AI Economics & Business Case Logic

AI Economics & Business Case Logic makes lifecycle cost, usage-sensitive unit economics and attributable financial impact explicit. It includes time-to-first-value, cost-to-outcome, ROAI, non-linear value curves, learning and option value, shared portfolio effects and scenario sensitivity.

CONNECT THIS TOPIC TO AI TRANSFORMATION

Assess the economics behind AI transformation decisions. Connect expected benefits to development, operation, oversight and change costs across the lifecycle.

Explore the holistic AIDIVE framework

Why this matters

A cheap inference can be part of an expensive workflow. Single-point forecasts can conceal recurring review effort, weak adoption, shared-cost double counting and assumptions that reverse the decision.

Questions to bring to the work

What does a usable outcome cost after review, exceptions and recurring operation?
Which assumption could reverse the recommendation, and how will it be tested?

Explore this chapter

I.3.1Time-to-First-Value

Measure elapsed time from authorised investment to a credible, decision-relevant first outcome, distinguishing it from launch or full benefit realization.

I.3.2Total Cost of AI Ownership

Include discovery, data, integration, model operation, human review, change, assurance, incidents, migration and retirement across the lifecycle.

I.3.3Unit Economics, Token Budgets & Cost-to-Outcome

Connect token or inference consumption to a usable service unit and business outcome, including failed attempts, review and exception handling.

I.3.4Financial Impact ROAI and Benefit Realization

Report attributable financial benefit after the full cost base, and name the management action that converts released capacity into realized value.

I.3.5Non-Linear Value Curves

Test thresholds, fixed costs, reuse, congestion and support burden because the relationship between scale and value may change shape.

I.3.6Learning, Option & Compounding Effects

Record learning when uncertainty changes a decision, options when a bounded investment preserves future choices, and compounding when reuse improves later outcomes.

I.3.7Portfolio-Level Value Logic

Reconcile shared costs and benefits while balancing immediate returns, reusable enablers, strategic options, obligations and concentration across the portfolio.

I.3.8Limitations of Single Point ROAI and Sensitivity

Use scenario ranges, sensitivity and confidence alongside ROAI so weak baselines or optimistic assumptions do not disappear inside one number.

What useful evidence looks like

A full cost boundary with actual and forecast workflow economics and benefit-realization actions.
Scenario ranges, sensitivity, confidence and portfolio allocation assumptions rather than one unsupported return figure.

Move from understanding to practice

AR-IM11

AR-IM14 · Value Curve and Sensitivity

Framework source

Editorial adaptation from the supplied AIDIVE Version 1 master documents.

AIDIVE Impact Dimension Version-1.docx · I.3 AI Economics & Business Case Logic; AIDIVE Impact - Practices & Playbook Version-1.docx · AR-IM11, AR-IM12, AR-IM13, AR-IM14

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