AI stocks: The developers, the enablers and the winners

The regulatory filing by Anthropic in the US formally fires the starting gun on the company’s Initial Public Offering (IPO) and its path to becoming a publicly owned firm whose shares trade on a US stock exchange.

This deal comes hot on the heels of SpaceX’s listing in June, when the sale of $75 billion in shares put a valuation of $1.75 trillion on Elon Musk’s rockets-to-AI-to-satellites firm.

Anthropic seems determined to come with an even bigger price tag at $2 trillion, but investors need to ask themselves when – or whether – the company can generate enough profits and cash flow to justify what would be the seventh-largest stock market capitalisation of any company in the world, based on current valuations. The spending by the large language model (LLM) developers and AI labs is clearly filtering down to a whole host of companies through a growing and complex food chain, that stretches across a range of areas:

• Firms such as OpenAI and Anthropic through to data centre and cloud computing giants Microsoft, Amazon and Alphabet (who are also developing their own AI and LLM offerings), as well as Oracle;
• Fledgling so-called neocloud providers of AI infrastructure and data centres such as Coreweave, Nebius and Iren;
• Providers of construction equipment for the building of the data centres, such as Caterpillar;
• Experts in areas such as water and power supply, cooling systems and connectivity to ensure the data centres run as efficiently as possible, such as Vertiv, Eaton, Schneider, Siemens, XP Power and Computacenter;
• Baseload power providers in new areas such as small modular nuclear reactors that could ease the strain on existing energy supplies and grids, including Oklo and NuScale, or the UK’s Rolls-Royce;
• Flash memory and data storage drives and cards, as made by SanDisk, Seagate, Western Digital;
• A range of silicon chip makers including, graphics processing unit (GPU) designer Nvidia and its key foundry manufacturing partner TSMC, customer accelerator (XPU) expert Broadcom, central processing unit (CPU) makers Intel and AMD or memory chip giants Micron, Samsung Electronics and SK Hynix;
• Semiconductor production equipment specialists such as ASML, Applied Materials, KLA and Tokyo Electron.

China has its own, rival AI developers, such as DeepSeek, Moonshot AI and Alibaba, who can draw on their own food chain of suppliers and whose DeepSeek, Kimi and Qwen models are looking to challenge OpenAI’s ChatGPT, Anthropic’s Claude, Meta’s Muse, SpaceX’s Grok, Microsoft’s Copilot and Amazon’s Nova.

Major spending spree

The spending arms race between the major AI labs has gone up several gears since OpenAI launched ChatGPT in November 2022 and DeepSeek launched R1 in January 2025.

As a result, David Roche of Quantum Strategy & Geonomics think tank asserts that US companies alone have invested $3.1 trillion in AI since 2013, including off balance-sheet commitments such as leases on data centres, a figure that, in his words, ‘is bigger than the combined cost of the Vietnam War, the Interstate Highway System, the Apollo program, the Marshall Plan, and the eradication of polio.’

The AI labs and hyperscalers are committed to a further $3 trillion in spending by 2030.

Investors are watching the supply chain

All of that cash is flooding through the food chain, to the particular benefit of the enablers of AI and the providers of modern-day picks and shovels, rather in the same way that it was the sellers of mining equipment who did rather better than the prospectors themselves during legendary American gold rushes of the nineteenth century.

This can be seen in the booming profits generated by the memory providers, silicon chip makers and semiconductor production equipment producers, and how well their share prices have done, especially in the US.

The Philadelphia Semiconductor Index, or SOX, a 30-stock basket of leading silicon chip designers and makers and semiconductor production equipment manufacturers has gone into orbit.

The benchmark has been buoyed by rapid revenue and profits growth across the industry, where annual sales could hit $1.5 trillion for the first time ever in 2026, according to leading consultants.

UK AI beneficiaries

The power of AI spending can be seen in the UK equity market too, given the lofty positions in the FTSE 350’s share price performance rankings of XP Power, Raspberry Pi and Computacenter. Computacenter currently tops the FTSE 100 this year, while XP Power and Raspberry Pi rank in the top three for the FTSE 250.

By contrast, not one of the Magnificent Seven of Alphabet, Amazon, Apple, Meta Platforms, Microsoft, Nvidia and Tesla features in the list of the top performers in the US.

Only three of those seven have managed to outperform the S&P 500 in 2026 to date and Oracle’s shares have been the worst of the lot. Its newly issued bonds are faltering, too.

Oracle’s woes relate to the substantial amount of borrowing it is using to fund data centre construction. The Magnificent Seven seem to be weighed down by concerns over competition from China, whether stories of ‘rogue’ AI activity will put off potential consumer and corporate users and how the hyperscalers’ massive expenditure is to be funded.

Even some of the Magnificent Seven are now either raising equity, debt or both as their previously prodigious cash flow wilts in the face of their substantial upfront spending commitments.

Big tech’s lack of disclosure

Not one of Microsoft, Alphabet, Amazon or Meta do a particularly good job at disclosing how much money they are making (or losing) as they develop their AI offerings, although Alphabet, Amazon, Tesla, Microsoft and Nvidia are booking capital gains on their equity investments in OpenAI, SpaceX and other developers as funding rounds boost their respective valuations.

SpaceX does disclose how much its AI system Grok is losing. In the first six months of 2026, SpaceX’s AI business generated $1.5 billion in sales and $2.5 billion in operating losses.

Anthropic reportedly made an $8 billion operating loss on $4.6 billion of sales, according to unofficial reports. The company’s sales have rocketed since then, judging by management’s statements that July’s annualised run rate (ARR) for sales was $65 billion, but ARR is not recognised under generally accepted accounting principles (GAAP) and the company’s claims it made a profit in the second quarter of 2026 appear to rely on adjusted earnings which exclude several key lines of costs, rather than GAAP standards.

As such, the further away companies are from the actual spending on AI and LLM development, and the closer they are to receiving that money, the better they seem to be doing, at least for now.

Justifying valuations

For the developers and labs to justify their stock market valuations, actual in the case of SpaceX or putative in the case of Anthropic and OpenAI, they will need to start to show a return of some kind on their investment at some stage.

The question is how patient investors will be, and whether LLM developers spark renewed enthusiasm and higher valuations, or disappointment that ripples across the entire AI supply chain.

LLMs may be just one part of the AI story, as companies develop smaller proprietary models while AI research unlocks opportunities in fields such as energy, healthcare and materials.

After all, anyone looking at the stock market landscape in 2000, just as the technology, media and telecoms bubble burst, would have had a hard time looking beyond Cisco, Intel, Nokia, Lucent and Nortel as the most likely future winners. By the same token, it would have been awfully difficult to pick out Amazon, Alphabet or Meta as this century’s biggest winners, at least to date.

Amazon was a loss-making bookseller, Google (as Alphabet was then) was just two years old, and Meta Platforms (Facebook back then) did not come into existence in 2004.