Sample readout. Synthetic data for a fictional organization; not a client’s results.
AI Adoption Health
90-day readout
240
People in one department
6
Teams
240
Copilot licenses
$7,200/mo
At an assumed $30 per user per month
3 teams
1 team
1 team
1 team
Teams
| Team | People | Pattern | After-hours share of work | Meeting hours / person / week | Delivery trend | Recommended next step |
|---|---|---|---|---|---|---|
| Platform Engineering | 52 | AI Amplifiers | 12% → 10% | 9 → 7.5 | +18% | Document what changed and keep it steady. |
| Claims Operations | 48 | AI Overload | 10% → 18% | 8.5 → 12.5 | +1% | Cut standing meetings (action 1). |
| Finance Close | 30 | AI Masks | 9% → 11% | 7 → 8 | −2% | Shift recognition toward delivery (action 2). |
| Customer Support | 56 | AI Amplifiers | 6% → 5% | 6.5 → 6 | +12% | Adopt the Data & Analytics working pattern (action 3). |
| Data & Analytics | 24 | Quiet Multipliers | 8% → 7% | 6 → 5.5 | +15% | Share the working pattern with two teams (action 3). |
| Product Design | 30 | AI Amplifiers | 7% → 7% | 8 → 7 | +9% | Adopt the Data & Analytics working pattern (action 3). |
Before = the 60 days before the Copilot rollout. Now = the latest 30 days.
Estimated license value by pattern
EstimateValue-producing
$4,860/mo · 67.5%
AI Amplifiers and Quiet Multipliers
Value at risk
$2,340/mo · 32.5%
AI Overload and AI Masks
| Pattern | Licensed people | Est. monthly cost | Share |
|---|---|---|---|
| AI Amplifiers | 138 | $4,140 | 57.5% |
| Quiet Multipliers | 24 | $720 | 10% |
| AI Overload | 48 | $1,440 | 20% |
| AI Masks | 30 | $900 | 12.5% |
| Total | 240 | $7,200 | 100% |
Method: monthly license cost is split in proportion to the number of licensed people in teams with each pattern; AI Amplifiers and Quiet Multipliers count as value-producing, AI Overload and AI Masks as value at risk.
Three team-level actions
- 1
Cut standing meetings
Claims Operations · AI Overload
What
Replace Claims Operations’s recurring status meetings with a short written update for four weeks, and keep only meetings that end in a decision.
Why
Meeting hours rose from 8.5 to 12.5 per person per week and the after-hours share rose from 10% to 18%, while delivery moved +1%. AI is adding review and coordination work, not removing it.
Measure
Team meeting hours and after-hours share, weekly for four weeks. Target: both back toward the baseline with delivery steady or up.
- 2
Shift recognition toward delivery
Finance Close · AI Masks
What
In Finance Close’s reviews and team updates, recognize completed close tasks and cycle time instead of Copilot usage.
Why
Usage looks healthy, but delivery is −2% and the after-hours share rose from 9% to 11%. Activity is being rewarded; output isn’t.
Measure
Team delivery trend over the next 30 days. Target: positive, with no rise in after-hours share.
- 3
Spread a working pattern that works
Data & Analytics · Quiet Multipliers
What
Data & Analytics runs two short working sessions with Customer Support and Product Design on how it drafts first versions with Copilot and reviews them asynchronously.
Why
Data & Analytics delivered +15% with fewer meeting hours (6 → 5.5) and a lower after-hours share (8% → 7%). It is the cheapest pattern in the department to copy.
Measure
Delivery trend and meeting hours for Customer Support and Product Design over the next 30 days.
Reported at team level only. Groups under five people are combined.