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.
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.
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.
What Boards and Audit Committees Should Actually Ask About AI
Most board conversations about AI are either too strategic or too tactical. The economic governance layer — capital discipline, value proof, and investment accountability — is largely missing. This article sets out what responsible oversight actually requires.
When to Stop: The AI Initiative Autopsy
Most organisations have detailed criteria for starting AI investments and almost none for stopping them. This is the most expensive gap in enterprise AI governance.
Enterprise AI Cost Basics
A practical primer on where enterprise AI costs accumulate and how leaders should think about them.
The Inference Cost Crisis: What Every Enterprise AI Buyer Should Know
Why inference has become the primary economic bottleneck in enterprise AI, what could happen when pricing normalises, and how buyers should prepare now.
AI Economics for Mid-Market Companies: Why the Enterprise Playbook Doesn't Scale Down
The standard AI economics frameworks were built for enterprise conditions that mid-market companies do not share. This piece examines what changes — and what a more practical approach looks like.
Building an AI Business Case That Survives Board Scrutiny
A practical guide for CFOs and finance leaders on what a credible AI business case requires — and the most common ways they fail under scrutiny.
Programmatic Access to AI Costs: A FinOps Practitioner's Billing API Guide
A practical reference for FinOps and platform teams on how to access AI cost data programmatically across the major model providers, hyperscalers, and coding tools — including what is available, what is not, and how to build a minimal cost aggregation pipeline.
The Cost of AI Governance: When the Operating Model Consumes the Portfolio
AI governance frameworks are genuinely necessary. They are also genuinely expensive. The question of how much governance is proportionate — and at what point the operating model costs more than it saves — is one of the least examined in enterprise AI.
The Economics of AI Vendor Selection: Lock-in, Pricing Risk, and Exit Costs
How to evaluate AI vendors on economic and risk grounds — not just capability. Covers pricing model risk, lock-in dimensions, consolidation exposure, and what a vendor exit actually costs.
What AI Actually Costs: Reference Cost Ranges for Enterprise AI
Reference cost ranges across the main layers of enterprise AI spend — from inference and platform fees to governance overhead and integration engineering. A practical starting point for internal planning and benchmarking.
AI Economics for the Engineering Leader
A practical guide for Heads of Engineering, platform leads, and CPOs on model selection economics, shift-left cost awareness, and build-versus-buy decisions in enterprise AI.
FinOps for Inference-Era Workloads
Why inference-heavy AI services require FinOps practices that extend beyond cloud billing into model behaviour, workflow design, and unit economics.
The CAIO's First 100 Days: An Economic Governance Playbook
A practical guide for newly appointed Chief AI Officers and VPs of AI on building visibility, proof standards, and cross-functional governance in the first hundred days.
What CFOs Should Ask of AI ROI Claims
Most AI ROI cases are structured to survive scrutiny rather than invite it. A genuinely credible AI business case looks different from what most organisations currently produce — and CFOs are the right people to demand the difference.
What Consulting Partners Need From AI Economics
How consulting partners and directors can use AI economics frameworks to improve client conversations, shape transformation programmes, and build more credible AI value-realisation work.
Where AI TCO Models Fail
Why enterprise AI cost models often break down once shared platforms, governance overhead, and operating complexity move beyond the model invoice.