THE £500BN AI SPENDING SURGE ISN’T WHERE THE REAL RETURNS LIE WARNS INVESTMENT EXPERT
ENTERPRISE SOFTWARE FIRMS EMERGE AS TRUE WINNERS OF AI REVOLUTION
A historic surge in global investment into artificial intelligence infrastructure is reshaping markets — but the companies capturing the greatest long-term value may not be the ones building the technology itself.
That is the view of investment specialist James Disney-May, who argues that while the AI boom has triggered unprecedented spending, the most durable returns are likely to accrue to businesses already embedded deep within enterprise workflows.
The scale of capital flowing into AI is difficult to overstate. “The AI spending wave is real and it is enormous. Goldman Sachs estimates hyperscale capital expenditure will reach $527 billion in 2026, with some forecasts putting the total closer to $700 billion,” said Disney-May.
“Jensen Huang called it the largest infrastructure buildout in human history at Davos. He is probably right.
“And for two years, the obvious trade was to back the companies supplying the hardware and compute that made it possible – Nvidia, the hyperscalers, the data centre operators. Goldman Sachs’ infrastructure basket returned around 44 per cent at its peak. The market was correctly pricing the first and most visible layer of demand.”
That first phase of the AI investment cycle — dominated by semiconductor firms, cloud providers and data centre operators — has delivered substantial gains. However, Disney-May suggests the market is now reassessing whether those building large language models and AI systems will ultimately capture the lion’s share of profits.
“The scale of spending is extraordinary. But extraordinary spending does not guarantee extraordinary returns. The market is beginning to realise that the biggest gains may not sit with the model makers,” he said.
The disparity between infrastructure investment and revenue generation is already becoming apparent. OpenAI, widely regarded as one of the most advanced AI developers, generated approximately $20 billion in annualised revenue last year — a significant figure, but modest relative to the vast capital deployed across the ecosystem.
At the same time, new entrants such as DeepSeek have challenged assumptions about the cost of building frontier-level models, demonstrating that cutting-edge systems may be developed far more efficiently than previously believed. That development has prompted investors to question whether high levels of capital expenditure will translate into sustained competitive advantage.
Meanwhile, enterprise adoption of AI is accelerating at pace. Corporate spending on AI solutions has surged from $11.5 billion in 2024 to $37 billion in 2025, underlining the growing demand for practical, revenue-generating applications.
Crucially, that spending is not flowing primarily to model developers.
“The more interesting businesses are not necessarily the ones building the best models. They are the ones already inside the workflow, with the data, the distribution, and a practical route to monetising AI,” Disney-May said.
“That is a less dramatic investment case, but often a more durable one.”
Sectors such as legal technology, financial compliance, healthcare software and procurement automation are emerging as key beneficiaries. These industries are integrating AI directly into everyday business processes, allowing them to capture immediate value through efficiency gains and enhanced decision-making.
ServiceNow provides a telling example. Earlier concerns that AI agents might disrupt its platform triggered a sharp sell-off, with the company’s share price falling by around 33 per cent. Yet the opposite outcome has materialised.
The company reported 21 per cent subscription revenue growth, secured 35 enterprise deals worth more than $1 million for its AI suite in a single quarter, and maintained robust forward guidance.
“The threat became a tailwind,” Disney-May noted.
Looking ahead, the rise of so-called “agentic AI” — systems capable of operating autonomously within enterprise workflows — is expected to reinforce this dynamic further. Rather than simply responding to prompts, these systems execute tasks, manage processes and make decisions within existing business structures.
That evolution, Disney-May argues, will deepen the advantage of companies already embedded in operational environments.
“Investors forget this in every technology cycle. The infrastructure layer can be essential without capturing all the value,” he said.
“Railways changed economies, but plenty of railway investors never saw the returns they expected. AI may follow the same pattern.”
For investors, the implication is clear: while AI developers are building transformative technology, the most attractive long-term opportunities may lie with companies that control distribution, data and customer relationships.
“The model makers are building something extraordinary. But the returns, when they come, are unlikely to be found there,” Disney-May said.
