Skip to main content
COMPEL Body of Knowledge

COMPEL Glossary / GL-06

AI Use Case

A specific, bounded application of AI technology to a defined business process or decision point, with a documented value thesis, identified stakeholders, risk classification, and success criteria.

What this means in practice

An AI use case is the fundamental unit of AI transformation — the entity that moves through COMPEL stages, accumulates evidence, and delivers measurable outcomes.

Context in the COMPEL framework

AI use cases are discovered and prioritized in Calibrate, designed in Model, built in Produce, validated in Evaluate, and continuously improved in Learn. Each use case maintains its own lifecycle state within the overall COMPEL program.

Where you see this

AI Use Case is most commonly referenced when teams work across the Calibrate , Model , Produce , Evaluate and Learn stages — especially within the Value Realization layer . It appears in governance artifacts, assessment instruments, and delivery playbooks wherever COMPEL is operationalized.

Related COMPEL stages

Related domains

Synonyms

AI application , AI initiative , AI opportunity , AI project

Related Terms Network

This diagram shows how AI Use Case connects to other concepts in the COMPEL body of knowledge. Each linked node is a term you can explore in turn.

Related terms for AI Use Case Network graph showing 3 related glossary terms connected to AI Use Case. AI Use Case Value Real… Workflow R… Governance…
3 related concepts connected to AI Use Case.
Accessible list of related terms
  • Value Realization — The end-to-end process of defining, tracking, and verifying the business value delivered by AI initiatives — from initial value thesis through baseline measurement, deployment, post-deployment review, and ongoing benefit tracking.
  • Workflow Redesign — The deliberate restructuring of business processes to embed AI capabilities at optimal human-AI handoff points, rather than overlaying AI onto existing manual workflows.
  • Governance Control — A defined mechanism — preventive, detective, or corrective — that enforces policy compliance, mitigates identified risks, or ensures operational integrity for AI systems.

See also

  • Value Realization — The end-to-end process of defining, tracking, and verifying the business value delivered by AI initiatives — from initial value thesis through baseline measurement, deployment, post-deployment review, and ongoing benefit tracking.
  • Workflow Redesign — The deliberate restructuring of business processes to embed AI capabilities at optimal human-AI handoff points, rather than overlaying AI onto existing manual workflows.
  • Governance Control — A defined mechanism — preventive, detective, or corrective — that enforces policy compliance, mitigates identified risks, or ensures operational integrity for AI systems.

Related articles in the Body of Knowledge

Related Terms

Other glossary terms mentioned in this entry's definition and context.