Why this site exists
AI is becoming easier to buy, embed and automate faster than most organisations are improving their ability to judge its economic value. Consumption can scale automatically. Evidence usually cannot.
Cost and usage measurement is being standardised by the FinOps Foundation's FOCUS specification and FinOps Framework, the TBM Council's taxonomy and, more recently, the Tokenomics Foundation's work on AI value classification and operating roles. This site does not try to replace any of them. It covers the management layer above that evidence: how a CFO, CIO or portfolio owner compares claims, accounts for scarce human capacity, and makes the call. The standards map shows where each body's work stops and the site's own proposals begin.
Who writes this
I'm Ed Epstein, an enterprise account executive at IBM in the Apptio portfolio (Apptio, Cloudability, Turbonomic), and I write and edit AI Economics Hub. IBM sells products in several areas this site covers, including FinOps, technology business management and AI value measurement, and is a member of industry bodies the site discusses, including the Tokenomics Foundation. This is an independent personal publication. The postings on this site are my own and don't necessarily represent IBM's positions, strategies or opinions. No IBM, client or partner confidential information is used. IBM-owned products are marked wherever they appear, and the vendor map describes products without rating them.
There is no editorial team. Where other people contribute in future, they will be named with their role.
Use of AI tools. AI tools are used in research, drafting and production, under human editorial direction. Material factual claims are checked against the cited source before publication. Where a claim cannot be supported, it is qualified, labelled as a hypothesis, or removed.
Funding and commercial relationships
- The site is free to read and carries no advertising. Readers can contribute to its running costs.
- No vendor pays for inclusion or placement in the vendor map. The map describes vendors from public sources and does not rate, score or rank them; see how it is built.
- The author works for IBM (see above). IBM-owned products are marked wherever they appear, and are described in the same way as every other product.
- Vendors can send factual corrections about their own products to the address below. Corrections are judged on the evidence supplied, and logged.
What is original here, and what is not
The site distinguishes four kinds of material, and labels each on the frameworks page:
- Hub proposals. A small number of models this site puts forward and asks readers to challenge: the AI Value Gap and attribution coverage, the AI Abundance Paradox, the AI Value Ledger, Scale / Hold / Redesign / Stop, and proof requirements that rise with autonomy. Each is versioned and dated.
- Adapted concepts. Established ideas applied to AI, with their lineage cited, such as the productivity J-curve and maturity models.
- Reference explainers. Descriptions of industry subject matter, such as token economics and TCO components.
- Tools. Calculators, worksheets and templates.
Where a term comes from someone else's work, such as the Tokenomics Foundation's quality floor or its Observe, Net, Convert, Book chain, the source is named at first use.
A note on names
The site uses AI Value Management for the discipline of connecting AI spend to measured outcomes. The word Valuemaxxing appears in the debate series and a few essays as a deliberate counterpoint to "tokenmaxxing". It is shorthand, not a methodology, and the site does not ask anyone to adopt it.
Who it is for
The writing is aimed at the people who have to sign off, run or challenge AI spend: CFOs and FP&A leads, CIOs and CTOs, heads of AI, FinOps, TBM, ITFM and portfolio practitioners, product owners, procurement leads and, increasingly, the line managers whose teams now create AI spend directly.
It is not a news site. It does not track every model release or funding round, and it is not a procurement guide. Market analysis appears where it changes a management decision.
How claims are handled
Claims are labelled across the site as evidence, reported findings, interpretation, house positions or speculation. Survey figures travel with their sample and population. Vendor and consultancy research is labelled as such. House positions are dated and tracked in the position ledger, and the full approach is in the methodology. Real changes are recorded in the changelog, also available as an RSS feed.
Corrections and contact
If something on this site is factually wrong, miscited or misleadingly framed, email contact@aieconomicshub.com with the page and the issue. Substantiated corrections are made on the page itself, with a dated note where the correction matters to the argument, and logged on the corrections page.
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