scorecard helps you pick AI tools that actually fit your workflows without quietly creating data, cost, or adoption problems. It is built for small teams who need speed, but still want sane guardrails around privacy, access, and reliability. Pair it with the Small Business AI Adoption Playbook for rollout planning and the LLM Safety Review Checklist for data handling. Use it in 15 minutes before you swipe the card.

Who it is for

Solo founders choosing AI tools for research, marketing, support, and ops.
Small businesses adding AI to existing workflows without hiring a team.
Operators and engineers evaluating vendors for internal use.
Job seekers and freelancers deciding what to learn and what to ignore.

What you get

A simple scoring model you can run in one meeting.
Risk flags that tell you when to slow down or ask for proof.
Decision rules: when to buy now, pilot, or walk away.
Copy-paste questions you can send to any vendor in one email.
A one-page summary format you can share internally.

Steps

Define the job to be done.
Write a single sentence: “We want this tool to ______ so we can ______.”
Pick one primary workflow only. Do not evaluate a Swiss Army knife for five different jobs.
Classify the data risk.
Mark what will touch the tool:
- Public data only
- Internal but non-sensitive
- Sensitive (customer data, contracts, HR, source code, financials)
If it is sensitive, you need hard answers on retention, training, access, and export controls.
Score the vendor in 5 categories.
Give 0 to 5 points per category (25 total):
- Workflow fit
- Security and privacy
- Cost and pricing risk
- Reliability and support
- Exit plan and portability
Run a 30-minute pilot test.
Use 3 realistic tasks. Time them. Capture outputs. Track failure cases.
If the tool fails on your core tasks, stop. Do not “hope it improves later.”
Apply the decision rules.
- 20–25: buy now, ship it into the workflow
- 14–19: pilot for 1–2 weeks with limits
- 0–13: do not buy, revisit after requirements change
Implement with guardrails.
Define who can use it, what data is allowed, where outputs are stored, and how you measure value.

Templates

Copy, fill, send. Use this before you buy any AI tool.

Template 1: 5-category scorecard

Quick scoring model. 0–5 each. 25 total.

AI Vendor Scorecard (0–5 each, 25 total)
      
      1) Workflow fit (0–5)
      - Does it solve the exact job to be done?
      - Does it plug into our tools without friction?
      Score: __ /5
      Notes:
      
      2) Security and privacy (0–5)
      - Data retention policy: __
      - Training on our data: yes/no/unknown
      - Access controls (SSO, RBAC): __
      - Audit logs: yes/no
      Score: __ /5
      Notes:
      
      3) Cost and pricing risk (0–5)
      - Pricing model (seat, usage, tier): __
      - Worst-case monthly cost estimate: __
      - Hidden costs (overages, add-ons): __
      Score: __ /5
      Notes:
      
      4) Reliability and support (0–5)
      - Uptime history / status page: __
      - Support response expectations: __
      - SLA available: yes/no
      Score: __ /5
      Notes:
      
      5) Exit plan and portability (0–5)
      - Can we export data easily?
      - Can we delete data fully?
      - How hard is it to replace?
      Score: __ /5
      Notes:
      
      Total: __ /25
      Decision: Buy now / Pilot / Pass

Template 2: Vendor questions email

Send this before a pilot. Forces clear answers.

Subject: Quick questions before we pilot
      
      Hi [Vendor],
      
      We are evaluating [Tool] for [use case]. Before we pilot, can you confirm:
      
      1) Data retention: how long are prompts and uploads stored by default?
      2) Training: is our data used to train any models? If no, where is that stated?
      3) Access controls: do you support SSO and role-based access?
      4) Auditability: do you provide audit logs or usage logs?
      5) Export and deletion: can we export all data and permanently delete it?
      6) Pricing: what triggers overages and what is the worst-case cost model?
      
      Thanks,
      [Name]

Template 3: 3-task pilot plan

Run 3 realistic tasks in 30 minutes. Time it.

30-minute pilot plan (3 tasks)
      
      Task 1 (core workflow):
      - Input:
      - Expected output:
      - Pass criteria:
      - Time saved estimate:
      
      Task 2 (edge case):
      - Input:
      - Expected output:
      - Pass criteria:
      
      Task 3 (failure mode):
      - Input:
      - What could go wrong:
      - Pass criteria:
      
      Result:
      - Keep / Pilot longer / Reject

Common mistakes

Buying the tool before the workflow is defined. You end up paying for features you do not use.
Ignoring data classification. You cannot “undo” sensitive data exposure later.
Trusting demos. Only your real tasks count.
No cost ceiling. Usage-based tools can surprise you fast. Estimate worst-case.
No exit plan. If you cannot export and delete, you do not own your workflow.