Problem path · Pilot Design & Evaluation
The company wants to use AI but cannot yet identify the right first process or the evidence required to continue.
Why this path
This path begins with process selection, then defines evaluation and ownership, and finally adds human handoff. It moves a pilot from “can it run?” to “should the business keep using and expanding it?”
Start from a task rather than a job title, then score business value, frequency, knowledge readiness, controllable risk, and process ownership.
How should the company select its first AI workflow?
Start from a bounded, frequent, knowledge-intensive process rather than a fashionable tool.
A five-part score for comparing candidate workflows.
Build an auditable evidence chain from work ownership and process speed to delivery quality, customer experience, and operating outcomes.
What evidence makes a pilot successful?
Define the human baseline, process measures, and decision rule before building.
An evidence chain from work ownership to operating outcomes.
Many AI initiatives stall because no one owns the process outcome, decides the rules, or maintains the workflow after launch.
Who decides rules and remains accountable for the process?
Many technical-looking blockers are unresolved ownership decisions.
A clear process-owner role for rules, exceptions, and expansion.
A reliable AI workflow knows when to stop, who should take over, what context to transfer, and how the decision returns to the process.
How should exceptions return to a person?
A reliable pilot needs observable stop conditions and an actionable context package.
Five trigger types and a minimum handoff checklist.
Continue here after the pilot is stable enough to enter daily work.
Organization & Service Growth How does executive AI learning become organizational buying?Continue here when the pilot creates training, purchasing, or organizational questions.
Prefer a frequent, knowledge-intensive process with a bounded result, reversible failure, and a named owner. It should produce enough samples for a short review cycle.
Measure the whole process: acceptance, correction, waiting, handoff, recovery, customer impact, and operating results. Do not rely on model accuracy or latency alone.
Two to four weeks is usually enough to collect a first set of reviewable samples. If the team still cannot explain what changed, revisit scope, metrics, or ownership.
Email the industry, workflow entry point, and current uncertainty. I will start by checking scope, evidence, ownership, and handoff.