AI Vendor Evaluation & Selection Scorecard

A defensible evaluation process with an enterprise-grade scorecard template to compare AI vendors across technical fit, security, compliance, risk, and business value—and arrive at a documented recommendation.

Follow-on / extension: best after you’ve established your baseline maturity and governance context (often via a Digital Maturity Assessment).

Request a sample scorecard/templateBook a feasibility call

Sample outputs (illustrative)

A reusable template plus redacted snapshots that show how vendor comparisons and decision logs are documented for executives, procurement, and risk teams.

  • Scorecard template with weighted criteria and evidence notes
  • Side-by-side comparison snapshot with rationale highlights
  • Risk, assumption, and decision log (owners + status)

Evaluation pillars

  • Architecture & integration fit
  • Security, privacy, and compliance
  • Governance, risk, and controls
  • Operations, support, and resilience
  • Commercials, lock-in, and economics
  • Value, adoption, and change impact

Evidence captured per vendor

  • Scored criteria with rationale (what we saw, not opinions)
  • Risks, assumptions, and open questions
  • Side-by-side comparison summary for executives
  • Recommendation and decision log for procurement/legal
Anonymized sample AI vendor scorecard template

Scorecard template (weighted criteria).

Anonymized sample AI vendor comparison snapshot

Comparison snapshot (side-by-side scores).

Anonymized sample AI vendor decision log

Risk and decision log (owners + status).

What you get

The engagement combines a structured scorecard, facilitated workshops, and evidence-backed comparisons so you can move from longlists to a defensible vendor selection.

  • A tailored AI vendor evaluation scorecard covering architecture, security, compliance, operations, governance, and commercial terms.
  • Facilitated working sessions to define scenarios, criteria, and weightings that reflect your real requirements and risk appetite.
  • Structured evaluation of shortlisted vendors using common criteria and evidence rather than ad hoc opinions.
  • Side-by-side comparisons and a clear recommendation that can stand up to scrutiny from procurement, legal, and audit.
  • A reusable scorecard and playbook you can apply to future AI vendor decisions.

Who this is for

  • CIO, CDO, Head of AI / ML / Data
  • Organizations running RFPs or shortlisting AI platforms, copilots, model‑hosting, or governance solutions
  • Teams needing a transparent, defensible way to compare AI vendors across functions
  • Enterprises that want to avoid lock‑in, hidden risks, and internal politics in vendor decisions

How the scorecard is used

A pragmatic sequence from requirements to recommendation, designed to work alongside your procurement and legal processes.

1. Frame & criteria

Align on use cases, risk posture, and constraints. Define evaluation pillars and weighting across security, compliance, technical fit, and value.

2. Assess vendors

Apply the scorecard to shortlisted vendors using documentation, demos, and (where relevant) pilots, capturing evidence against each criterion.

3. Decide & document

Produce a clear comparison, recommendation, and rationale that can be shared with executives, governance forums, procurement, and legal.

See whether this matches your next AI vendor decision

If you’re planning an AI vendor selection or renewal, we can walk through the scorecard and see whether it fits your context.

Frequently asked questions

Key details about how the AI Vendor Evaluation & Selection Scorecard is used in practice.