Adoption metrics count usage. They miss discernment.
| Adoption metric | The capability question behind it |
|---|---|
| Seats active | Are people framing the problem before they prompt? |
| Prompts per user | Do they check output against evidence, or accept it? |
| Time saved | Do they catch a confident error under time pressure? |
| User satisfaction | Do they escalate when uncertainty is high? |
| Agent tasks completed | Does a named person own, and defend, the decision? |
Readiness you can show the board.
- An AI workforce readiness baseline in 30 days, measured in behavior rather than self-report.
- Evidence of human oversight whether people verify consequential output and escalate uncertainty.
- AI discernment knowing when to trust, check or override AI, tracked over time.
- Human-agent collaboration delegation, context and accountability as agents take on work.
- Responsible AI as observed behavior what people actually do, next to what policy asks.
- Less offloading of judgment people practice forming a view before they read the output.
Specification, Verification, Conviction.
Three questions that decide whether AI makes a team sharper or faster at being wrong.
Specification
Can people define what matters before asking AI, or anyone else, to act?
- Problem framing
- Clear communication
- Context setting
- Constraint definition
- Asking the right question
- Signal from noise
Without it: vague in, vague out. AI answers the question it was given, not the one that mattered.
Explore specification →Verification
Can people tell whether an answer, recommendation or assumption holds up?
- Critical thinking
- Evidence evaluation
- Assumption testing
- Contradiction detection
- Systems thinking
- Second-order effects
- Recognizing uncertainty
Without it: review becomes a rubber stamp on generated text.
Explore verification →Conviction
Can people make and defend a justified decision, and still update when the evidence changes?
- Decision quality
- Leadership judgment
- Persuasion
- Negotiation
- Accountable action
- Updating on evidence
Without it: the model decides, and nobody owns the call.
Explore conviction →Built to pass security review.
Runs in the browser with nothing to install. No integration is required. Each client runs in its own isolated environment and client data never mixes.
Evidence from production
Figures from production, measured against each person's own opening baseline.
Measure whether your workforce can work with AI responsibly.
Comparing options? See how RCM ThinkLabs compares with Workera, Viva Insights and other alternatives.