ANDREW STALLWOOD-KEEGAN

Follow theincentives.

I write about AI, capital and power: who makes the money, whose business model breaks, and what happens when the technology meets the real world.

Start with the questions
AI / CAPITAL / POWER
Andrew Stallwood-Keegan
ANDREW STALLWOOD-KEEGAN
ON SUBSTACKThe 2040
Brief.The economics behind what comes next.

QUESTIONS I’M EXPLORING

IDEAS & ARGUMENTS

Earlier writing

All essays on Substack
On the horizon2 essays in development

The two essays above are in development. Published links will appear here.

01 / EXPERIENCEPRACTICE & PERSPECTIVE

Ideas meet
commercial reality.

I know the difference between a compelling idea and one a client will actually pay for. My career has been built around understanding businesses well enough to connect the two.

Systems ThinkerCEOFounderFuturistStrategic RainmakerEntrepreneurAuthor

Vantage Point Global

Founder & CEO

GFT Technologies

Director

Genpact Capital Markets

Senior Vice PresidentEurope & Scandinavia

More experienceLess experience

Phi Partners

Global Sales Director

FDM Group

Business Development / GTM

Salesperson of the Year — two years running.

Lloyds Banking Group

Analyst

02 / PUBLICATIONSBOOKS, ESSAYS & IDEAS

Room for
the whole argument.

Some questions deserve
more than a passing opinion.

03 / BACKGROUNDTHE PERSON & THE PERSPECTIVE

A habit of
asking why.

The sales instinct never really leaves you. Who needs this? Why would they pay? Does it actually work?

My route into these questions runs through banking, technology and sales: from Lloyds and FDM to senior roles at Genpact and GFT, and founding Vantage Point Global. Understanding the client’s business has always been the interesting part for me. The technology has to make sense inside it.

That is also how I approach the future. AI and robotics fascinate me, particularly when falling costs make an established business model look suddenly rather expensive. I follow those consequences through companies, labour markets and the institutions trying to keep up.

I’m optimistic about what we can build. I’m less easily persuaded by the presentation.

ON X & SUBSTACK

X is where I put an observation into the conversation and see which questions it opens up. Substack gives me room to follow the evidence, do the sums and develop the argument. If the numbers spoil a good theory, the theory has to go.

04 / PAST COMPANIES

Where I’ve worked.

GFT TechnologiesVantage Point GlobalGenpact Capital MarketsCapitaFDM GroupLloyds Banking GroupPhi Partners
05 / CLIENTS

Who I’ve worked with.

Deutsche BankJ.P. MorganMorgan StanleyUBSHSBCBarclaysBNP ParibasBank of TokyoNomuraCitiLCH.ClearnetCredit SuisseSilicon Valley BankBear StearnsEBRD — European Bank for Reconstruction and DevelopmentSantander
INGDanske BankHypoVereinsbankCrédit AgricoleSwedbankNordeaABN AMROSociété GénéraleNatWestUniCreditBBVACommerzbankRabobankHandelsbankenAIB
Lloyd’s of LondonAmlin — MS Amlin logoTokio MarineQBEACE ReinsuranceBBCVirgin MediaVirgin MoneyMercedes-BenzAXAHastings DirectThomson ReutersFreshfieldsLinklaters
06 / CONTACTLET’S TALK

Have something
worth exploring?

A difficult business question, a research commission, a speaking invitation, or a disagreement worth having. I’m interested.

ask@wf2040.ai

To ask@wf2040.ai via FormSubmit.
A spam check may appear before sending.

AI & ENTERPRISE ARCHITECTURE / EXCERPT
NVIDIA GTC and The Last Architecture

Beyond the Agent.

Why the next AI revolution is about enterprise architecture.

Andrew Stallwood-Keegan ·

Something interesting is happening in the way the technology industry talks about artificial intelligence. For much of the past three years, attention has been concentrated on the capabilities of individual models. We have watched increasingly sophisticated systems demonstrate extraordinary abilities in language, mathematics, programming, scientific reasoning and complex problem-solving. Each release has been accompanied by another round of benchmarks, comparisons and speculation about how much closer we might be to artificial general intelligence. It has been an astonishing period of technological progress, although the conversation has sometimes resembled an endless competition to establish which machine is currently the cleverest.

That emphasis is beginning to change. The question attracting attention is no longer simply what an AI model can do when presented with a difficult problem, but what happens when that intelligence is connected to the systems, information and processes through which an organisation conducts its business. A model that can analyse a contract is impressive; a system capable of obtaining the relevant documents, interpreting the applicable policy, resolving an ambiguity, obtaining the necessary authorisation and progressing the underlying transaction represents something rather different. The distinction is between producing an answer and performing work, and it has consequences which extend considerably beyond the technology required to make either possible.

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AI & FINANCIAL MARKETS / EXCERPT
AI agents connected across a simulated financial market

Building a Financial Market
Inside a Computer.

How artificial intelligence is making it possible to simulate thousands of investors, experiment with financial crises and potentially understand the behaviour of markets in ways we never could before.

Andrew Stallwood-Keegan ·

Last night I attended a conference on agentic AI in financial services. Much of the discussion concerned the challenges you would expect from an industry entrusted with trillions of pounds of other people's money: regulation, accountability, model security, operational resilience and the question of how much autonomy we should actually give intelligent machines. All important subjects, particularly when the machines in question are increasingly capable of making decisions and executing transactions without human intervention.

But one discussion caught my imagination more than anything else that evening, and I've found myself thinking about it ever since. Researchers and financial institutions are beginning to experiment with something rather extraordinary: building artificial financial markets populated by thousands of autonomous AI agents, each behaving as an individual market participant, making investment decisions, reacting to information and influencing the behaviour of everybody else.

Read more…Continue reading on Substack
AI & HUMAN PROGRESS / EXCERPT
Two imagined AI futures: dystopia and technological abundance

We Were Promised the Terminator.
We Might Get Star Trek.

How artificial intelligence could deliver the most extraordinary period of human progress in history.

Andrew Stallwood-Keegan ·

Hollywood has spent the better part of fifty years preparing us for the arrival of artificial intelligence, and apparently the first thing it intends to do is kill us. In The Terminator, an American defence network becomes self-aware, decides humanity is an inconvenience and initiates nuclear Armageddon. Terminator 2: Judgment Day improved upon the formula by introducing a liquid-metal assassin that could impersonate practically anybody. Stanley Kubrick's 2001: A Space Odyssey gave us HAL 9000, an intelligent computer that concludes the mission would proceed considerably more efficiently without its human crew. The Matrix went further still, reducing humanity to a captive biological resource, imprisoned inside an artificial reality.

There is a remarkably consistent theme running through these films. The moment a machine develops anything approaching human intelligence, it apparently acquires our least attractive characteristics, together with an irresistible desire to exterminate its creators. Intelligence, we are encouraged to believe, is inherently dangerous, particularly when it doesn't need sleep, doesn't get bored and cannot be persuaded to take early retirement.

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AI, AUTHORITY & ACCOUNTABILITY / EXCERPT
Human computers working in a historical office transition into a modern AI-enabled enterprise

From Human Computers
to Accountable Autonomy.

Decision Rights and Institutional Responsibility in the AI-Native Enterprise

Andrew Stallwood-Keegan ·

The central question facing large enterprises in the age of artificial intelligence is not whether machines will make decisions, because in many operational environments they already do. The more serious question is whether institutions can redesign their operating models, governance structures and accountability frameworks quickly enough to remain in control of decisions increasingly shaped, sequenced or executed by intelligent systems. This is not a narrow technology question. It is a question about authority, institutional design and the future architecture of accountable enterprise behaviour.

In 1979, IBM captured a principle that became one of the most durable management assumptions of the digital era: a computer can never be held accountable, therefore a computer must never make a management decision. The statement was not merely a technical caution from the mainframe age. It expressed a deeper truth about the relationship between calculation, judgement and responsibility. Machines could process information, but they could not stand inside the moral, legal or institutional chain through which consequential decisions acquire legitimacy.

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AI, PENSIONS & POWER / EXCERPT
A pensioner and commuters beside the Thames, looking towards Parliament

A richer Britain.
Whose dividend?

Labour says AI will make Britain richer. So why are pensioners being cut out of the dividend?

Andrew Stallwood-Keegan ·

This isn’t just any Labour government. It is a Labour government taking Britain through the next industrial revolution. Let the importance of that statement sink in for a moment. We are living through what may prove to be the most consequential economic transformation in more than a century.

Governments do not build economic policy around the world as it looks this afternoon. They build roads for traffic that does not yet exist, power stations for electricity demand decades away and defence programmes around threats that may not materialise for twenty years. The Treasury models the finances of people who have not yet retired, workers who have not yet entered the labour market and taxpayers who have not yet been born. Long-term government is, by definition, an exercise in imagining the future. Which makes Labour’s treatment of artificial intelligence and pensions rather interesting.

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POLICY & POWER / EXCERPT
Whitehall and the Houses of Parliament in the sunshine

Free care.
At what cost?

Pensions, robotics and the hidden economics of free personal care.

By Andrew Stallwood-Keegan

Most people think about the next few years. Governments think in decades because they have to. You worry about next year’s mortgage, whether your pension will stretch far enough and what happens if you eventually need care. The Treasury worries about what tens of millions of people will cost in 2035, 2045 and 2055. It models demographics, pensions, productivity, debt, healthcare and the future labour market because running a country requires rather more forward planning than deciding what to have for dinner.

That matters when a government makes a promise whose serious costs will arrive decades from now. Labour has proposed a National Care Service providing free personal care for older people, alongside a change to the State Pension triple lock from April 2030. The Government estimates that the pension change will reduce future state-pension spending by £15 billion a year by 2039–40 and £50 billion a year by 2049–50 in nominal terms. The care service, meanwhile, will be introduced progressively as the new settlement develops.

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