Acme Corp has adopted 112 AI workflows across 14 active team members, delivering an estimated £186,000 annual value — equivalent to 2.7 FTE of additional capacity. The team adoption rate is 79%.
Engineering leads value creation at 34.5h/week saved, followed by Marketing (28.0h) and Operations (22.5h). ChatGPT remains the most widely adopted tool at 79% team coverage, with Claude and Cursor growing rapidly. 82% of implementations have documented human oversight levels.
Three high-priority recommendations are identified: accelerating piloting-stage workflows in Sales, improving evidence quality in Finance, and expanding Cursor adoption across the Engineering team.
112
Workflows Adopted?
+19 vs prior
127h
Hours Saved / Week?
+18.5h vs prior
£186k
Est. Annual Value?
+£24k vs prior
148
Total Tracked?
+32 vs prior
11 of 14 members have logged their AI stack.
Engineering
38 adopted · 4 members
£49,900/yr
72% evidenced
Marketing
29 adopted · 3 members
£49,510/yr
69% evidenced
Operations
18 adopted · 2 members
£31,400/yr
62% evidenced
Sales
14 adopted · 2 members
£24,700/yr
48% evidenced
Design
9 adopted · 2 members
£20,640/yr
50% evidenced
Finance
4 adopted · 1 member
£9,850/yr
33% evidenced
AI workflows in use that have high potential for full automation — freeing up further team capacity.
By Department
| Department | Distribution | H / M / L |
|---|
| Engineering |
|
18 / 23 / 9 |
| Marketing |
|
15 / 16 / 7 |
| Operations |
|
9 / 11 / 4 |
| Sales |
|
7 / 8 / 3 |
Based on all 148 tracked implementations (largest four departments shown). 82% documentation coverage.
Deterministic gaps identified from the data. These are not speculative — they reflect measurable exposure.
⚠
Evidence Gap — Finance (33% evidenced)
Finance has the lowest evidence rate of any department: £6,600 of its £9,850 in estimated savings isn't yet backed by evidence. Adding outcome evidence here would significantly strengthen the business case when presenting to leadership.
◎
Concentration Risk — Sarah Johnson (11.4% of team hours)
A single individual accounts for 11.4% of total reported weekly hours saved (14.5h/wk). If this person leaves or changes role, reported team value drops materially.
⏸
Stalled Adoption — 9 workflows in piloting
9 implementations are stuck in piloting and not delivering confirmed value. Unblocking these represents an estimated £17,280 of potential annual uplift — primarily concentrated in the Sales team.
✓
HITL Coverage — 82% documented
Strong human oversight documentation across the team. The remaining 18% of implementations without oversight classification should be reviewed before the next board cycle.
1
Run a structured pilot unblocking session with Sales. 9 stalled workflows represent £17k of recoverable annual value. Assign a dedicated AI champion in the team and set a 6-week target for pilot-to-adopted conversion.
2
Prioritise evidence collection in Finance. At 33% evidenced, Finance is the weakest department for business case credibility. Introduce a simple outcome logging step into existing Finance workflows — even a monthly time-saving confirmation would move the needle significantly.
3
Expand Cursor adoption across the full Engineering team. Currently 2 of 4 Engineering members use it. Given the 11.0h/wk productivity demonstrated by Marcus Taylor, rolling this out org-wide could add an estimated £15k+ in annual value.
4
Reduce concentration risk by cross-training AI knowledge. Sarah Johnson's 14.5h/wk saved represents 11.4% of team output. A structured knowledge-sharing session would both reduce key-person dependency and lift the baseline for lower-performing members.
AI-generated recommendations based on team data
Methodology: Time savings based on reported usage frequency (daily = 240×/year, weekly = 48×/year, etc.).
Annual value uses each member's actual salary from their profile where available; falls back to £45,000.
FTE equivalent = annual hours ÷ 1,920 working hours/year.
"Evidenced" = validated or measured confidence level.
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