Reading the Team Dashboard
The dashboard shows you readiness distribution, member scores, dimension breakdowns, and coaching briefs. Read the signal fast. Identify strong operators. Spot gaps. Make rollout decisions.
What to look at first
Start with the readiness distribution chart. This shows how scores spread across your team. Look for clusters. If most people score 60-75, you have a solid middle tier that needs structured support. If you see a few people at 85+ and everyone else below 50, you have champions and a gap. Next, check the dimension breakdown. Maybe your team is strong on AI Delegation & Direction but weak on Verification & Judgment. That tells you where training effort should go. Then look at individual member scores. Sort by overall score to find your strongest operators. These are not always the loudest advocates. Sometimes the person who talks about AI the least is the one who actually knows how to use it.
- •Readiness distribution shows the shape of your team capability. Tight cluster means consistency. Wide spread means you need tiered support.
- •Dimension breakdown (AI Delegation & Direction, Technical & Model Literacy, Practical Implementation, Verification & Judgment, Workflow, Skills, Agents & Harnesses) shows where the team is collectively strong or weak. Use this to prioritize training topics.
- •Individual scores identify champions (high across all dimensions), specialists (strong in one or two areas), and people who need more support before touching production AI.
- •Member detail pages have coaching briefs (AI-generated summaries that translate scores into actionable guidance), translated scores (what each score level means in business terms), and section breakdowns (how they performed in each part of the assessment).
- •Teams can have members with scores from both rubric generations. Dashboards mark 2026-badged scores. Comparing a 2025 score to a 2026 score is apples to oranges. For clean team comparisons, encourage members to reassess on the current rubric.
How to act on the data
Do not just read the dashboard and move on. Make decisions. Who should lead the first AI workflow design. Who should be grouped together for a pilot project. Who needs coaching before they touch production tools. Who should wait. The dashboard gives you the signal. You turn it into operational plans.
- •Identify champions: People who score 80+ across all five dimensions should lead workflow design, train others, and set standards for production AI use.
- •Group by readiness tier: High performers can pilot new tools immediately. Middle tier needs structured practice and guardrails. Low performers should wait or get one-on-one coaching before joining broader rollout.
- •Spot dimension-specific gaps: If someone scores high on AI Delegation & Direction but low on Verification & Judgment, they can use tools but need coaching on when to push back on AI outputs. If someone scores high on Technical & Model Literacy but low on Practical Implementation, they understand the theory but need hands-on support.
- •Use coaching briefs to personalize follow-up: The AI-generated briefs on member detail pages give you talking points for one-on-one conversations. Do not treat them as gospel but use them as a starting point for targeted coaching.
- •Reassess when context changes: If you roll out new tools, new workflows, or new training, reassess key people to see if capability has changed. The assessment is not a one-time snapshot. Use it as a baseline and measure growth.