Abundance Economics — The Economic Mechanisms of the AI Age

A structural model of the AI economy

The Economic Mechanisms of the AI Age

Every technology before now helped workers become more productive. This one makes the workers.

Abundance Economics treats AI not as a marvel or a menace, but as a growing share of work moving from people to software and machines — and follows it to consequences few have modeled: structural price disruptions, transformed competition, disappearing tax bases, and career ladders with disappearing rungs.

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By John Leslie Millar · Abundance Economics Press

Why the model is different

Capability is not the same as consequence

The useful question for leadership is not what AI can do. It is how capability moves through cash flows, costs, prices, balance sheets, labor markets, tax systems, and competitive structure.

Start with the economic input

AI increasingly performs work that used to require people. That shifts work from hiring, training, wages, and careers toward software, compute, machines, electricity, and capital.

Trace the transmission

Lower work costs do not stay inside productivity slides. They move through margins, pricing, revenue models, customer budgets, public revenue, and the signals investors use.

Test it case by case

The framework earns its keep only when applied to actual firms, industries, sectors, and policy problems. The archive is where that testing lives.

Who it's for

For the people who have to act on it

Executives

Your AI problem is not only deployment.

It is knowing where lower work costs break pricing power, hiring pipelines, customer relationships, legacy assets, and the moat your strategy assumes still exists.

Which part of your advantage is structural, and which part is only friction?

Investors

The market may read the wrong signals.

Falling revenue can hide rising real output. Protected revenue can hide a weakening competitive position. The question is not who mentions AI, but whose economics change.

Where is the market pricing a product cycle when it should be pricing a cost-curve shock?

Policymakers

The numbers may misread the transition.

GDP, employment data, tax receipts, and debt metrics were built around human labor as the central taxable flow. AI changes the flow before institutions change the instruments.

What happens when real output rises but the taxable flows shrink?

Serious readers

This explains why several systems feel unstable at once.

Work, prices, careers, government finances, company moats, and markets are not separate AI stories. They are connected consequences of the same economic mechanism.

What changes when work stops scaling only through people?

The book

The full model in one place

Abundance Economics: The Economic Mechanisms of the AI Age sets out the model from first principles — following AI from work automation into costs, prices, competition, tax systems, employment, careers, government debt, and institutional response.

In the book, this shift is named manufactured labor: work produced through software, compute, machines, and capital, rather than through human hiring alone. Once labor can be manufactured, it behaves like any other manufactured good — it scales, and it falls in price as more is made.

Coming soon See the evidence base

Abundance Economics Research

The research is the model applied

The research archive contains hundreds of published reports applying the mechanisms described in the book across companies, industries, sectors, and market events.

A selection of published Abundance Economics research reports

Company Reports

Business-model exposure

A Company Report examines how a firm makes money, where its costs sit, and how durable its margins are — whether its moat is structural or friction-based, and where AI-native competitors may attack. Does it benefit from falling input costs, suffer from shrinking customer revenue, or both at once?

Example: NVIDIA →

Industry Reports

Value-chain disruption

An Industry Report covers a full competitive system — firms, customers, suppliers, workflows, regulations, and margins. It traces where labor sits in the value chain, which tasks are exposed first, how pricing shifts as costs fall, and where entry barriers weaken as AI-native firms appear. The aim is actionable: where pressure arrives first, which operating assumptions fail, and what to decide before competitors do.

Example: Accounting & Audit Services →

Sector Reports

Sequencing and cascades

A sector holds many industries — healthcare, financial services, transport, energy, retail — each moving at a different speed. A Sector Report maps the terrain: which industries are exposed first, which stay protected, how disruption cascades from one to the next, and where capital, regulation, and institutional resistance shape the transition. At its widest, it traces how a sector's tax base, employment, and competitive boundaries may shift across an economy.

Example: US Healthcare →

Market Notes

Current events with structure

A Market Note is a shorter, faster response to current news — an earnings surprise, a policy decision, a funding round, a strategic move. Its job is interpretation: what the event reveals about the mechanism underneath. Is a moat weakening? Is the market pricing a structural shift as a passing event?

Example: The Grid Is the AI Bottleneck →

Briefings

Cross-sector mechanisms

A Briefing is a longer study of a theme that cuts across companies, industries, and sectors — AI infrastructure financing, the economics of compute, the capital-structure risk of fast hardware depreciation, or the way markets misread deflationary business models. It takes a complex topic and shows how it changes once the mechanisms are applied.

Example: Terafab →

Browse the full research base

See how the same mechanism appears across technology, healthcare, banking, construction, retail, defense, media, and energy.

Subscribe to AER on Substack Browse the archive

Engagement

Run the model on your own business

The book gives you the mechanism. An engagement puts it to work inside your own company, with the people accountable for the outcome in the room — from a focused Q&A with the author to a full executive workshop, customized to your firm. It doesn't hand you a consultant's report and leave. Using tools built on the Abundance Economics method, it helps your team build their own — so the capability stays with them after the room clears.

Understand the impact

How the mechanism reaches your specific revenues, costs, competitive moats, and exposure — not AI in the abstract, but your business.

See the changes coming

How to read the transition as it develops, rather than reacting to each headline as a separate event.

Assess each change

A method for weighing what a given shift actually means for your position, as it arrives.

Strategize the response

How to turn that read into decisions — and a concrete to-do list the team can start on the next morning.

Scoped to your firm and your decision — from a single author-led session to a hands-on, customized workshop.

Request a briefing

The author

John Leslie Millar

Millar has spent his career across two worlds. The fast world of frontier technology — as co-founder of one of Europe's earliest technology accelerators in Cambridge, England, and through later work with the Silicon Valley and Stanford ecosystem.

And the slow world of established institutions — first through medicine, then as a senior executive at a multi-billion-dollar property developer, and as an advisor to governments across Asia and Europe on economic strategy, technology, and implementation.

That cross-system vantage is the book's method: it analyzes AI not as a story about capability, but as a set of economic mechanisms with predictable structural consequences.

John Leslie Millar on LinkedIn →

Choose the path

Start where the decision is

Read the book

The full model

Understand the model from first principles and the consequences it traces across the economy.

Get the book →

Follow the research

Ongoing applications

Track how the framework applies to companies, sectors, industries, and market events as they develop.

Subscribe →

Apply the methodology

Your live decision

Run the framework against a live company, portfolio, policy, sector, or board-level problem.

Discuss an application →