Before the pilot: five questions for agent readiness
A compelling demo leaves important questions open. Use a five-dimension rubric to examine the data, authority, evidence, ownership and people behind your next agent initiative.
Ownership, accountability and ways of working for teams that introduce agents into live business processes.
A compelling demo leaves important questions open. Use a five-dimension rubric to examine the data, authority, evidence, ownership and people behind your next agent initiative.
A list of AI ideas is not an operating plan. Define the work, decisions, authority and evidence before deciding whether an agent belongs in the workflow.
Classify AI by the action path it creates, not the label on the product. The distinction determines ownership, controls, evaluation and release evidence.
A centre can concentrate scarce expertise and reusable controls, or become an approval queue detached from real work. Choose the mandate before the structure.
A useful quarterly watchlist tracks changes that could alter real decisions: system authority, evidence, incidents, standards, providers and organisational readiness.
Do not divide work into “human” and “AI” columns. Redesign tasks, decisions, authority, handoffs and learning so each role remains operable and accountable.
A successful demonstration does not create a live service. Pilots stall when they test capability without resolving ownership, integration, economics and operating evidence.
Model launches are not transformation milestones. Organize the roadmap around workflow, evidence, authority, operating and expansion decisions.
Design an AI workshop backwards from a named decision, then capture evidence, assumptions, disagreements, owners and triggers in an artefact that survives the meeting.
Finance agents can prepare, reconcile and investigate, but posting, paying and attesting require deliberately separated authority.
Enterprise readiness scores hide the conditions that make one workflow viable and another reckless. Assess readiness where data, authority, people and operations meet.
A useful responsibility map connects each AI decision and artefact to a named accountable owner, a performing role, required contributors and evidence of completion.
KEEP EXPLORING
Read the method, assumptions and questions to ask.