CFO lens
Start with proof, capital discipline, and economic accountability.
Use the value thesis, maturity model, and ROI framework to test whether AI spend is becoming economically legible.
Vendor-neutral editorial
AI economics, value, and strategy.
AI Economics Hub is a vendor-neutral publication for senior leaders who need a clearer language for AI economics, from value proof and TCO to FinOps, TBM, ITFM, and portfolio governance.
The question is no longer whether AI is interesting. It is whether organisations can explain what they are spending, who owns the economics, and what value is being proved.
Why readers return
Evidence-backed frameworks rather than vendor positioning
Editorial guidance for finance, technology, and portfolio leaders
Reference material built for meetings, planning, and governance review
Core reading
The flagship frameworks for enterprise AI economics
Flagship essay
The AI Value Gap
The central thesis: most organisations still cannot prove whether AI is delivering economic value, because visibility, accountability, and proof remain fragmented.
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Signature framework
The Layers of AI Value Management
A governance stack for connecting AI usage, output quality, workflow impact, portfolio decisions, and personal accountability.
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Signature framework
AI Economics Maturity Model
A maturity model for moving from fragmented AI activity to governed, provable, portfolio-level AI value.
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Core framework
AI TCO Framework
A seven-layer cost model for understanding what AI really costs once orchestration, governance, and support are included.
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Flagship reference
AI Economics KPIs
A filterable library of 30 KPIs for governing AI cost, value, accountability, portfolio performance, and financial planning.
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Latest articles
Recent analysis for finance, technology, and operating-model leaders
Articles · 28 May 2026
Agentic AI Economics: Why Your Existing Frameworks Are Already Obsolete
Every AI economics framework in use today was built on a shared assumption — a human initiates a task, an AI model assists. Agentic systems break that assumption. The economic implications are not incremental. They are structural.
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Articles · 28 May 2026
AI Economics in Regulated Industries: Why the Standard Framework Breaks
The AI economics frameworks used in most enterprise conversations were built for tech-company conditions. In financial services, healthcare, and regulated government, the economics are structurally different — and the standard approach systematically underestimates cost and overestimates return.
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Articles · 28 May 2026
The Spell-Checker for Thinking: Personal AI Accountability for Knowledge Workers
We accepted the spell-checker trade-off without much debate. AI is now proposing the same deal for reasoning, judgment, and original thought. Whether to accept it — and on what terms — is a question worth being deliberate about.
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Persona pathways
Different entry points for different leadership questions
CIO lens
Treat AI as an operating model, not a collection of pilots.
Move from scattered pilots to a clearer view of shared platforms, governance burden, and portfolio consequence.
FinOps lens
Bring AI demand inside a stronger cost-governance loop.
Connect model usage, orchestration choices, and optimisation decisions back to allocation and unit economics.
TBM lens
Translate AI into service, capability, and portfolio language.
Use TBM structures to separate foundational AI capability investment from local demand and business accountability.
ITFM lens
Bring AI into planning, forecasting, allocation, and management reporting.
Use AI-specific cost categories and more continuous visibility to make AI legible inside formal financial management cycles.
Portfolio lens
Compare AI initiatives as a governed portfolio, not a queue of exceptions.
Use return timing, strategic fit, and scarce resource demand to decide what to fund, scale, redesign, or stop.
Reference desk
Durable material for meetings, planning, and governance review
Use these sections when the question is not just what to read next, but how to create shared language across finance, technology, strategy, and operating teams.
Reference library
Glossary
Shared definitions for AI economics, TCO, ROI, FinOps, TBM, ITFM, governance, and portfolio language.
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Market reference
Vendor Map
A structured view of the market categories emerging around cost visibility, allocation, optimisation, and value proof.
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Metric reference
AI Economics KPIs
A practitioner-ready KPI library for selecting metrics by governance domain, role, and maturity level.
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Operating discipline
FinOps, TBM, ITFM, and SPM
A connected set of operating-model lenses for making AI spend, ownership, planning, and portfolio decisions more legible.
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Editorial briefing
A quieter way to keep up with AI economics
The briefing will focus on durable frameworks, market structure, cost and value signals, and governance questions that are useful beyond the current news cycle.
Editorial briefing coming soon
The briefing will open once delivery infrastructure is connected. Until then, the articles library is the best way to follow new analysis.
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