Stop choosing AI use cases; start defining workflows
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.
Decision-led guidance for selecting workflows, redesigning roles and moving useful agent systems into operation.
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.
A centre can concentrate scarce expertise and reusable controls, or become an approval queue detached from real work. Choose the mandate before the structure.
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.
Agents earn their complexity only when a workflow needs bounded adaptation. A disciplined no-agent test can reveal when rules, search or ordinary software is safer and cheaper.
Model launches are not transformation milestones. Organize the roadmap around workflow, evidence, authority, operating and expansion decisions.
Enterprise readiness scores hide the conditions that make one workflow viable and another reckless. Assess readiness where data, authority, people and operations meet.
Rank agent opportunities by decision value, workflow evidence, feasibility, consequence and reuse—not by enthusiasm, executive volume or demo polish.
Live agents cut across product, operations, risk and technology. One accountable service owner needs explicit decision rights supported by named control owners.
An agent is not reliable if people avoid it, over-trust it or route around its controls. Adoption evidence belongs beside technical performance evidence.
KEEP EXPLORING
Read the method, assumptions and questions to ask.