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Poor scope creates poor diagnostics. “Find every AI opportunity in the company” usually produces shallow evidence and uncontrolled delivery effort.

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Start with the business question

Good questions connect a process to a business outcome, for example:
  • Where does proposal production create avoidable rework?
  • Why is customer onboarding taking longer as the company scales?
  • Where could automation improve service throughput without reducing control?

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Define scope explicitly

Document:
  • process start and end points;
  • teams and locations included;
  • relevant systems;
  • stakeholder groups;
  • interview coverage;
  • where screen observation will or will not be used;
  • outputs;
  • exclusions.

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Set success criteria

Examples include a validated current-state map, agreement on the most important constraints, a prioritised opportunity backlog, transparent value assumptions and a decision on the first implementation project.

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Identify client responsibilities

The client may need to provide a sponsor, process owner, stakeholder access, participant availability, security/privacy approvals and timely review of findings.

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Scope control question

Does this help answer the agreed business question, or is it a new piece of work?
If it is new, trade scope, timeline or fee rather than silently absorbing it.