Cost & Value
The pages and articles most useful for understanding AI cost structure, value proof, and the economic trade-offs behind enterprise deployment.
This area is designed for readers trying to answer hard questions about total cost of ownership, ROI, unit economics, and whether AI activity is producing financially credible outcomes.
Core frameworks
Start here if the immediate question is what AI really costs and how that cost should be compared to value claims.
Value framework
The Layers of AI Value Management
Connect AI cost to quality, workflow impact, portfolio decisions, and personal accountability.
Cost framework
AI TCO Framework
A seven-layer model for understanding the full burden of enterprise AI capability.
Return framework
AI ROI Models
A boardroom-friendly framework for evaluating AI return across multiple dimensions.
Flagship reference
AI Economics KPIs
Definitions, formulas, examples, and benchmarks for governing AI cost and value.
Flagship essay
The AI Value Gap
Why many organisations still struggle to connect AI spending to provable outcomes.
Article
The Inference Cost Crisis
Why inference is becoming the primary economic bottleneck and what enterprise buyers should do about it.
Supporting analysis
Use these pieces to test where cost models, value claims, and operating assumptions often break down in practice.
Article
Where AI TCO Models Fail
Why enterprise AI cost models often break once shared platforms and operating burden expand.
Article
What CFOs Should Ask of AI ROI Claims
A finance-led checklist for testing whether AI return claims are specific and credible.
Article
AI Economics for the Engineering Leader
A practical guide to model-selection economics, prompt efficiency, and shift-left cost awareness.
Domain overview
FinOps & AI
How consumption governance and optimisation affect the economics of AI services.