Frameworks
Frameworks index
Every model and tool on the site, placed on the four phases of the AI Economics System: measure, prove, decide, operate. Each card says whether it is this site’s own proposal, an established idea adapted to AI, an explainer or a tool, so you can tell what is new from what is borrowed. It also says which door it sits in: Understand explains, Implement is something you can use on Monday.
Hub proposals carry a version number and stay below 1.0 until they have survived outside challenge. How the labels work.
The whole system
How the four phases connect, and which external standard covers which part. How the system works
- Reference explainerMap the system · UnderstandThe AI economics mapOne map from compute to business value to capital allocation, showing where external standards stop and decisions begin.Best for: Seeing how cost, use, value and decisions connect, and which standard covers which part.
- Reference explainerMap the system · ReferenceStandards and frameworks mapWhat FOCUS, the FinOps Framework, TBM and the Tokenomics Foundation cover, and where the hub's models fit.Best for: Seeing which body's work covers which part of the problem.
Measure
What does AI fully cost, where is it consumed, and who owns it? How this phase works
- Reference explainerUnderstand cost · UnderstandAI TCO FrameworkSeven cost layers, most of which never appear on the model invoice.Best for: Checking that a business case prices more than the model invoice.
- Reference explainerUnderstand cost · UnderstandToken economics explainedThe anatomy of a token bill: input and output, caching, context, agent loops, and where the meter ends.Best for: Understanding what drives a token bill.
- Adapted conceptDiagnose · UnderstandThe AI icebergValue is the visible tip. The submerged base is what keeps it afloat, and what most programmes forget to fund.Best for: Showing sponsors the costs a business case usually leaves out.
Prove
What changed because AI was used, and how strong is the evidence? How this phase works
- Hub proposalv0.9Diagnose · UnderstandThe AI Value GapWhy AI cost is visible and AI value is not, and how attribution coverage measures the difference.Best for: Showing a board how much AI spend has a measured outcome behind it.
- Hub proposalv0.5Measure value · ImplementThe AI Value LedgerOne record per material workflow: owner, baseline, cost, evidence level and a decision. With a template.Best for: Keeping one decision-grade record per material workflow.
- Hub proposalv0.9Measure value · UnderstandAI Value AttributionConnecting each unit of AI work to a baseline, an owner and evidence of change.Best for: Computing attribution coverage for the first time.
- Reference explainerMeasure value · UnderstandAI ROI ModelsReturn measured across several dimensions, built to survive board scrutiny.Best for: Choosing which return dimensions a business case should cover.
- ToolMeasure value · ImplementAI Economics KPIsThe KPI library across seven governance domains, led by attribution coverage.Best for: Picking eight to twelve KPIs to track, from a library of thirty.
- Adapted conceptUnderstand constraints · UnderstandThe productivity J-curveWhy AI returns lag investment by design, and how to tell a dip from a failure.Best for: Setting expectations for a dip after launch.
- Reference explainerMeasure value · UnderstandHow to read an AI metricThe distinction ladder from activity to strategic impact, then the set: attribution coverage, cost per successful outcome, value dimensions and capture status.Best for: Sorting a dashboard's metrics from activity to impact, then choosing a set before picking KPIs.
Decide
Given the economics and the evidence, what should be scaled, held, redesigned or stopped? How this phase works
- Hub proposalv0.5Understand constraints · UnderstandThe AI Abundance ParadoxWhen generation is cheap, review and absorption set the ceiling on value.Best for: Finding the stage where review or absorption caps value.
- Hub proposalv0.5Decide · ImplementScale, hold, redesign, stopDecision rules that combine return on scarce capacity with the strength of the evidence.Best for: Turning a value claim and its evidence into an action.
- Hub proposalv0.5Decide · ImplementProof for autonomyEach step up the autonomy ladder needs a stronger level of evidence before it is granted.Best for: Setting how much evidence an agent needs before it is allowed to act alone.
- ToolDecide · ImplementAI Proof of Value ScorecardScore an AI pilot on eight dimensions, from baseline and feasibility to economics, risk and measured results.Best for: Scoring a pilot before deciding whether to scale it.
Operate
Who owns each part, how often is it reviewed, and what reaches the board? How this phase works
- Hub proposalv0.1Decide · ImplementThe AI value lifecycleSeven stages from funding to decision, each with an owner and a gate, and a separate path for bought AI.Best for: Agreeing who signs off each AI value decision, and what evidence each gate needs, from funding to scale or stop.
- Hub proposalv0.5Assess maturity · UnderstandAI Value Management LayersHow the discipline stacks, from usage visibility to portfolio decisions.Best for: Seeing which layer of capability a programme is missing, alongside the maturity model's overall level.
- Adapted conceptAssess maturity · UnderstandAI Economics Maturity ModelFive levels from fragmented spend to governed, provable value.Best for: A rough self-assessment to agree where to invest next.
