Original Framework / Research and Product Design

AI Economics Decision Framework

How an executive argument about AI sequencing became a transparent, recalculable operating tool instead of another static ROI slide.

The problem

Activity is not the same as an accepted business result.

AI business cases often lead with model price, licenses, prompts, or estimated hours saved. Those measures do not show whether the business received a usable, compliant, complete outcome—or what review, correction, integration, risk, and operating work was required to produce it.

The questionHow can an executive argument about AI sequencing become a transparent, recalculable operating tool rather than another static ROI slide?

The approach

Design for challenge, not persuasion.

01

Build the argument around operating evidence

The paper separates adoption from enterprise impact, technical activity from verified outcomes, and released capacity from realized cash savings. Externally sourced claims are mapped to a source ledger and publication limitations.

02

Convert the thesis into three engines

AI TCO covers implementation, recurring operations, human review, rework, infrastructure, governance, and risk. Verified outcomes separate first-pass, reviewed, corrected, failed, and unresolved work. The business-case engine adds baseline comparison, ROI, payback, NPV, break-even, and capacity.

03

Expose every assumption

The calculator labels evidence quality and returns “not comparable” or “not calculable” instead of zero. Capacity never becomes cash by default, expected loss is protected from double counting, and the tool never recommends headcount reduction.

04

Make the system maintainable

Dense factual graphics become semantic HTML. Formula versions, dated pricing snapshots, pure calculation modules, and exported inputs make every result reproducible.

Calculation architecture

Three engines. One verified denominator.

Engine 1AI TCO

Upfront, recurring, review, rework, integration, governance, and risk.

Engine 2Verified outcome

First-pass, reviewed-pass, corrected, failed, and unresolved.

Engine 3Business case

Hard ROI, risk-adjusted value, payback, NPV, break-even, and capacity.

Deliverables

A publication system, not a single artifact.

  • Board and C-suite executive white paper
  • Source ledger and paragraph-level evidence controls
  • Ten-graphic visual system with factual-qualification review
  • AI Cost Reality Calculator specification
  • 12-input MVP and advanced model-economics plan
  • Formula registry, JSON data schema, and acceptance test vectors
  • Static-site content, structured data, analytics, privacy, and release plan

Current status

Published, tested, and deliberately bounded.

Formula 1.1.0 is implemented as an isolated calculation engine and validated against acceptance vectors plus boundary tests. The interface remains static and private: calculations stay in the browser and are not submitted.

Boundaries

No client result is being claimed.

This work demonstrates a research and product-design system. It does not claim a client savings result, a typical AI ROI, production adoption, or an audited financial outcome. The calculator produces decision support from user inputs; it is not accounting, legal, investment, employment, cybersecurity, or regulatory advice.

Use the system

Challenge the economics.

The calculator makes the assumptions visible and reproducible.