The AI Boom Is Real. But Who’s Actually Making Money?

Companies are shoveling hundreds of billions into AI, but the biggest winners might not be the ones building it. And investors would be wise to follow the profits.

• AI investment has already surpassed the peak of the dotcom-era telecom boom, but history shows that transformative technologies don’t always deliver strong returns for investors.
• The AI boom’s profits are unevenly distributed, with chipmakers capturing the lion’s share while AI developers struggle to turn rapid revenue growth into profits.
• AI’s biggest long-term winners may be the businesses using cheaper AI to boost productivity, rather than those spending billions to develop the technology.

The recent selloff in AI stocks has brought a growing investor concern into sharper focus. Companies are pouring eye-watering sums into chips, data centers, and the infrastructure needed to power AI, but there’s a larger question hanging over all that spending: whether it’ll actually pay off.

AI keeps getting smarter and more capable, but the financial rewards are proving a lot harder to pin down.

That’s one of the big takeaways from a new white paper from L&G economist Matthew Rodgers. In the research, he digs into the sheer scale of AI investment and the uncertainty surrounding its payoff. And he makes an important point: a technology can transform the economy without every company behind it making a fortune.

For investors, that means it’s essential to look beyond the hype to see where the cash is going, who’s making money, and whether the profits can last.

Welcome to the biggest infrastructure boom in decades.

The amount of money flowing into AI is staggering. L&G estimates that AI infrastructure spending will be equal to about 1.3% of the total US economic output this year. That’s hundreds of billions of dollars going toward data centers, chips, and the electricity to run them.

For perspective, that’s already slightly above the 1.2% reached during the telecom infrastructure boom at the turn of the millennium. It’s still well below the railroad boom of the 19th century, when investment peaked at nearly 5%. But make no mistake: this is one seriously hefty infrastructure spending spree.

Past performance is not indicative of future results.

AI investment recently surpassed peak early-2000s telecom spending but remains well below historical railroad investment. Data as of July 2026. Sources: NBER, FCC/US Telecom, company filings, L&G.

History comes with a warning, though.

The railway boom transformed transportation, and the telecom boom helped lay the foundations for the modern internet. But neither guaranteed handsome returns for the investors financing them. In some places, companies built far more infrastructure than they needed. Competition drove down prices, and plenty of companies struggled to earn enough to cover what they’d spent.

That doesn’t mean AI is destined for the same fate. In fact, L&G is siding with the optimists, at least for now. AI developers are still paying top dollar for every new chip, and each new generation of AI models seems to bring another leap in what the technology can do. So far, there’s little evidence that the industry’s appetite for computing power is fading.

Still, that doesn’t necessarily mean that strong demand will lead to strong investment returns. Companies could be right about AI’s enormous potential and still end up spending more than they can profitably recover. After all, the ultimate test isn’t how much infrastructure gets built or even how useful it becomes – it’s whether the companies financing it can earn enough to justify the cost.

And that’s where the story gets particularly interesting, because the profits from the AI boom aren’t being shared equally.

Follow the profits, not just the spending.

There’s an awful lot of money changing hands in AI, but the companies involved aren’t benefiting equally.

L&G’s research highlights an interesting divide between three parts of the industry – infrastructure suppliers like Nvidia and TSMC, data center and cloud computing providers like Microsoft and Amazon, and AI developers like OpenAI and Anthropic.

And the differences in profitability are striking. Infrastructure suppliers in L&G’s analysis have operating profit margins of around 51%, while the group containing major cloud computing providers has margins of roughly 30%. AI developers, meanwhile, are losing around 45 cents from operations for every dollar of sales – despite their rapidly growing revenue. In other words, the companies building the brains behind AI aren’t necessarily the ones making the most money from it.

Past performance is not indicative of future results.

Profitability across the AI supply chain. Infrastructure stocks are Nvidia, TSMC, and ASML. Cloud and data centers are Microsoft, Google, Amazon, and CoreWeave. AI developers are OpenAI, and Anthropic. Sources: Bloomberg, The Information, FT, L&G.

That makes sense for now.

AI developers are spending heavily on research, computing power, and talent as they race to build better products and attract customers. According to L&G, their computing costs alone eat up about three-quarters of their revenue.

Of course, today’s winners won’t necessarily be tomorrow’s. If infrastructure spending slows, chipmakers could face weaker demand and greater competition. AI developers have their own challenges, particularly as increasingly capable, freely available models make it harder to charge premium prices. And data center operators could eventually find themselves fighting harder for customers if the industry builds more computing capacity than it needs.

There’s an important caveat here, too. Companies like Microsoft and Amazon rake in profits from businesses that have little to do with AI. So their overall profit margins don’t tell us exactly how profitable their AI investments are.

And while spreading your money across chipmakers, cloud providers, and AI developers might seem like a sensible way to manage these risks, there’s a potential snag there: those businesses are more closely connected than they might appear. A slowdown in AI spending could hurt several of them at once.

There’s another possibility worth considering.

As AI becomes cheaper and more widely available, some of the biggest winners could ultimately be the companies that use the technology, rather than those that develop it. After all, businesses that can boost productivity without spending billions building AI models could be well-positioned to benefit.

And that’s an important insight – because AI could become an enormous economic success even if some of today’s biggest AI investments disappoint.

A winning technology isn’t always a winning investment.

You don’t have to be an AI skeptic to be cautious about AI stocks.

L&G remains broadly optimistic that the technology will boost productivity and transform industries over time. And I largely agree. The uncertainty lies in how much of that economic value today’s AI companies will actually capture.

Take the falling cost of AI tools.

That shift is already underway – L&G’s data shows that average prices for one group of AI models meeting a minimum performance standard fell by more than 80% between early 2025 and mid-2026. As those costs decline, more businesses will adopt AI, improving their productivity and potentially creating entirely new products and services.

Past performance is not indicative of future results.

Average price per million tokens for AI models scoring 20 or more on the Artificial Analysis Intelligence Index. Data as of June 2026. Sources: Artificial Analysis, L&G.

That’s good news for the economy – but lower prices could also squeeze the profits of companies selling those tools. Consumers and businesses using AI might end up capturing much of the benefit instead.

Something similar could happen with data centers, too. If providers build capacity with the expectation that demand will keep soaring, they may eventually find themselves competing harder for customers, putting pressure on what they can charge. The infrastructure could remain enormously useful even if its owners struggle to earn attractive returns.

And that’s why share prices matter just as much as the technology itself. A company could grow rapidly, increase its profits, and still turn out to be a disappointing investment if investors paid a price that assumed even greater success. Conversely, businesses with lasting competitive advantages and more reasonable valuations could continue to reward shareholders as AI spreads.

That’s why investing in AI isn’t simply about identifying the most exciting technology or the fastest-growing company. It’s about finding businesses that can turn the opportunity into lasting profits – and buying their shares at a reasonable price.

And finally, here’s what this means for investors.

The AI boom still offers plenty of opportunities, but picking the winners will require looking beyond impressive technology and soaring sales.

Here are three things worth keeping in mind.

First, follow the cash. A company can report rapid sales growth while spending even faster on chips, data centers, and other infrastructure. So pay attention to free cash flow – the money a business has left after covering its operating costs and investments. Firms that can turn AI demand into growing cash flow without constantly ramping up spending may be better placed to reward shareholders over time.

Second, look for advantages that can last. Today’s market leaders won’t necessarily stay ahead forever. As competition heats up and AI tools become cheaper, businesses with strong customer relationships, unique technology, or other advantages that rivals can’t easily copy may be better positioned to protect their profits. The same applies to the companies using AI to lower their costs – particularly those that can keep the savings instead of passing them on to customers.

Third, don’t overlook the price. Even a brilliant business can be a bad investment if you pay too much for its shares. And owning several AI-related stocks doesn’t necessarily mean you’re diversified, especially when their fortunes depend on the same spending boom. Checking how much of your portfolio is tied to AI could help avoid taking on more risk than you intend.

Ultimately, AI doesn’t need to be a bubble for some investments to disappoint. The technology could transform entire industries and create enormous wealth, but that doesn’t mean every company involved will walk away richer.

For investors, the real opportunity lies in finding businesses that can turn AI’s promise into lasting profits – without paying too much for them.

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Originally Posted November 4, 2026 – The AI Boom Is Real. But Who’s Actually Making Money?