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Free educational planning tool

AI economics scorecard: revenue quality, cost pressure and compute exposure

Turn a frontier-AI revenue headline into a structured diligence conversation. Adjust the inputs, see the transparent score drivers and email yourself a personalised two-page scorecard.

Transparent 100-point modelCompute sensitivityNo valuation claims

Educational planning tool only — not investment, credit or valuation advice.

Choose then edit a scenario

OpenAI economics scenario

Choose a source-qualified preset or start a blank comparator. Every number remains editable; a zero in a preset indicates an undisclosed or deliberately un-inferred value, not a real zero.

Preset disclosure note

Reported inputs only: annualised recurring revenue and planned compute spend are reported; current gross margin, operating expenses, cash and enterprise mix are not treated as disclosed here and remain at zero until you replace them.

Visual breakdown

Score drivers

The bars below make each score component visible. Thresholds are explained in the downloadable scorecard and should be challenged against primary-source evidence.

17 + 15 + 17 + 14 + 12 + 15 + 10 = the page's transparent 100-point model.
DriverMaximum already on the pageWhat the default view says
Revenue scale17Scored against this tool's $20B reference ceiling. The default view shows 17/17.
Gross margin15Not scored until a comparable gross-margin input is supplied.
Operating discipline17Not scored until comparable revenue and operating-expense inputs are supplied.
Liquidity buffer14Not scored until cash and a comparable cost or compute input are supplied.
Revenue growth12Not scored until a like-for-like growth input is supplied.
Enterprise mix15Not scored until an enterprise-mix input is supplied.
Capital visibility10A yes/no visibility input. Not an assessment of funding quality. The default view shows 10/10.

token calculator — A model API rate is not this scorecard.

AI governance — Operating credibility is a governance question, not a score.

Revenue scale

Reported revenue scale relative to this tool's $20B reference ceiling.

17/17

Gross margin

Not scored until a comparable gross-margin input is supplied.

0/15

Operating discipline

Not scored until comparable revenue and operating-expense inputs are supplied.

0/17

Liquidity buffer

Not scored until cash and a comparable cost or compute input are supplied.

0/14

Revenue growth

Not scored until a like-for-like growth input is supplied.

0/12

Enterprise mix

Not scored until an enterprise-mix input is supplied.

0/15

Capital visibility

A simple yes/no visibility input; it is not an assessment of funding quality.

10/10

Sensitivity

What changes the picture?

This simple stress check asks how the planning score changes when margins compress and operating costs rise, or when compute-spend needs exceed the original assumption.

Baseline inputs

27

Margin −10 pts + operating costs +20%

27

Compute spend +50%

27

Personalised resource

Email my scorecard

Get a clear two-page PDF with your inputs, score drivers and sensitivity checks. This is a transactional resource request, not a marketing subscription.

We use your email only to deliver this requested scorecard and deduplicate requests. This is not a marketing subscription.

Research context

OpenAI: source boundaries and comparison limits

Reported 2026 press coverage; ARR/run-rate is not recognised revenue and forecast spending is not audited actual spend.

The selector does not independently validate information or generate a company rating. It only populates linked, qualified planning inputs; all values should be checked and replaced for the purpose you are assessing.

Next step

Turn an economics question into an operating decision

A credible AI plan connects compute, data rights, authority boundaries, content visibility and real commercial measurement. The free audit is an appropriate start when the question is how ready your own site and growth operations are for AI-mediated discovery.

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FAQ

Questions about the AI economics scorecard

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