Pilot one workflow before you scale it
Pilot is the proof engagement for teams that need real signal from actual work, not more speculation or slideware.
If the pilot underperforms, the work is still useful
A pilot does not need to become a permanent solution to be worth doing. If it misses the agreed target, you still leave with evidence, lessons, and a clearer decision to adjust, pause, or stop.
This engagement keeps scope narrow on purpose: one workflow, one owner, and a clear definition of what would count as useful. The point is to learn quickly, adjust honestly, and decide what should happen next.
- Workflow owner
- Scope boundaries
- Success criteria
- Reviewer path
- KPI scorecard
- Stop, pause, or continue logic
Examples of what we may measure
Examples only. Final measures are set during scoping.
What you leave with
- A bounded pilot
- A working scorecard
- Observed findings and constraints
- Decision notes on what to do next
- Any agreed handoff materials
What you keep
- The scorecard
- Observed constraints and findings
- Key documentation
- Any agreed handoff artifacts
Reviewer-ready from the start
When reviewer input is needed, the work documents the workflow in scope, systems involved, data considerations, what stays out of scope, and who owns the outputs before the work widens.
- Workflow and system boundaries are explicit
- Reviewer involvement happens early when needed
- Measurement and checkpoints are documented
- Scope does not widen casually
- Documentation survives the engagement
Practical AI work is easier to approve, safer to adopt, and easier to maintain when the review posture is visible early.