AI Interviews
Some of the most important evidence in consulting isn't written down — it lives in stakeholders' heads. AI interviews capture that conversationally: a topic-based interview collects answers from a stakeholder and turns them into citable evidence for the engagement.
This page covers AI interviews in the assessment/evidence workflow. For the feature itself — what the AI Interviewer does, its inputs, processing, and outputs — see the AI Features section.
Who can access
Members of the engagement team can launch interviews. Interviews are designed to be completed by stakeholders, including people outside the core team.
How it works
An AI interview is organized around topics relevant to the assessment. The stakeholder answers conversationally, and their responses become evidence the engagement can retrieve and cite — the same way an uploaded document would. This means tacit knowledge ends up grounded and traceable, not just noted.
You can launch AI interviews from two places:
- Diagnose — as part of the evidence step before running an assessment.
- Data & Evidence → Collect data — topic-based collection at any time.
Step by step
- From Diagnose (section 3) or Data & Evidence → Collect data, start an AI interview.
- Choose the topics to cover.
- Share it with the stakeholder to complete.
- As responses come in, they become evidence on the engagement.
- Run or re-run your assessment so the new evidence is included.
Best practices
- Use interviews to fill gaps. When an assessment shows Not grounded answers, an interview on that topic is often the fastest way to close the gap.
- Target the right people. Direct each interview at the stakeholder who actually holds the knowledge.
- Re-run after interviewing. New interview evidence only affects results on the next run.
Common errors
| Symptom | Likely cause | What to do |
|---|---|---|
| Interview evidence not reflected | Assessment ran before responses came in | Re-run the assessment after the interview completes |