Electricity transformed the world, not simply because it existed but because of what it made possible. That distinction may prove important as we think about Artificial Intelligence (AI).
In 1882, Thomas Edison built the world’s first commercial power station at 255 Pearl Street in Lower Manhattan, New York. The incandescent light bulb was revolutionary, but the real breakthrough was the system behind it: the generators, cables, meters and distribution network that moved electricity from labs into homes and businesses.
By 1900, investors knew electricity would change the world. What they did not know was which companies would win, how long it would take or where the profits would accumulate.
The economic winners were not always obvious. Electricity utilities became essential, but many of greatest profit pools emerged in factories, new industries and business models enabled by electricity. The same applies to AI: we know it will change the world; what we don’t know is where the enduring economics will settle.
Today, semiconductor designers, equipment manufacturers and infrastructure providers are earning extraordinary returns from the AI buildout. But it would be a mistake to assume that tomorrow’s profit pools will look the same as today’s. Many companies at the centre of the AI narrative remain only modestly profitable or loss-making, so their valuations depend heavily on assumptions about future cash flows.
Every era has its transformational technology
In the 1920s, radio was the internet of its time.
Its adoption was explosive. US radio stations grew from just five in 1921 to more than 500 by 1923, while equipment sales rose from $60 million in 1922 to more than $840 million by 1929. It had become one of the defining technologies of its age.
At the centre was RCA. Between 1921 and its 1929 peak, RCA’s share price rose almost 100-fold as investors bet that radio would change the world. They were right. But by 1932, despite radio’s continued rapid spread, RCA’s share price had fallen almost 98%.
The lesson is that technological success and investment success are not always the same thing. The investors may correctly identify the future and still misjudge where the economics will settle.
Yes, AI is here, but something unusual is happening
The world’s greatest software companies have started behaving more like infrastructure businesses. Microsoft, Amazon, Alphabet and Meta are undertaking one of the largest private infrastructure buildouts in modern history, spending heavily on data centres, semiconductors, servers, networking equipment, land, power and cooling.
The numbers are striking. Microsoft’s net property and equipment rose from $135.6 billion in 2024 to $205 billion in 2025, much of it related to data centres.
More of the cash these companies generate is reinvested into physical infrastructure. Balance sheets, once dominated by intangible assets, are increasingly filled with tangible infrastructure and land. The language remains digital, but the economics is becoming industrial.
For decades, digital economy winners became more capital light as they grew. Today, AI leaders appear to be becoming more capital intensive.
The question for investors is profound: what happens to returns on capital, profitability and valuation multiples when software businesses begin to resemble infrastructure businesses?
AI is often described as the next software revolution. But the scale of investment suggests another possibility: AI may prove less like the internet and more like electrification.
Electricity became a foundational input across world industries. Factories did not become electricity companies; they became factories powered by electricity. Banks, retailers, asset managers and manufacturers may likewise become powered by AI.
If so, the largest profit pools may not accrue only to those building AI. They may emerge in industries and business models that use it to reshape how value is created.
People tend to imagine the future as an improved version of the present: a faster horse, attributed to Henry Ford who once said, “If I had asked people what they wanted, they would have said faster horses.”
Yet major technological shifts can overturn the assumptions on which an industry is built.
We are already experiencing AI’s benefits as an asset manager. We can process more information, analyse more companies and investigate opportunities across more geographies with the same number of analysts.
But this may still be the “faster horse” stage of AI: using a new technology to perform existing tasks more efficiently.
The larger opportunities may emerge from businesses that use AI to change how an industry works, how value is created and where the profit pool accrues.
History teaches us that profit pools do not simply grow; they move
The internet did not merely expand existing profit pools. It disrupted them, redirected value away from incumbents or created entirely new ones. AI may do the same.
As investors our task is to watch where AI disrupts, enhances or reprices profit pools. We cannot know with confidence where the greatest value will accrue, but AI could materially change the economics of many industries.
Some of the most important beneficiaries may not be today’s AI leaders: model developers, semiconductor companies or cloud providers. They may not even exist yet.
AI may become as foundational as electricity. If it does, the largest winners may be those that use it to rewrite the rules of the game.
AI may be inevitable. Investment returns are not
Pearl Street in New York offers a useful reminder. Investors recognised electricity’s transformative potential but could not know where the economics would ultimately settle.
AI may prove similar. The technology appears transformative, the adoption inevitable and the investment opportunities enormous. Our task is not simply to predict whether AI will change the world, but to identify where the profit pools migrate, who captures them and whether today’s price reflects those possibilities.
History rarely provides answers. It often provides better questions. The most important question today is not who is building AI, but who will ultimately use it to change the rules of the game. Technology changes the world. Economics determines the winners.
