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Concept Fable

AI use case checklist

Conclusion first:An AI Use Case Inventory is a list of AI use cases maintained by an organization, recording use case names, business purposes, systems/models, data inputs, vendors, owners, risk classifications, operational status, review records, and retirement plans. It is the foundation for AI governance, risk management, compliance audits, investment prioritization, and Shadow AI governance.

AI Use Case Inventory · Governance

Read the story first. There is no rush to give a definition here; let the question grow on its own first.

Fable

The city lord finally knew how many capable puppets the city was actually keeping

All the shops in the city said they had clever tricks that could save manpower, speed up checkout, and reduce losses. At first, the chamber secretary handled matters based on ideas reported orally by the shopkeepers, relying on familiar people and familiar paths, and when the business was small, mistakes were rare. The secretary realized that "everyone wants to try AI" is not a manageable project list; every opportunity needs a scenario, users, frequency, benefits, and an owner.

Half a year later, a great deal of silver had been spent, yet the truly useful methods were too many to count. The more ideas there were, the more obvious duplicate buildout and lack of ownership became; ranking only by volume would direct resources to those best at expressing themselves rather than to the opportunities most worth validating.

The first repairs were urgent: whoever was loudest got funding first, and whoever wrote the flashiest proposal went to the top of the list. Popular ideas got budgets first, which looked proactive in the short term, but did not explain users, benefits, or responsibility for failure. Yet new problems followed: everyone stared only at the most visible places, and small distant deviations accumulated deeper and deeper.

The clerk registers business pain points, trigger frequency, data conditions, expected benefits, risks, dependencies, and validation metrics item by item, then arranges pilots by value and feasibility.

The clerk registered shop by shop: who this tactic is for, what problem it solves, how many times it appears each day, which ledgers are needed, who is responsible if something goes wrong, and how much labor it can save. This step was troublesome and at first even slowed the schedule; but after several rounds, there was less rework, and the masters no longer changed the rules on a whim. The checklist let the chamber of commerce know which opportunity to validate first, which investment to pause, and who was responsible for each decision.

The checklist shifts the discussion from "can we do it" to "which one do we validate first"; the value of use-case inventory is that it gives portfolio decisions a basis and makes pausing an opportunity explainable.

Once the list was laid out, some flashy ideas were crossed off, while several unremarkable small tasks moved to the front. From then on, only by first taking stock of opportunities one by one could they know where to invest and where to stop.

Concept Anchor

This story is about: AI use case checklist

An AI Use Case Inventory is a list of AI use cases maintained by an organization, recording use case names, business purposes, systems/models, data inputs, vendors, owners, risk classifications, operational status, review records, and retirement plans. It is the foundation for AI governance, risk management, compliance audits, investment prioritization, and Shadow AI governance.

What matters is that it is not just a term, but a structural problem that repeatedly appears in real AI / Agent systems. Understanding it lets you judge when to add a model, when to change a process, and when to add governance.

Story Mapping

  • The capable puppet: AI tools, models, and Agents within an organization
  • Departmental trials: decentralized AI adoption
  • Only mentioning small tools: underestimating the actual business impact
  • Publishing must follow the rules: governance cannot be enforced without an inventory
  • Master Volume: AI Use Case Inventory
  • Owner, data, vendor, risk level: key fields of the inventory
  • Duplicate procurement consolidation: portfolio management
  • Ask about benefits and risks: turning AI from an experiment into a manageable asset

Andy Ren Xu's judgment

The practical value of this concept is that it helps you break "AI features that look smart" into deliverable, verifiable, and governable units of work.

model inventorysystem inventoryrisk classificationapplication portfolio
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