AI use case owner coverage
The share of AI tools and agents with a single named human owner.
Formula
AI owner coverage
(AI use cases, tools, or agents with one named human owner / total AI use cases, tools, or agents) * 100
Unit
percent
Direction
Higher is better
Cadence
Monthly during AI rollout.
Numerator
AI items with one named human owner
Denominator
Total AI items inventoried
Worked Example
AI use case inventory review.
AI use cases
25
Use cases with named human owner
18
Calculation
18 / 25 * 100
Result
72%
Interpretation
Too many AI use cases lack clear human accountability.
Recommended action
Assign owners before expanding use cases or autonomy.
Why it matters
This metric helps leaders see whether the ai amplification layer is healthy enough to support execution and AI readiness.
What it reveals
Whether AI-supported work has clear human accountability.
Manual assessment method
Inventory AI use cases, copilots, tools, and agents. Confirm each has a named owner or supervisor.
Lapemo calculation path
Live through agent supervisor coverage and AI-enabled tool ownership where records are populated.
Interpretation Bands
Healthy
85-100%
Strong enough for normal operating review.
Watch
70-84%
Usable, but gaps should be assigned owners.
Risk
50-69%
Weak enough to slow execution or create risk.
Critical
<50%
Do not scale the related workflow without intervention.
Required inputs
- AI use case inventory
- Human owner
- Supervisor
- Autonomy level
Data sources
- AI readiness diagnostic
- Agent accountability checklist
- AI inventory
Common pitfalls
- Counting vendor or tool as owner
- Ignoring supervisor role for agents
Recommended actions
- Name human owners
- Define supervisors
- Block ownerless AI scale
Measure Before You Scale
Measure the operating model before AI amplifies it.
Use the Metrics Library to understand what to diagnose, what to monitor, and where Lapemo can turn framework metrics into operating intelligence.