Section 11
Enterprise Value & ROI
Separating technical performance from enterprise outcomes, and measuring across three scopes.
AI4EA considers AI successful when it produces measurable enterprise outcomes. Value should be evaluated across productivity and efficiency, innovation and time to value, decision quality, risk and compliance, cost optimization, customer outcomes and strategic advantage.
11.1 Value Measurement Hierarchy
AI4EA separates technical performance from business value. Technical AI performance is an enabler, not a substitute, for enterprise outcomes.
Enterprise / Strategic Outcomes
Revenue, productivity, risk reduction, customer experience, strategic capability
Use Case Outcomes
Adoption, time saved, processing improvement, decision quality, customer outcome
AI Technical Performance
Quality, accuracy, task success, latency, reliability, cost and safety
Operational Efficiency
Infrastructure utilization, cost per inference/transaction, throughput and resource efficiency
Metrics should be traceable upward: operational efficiency supports solution performance; solution performance enables user and use-case outcomes; and those outcomes should contribute to business and strategic value.
11.2 Value Scope
Value should also be assessed across three scopes: Use Case Value → Platform Value → Enterprise Value. This prevents shared AI capabilities from being judged solely by the economics of an individual project.
Primary outcome
Traceable enterprise value.
Core artifacts