Operating Model
How to actually run this
Most of the AI value problem has been solved before, under a different name. Cloud FinOps spent a decade learning to govern variable, decentralised spend without strangling the experimentation that made it valuable, and AI value management inherits much of that playbook plus one genuinely new layer. This section covers what transfers, what does not, who owns AI value, and the human work of adoption, incentives, and change where value is actually won or lost.
Core pages
The operating model for AI value: what carries over from FinOps, what's genuinely new, and the human blockers where programmes actually stall.
Foundation
The FinOps lineage
What carries over unchanged, and the one thing FinOps was never built to supply.
Adoption
The blockers are human
Why programmes stall on behaviour, not technology, and the 90-day start.
Procurement
Per-seat is dying
How agentic AI rewrites SaaS pricing, procurement and build-versus-buy.
Portfolio
SPM and AI
The portfolio discipline that turns value data into investment decisions.
Finance view
Building AI business cases that survive scrutiny
What a credible AI business case requires: complete cost models, realistic benefit claims, and proof standards defined before approval.
Supporting disciplines
How TBM, ITFM, and related disciplines adapt to AI economics.
Domain overview
TBM & AI
How service and portfolio management disciplines adapt to shared AI capability economics.
Domain overview
ITFM & AI
How budgeting, planning, forecasting, allocation, and reporting disciplines adapt to AI.
Signature framework
The Layers of AI Value Management
How usage transparency, output quality, workflow value, delivery alignment, and portfolio strategy fit together.
Signature framework
AI Economics Maturity Model
A maturity model for judging whether the organisation is becoming more governable as AI scales.