AI Evaluation Evidence Pack — Essentials Edition

A practical starting point for asking better questions about AI evaluation evidence.

AI evaluation results can be difficult to interpret, especially when you're responsible for project decisions rather than conducting the technical evaluation yourself.

The AI Evaluation Evidence Pack — Essentials Edition introduces a set of questions and checks to help you examine the evidence behind an AI decision and identify areas that need further investigation.

What's inside:

• Five Questions: A framework for examining what is being measured, how it was measured, whether the result can be trusted, whether it reflects the intended use case, and what decision it supports.

• Six Key Areas: Questions to explore measurement, data, evaluation design, analysis, validity, and real-world applicability.

• Questions for Your Role: Selected prompts for six perspectives, from Product and Program Management to Research, Operations, and Leadership.

• Quick Checks: Nine checks covering the Learning Loop, Human Evaluation & Inter-Rater Reliability, and Validity & Real-World Fit.

• Record the Call: A worksheet for capturing the evidence, key gaps, decision, and ownership.

Who it's for: Product, program, and technical project managers; data and research leads; Chiefs of Staff; operations leaders; and others accountable for AI project outcomes.

How to use it: Bring these questions to an AI project review, use them to prepare for a conversation with an evaluation team, or identify what you still need to know before making a decision.

Want to go deeper?

The AI Evaluation Evidence Pack — Complete Edition expands these foundations into a full working toolkit, with six detailed role guides, three step-by-step session guides and companion worksheets, a worked example, and a comprehensive Decision Record.

The Essentials Edition helps you get started. The Complete Edition helps you work through the process in greater depth.

Better questions. Smarter decisions.