The message from investors to the software, wealth management, legal services and logistics industries this month has been clear: AI is coming for your business.
The release of new, ever more powerful AI tools has coincided with a stock market slide, which has swept up sectors as diverse as drug distribution, commercial property and price comparison sites. Advances in the technology are giving increasing credulity to predictions that it could render millions of white collar jobs obsolete – or, at least, eat into the profits of established companies.
Carl Benedikt Frey, the author of How Progress Ends and an associate professor of AI and work at the University of Oxford, says investors are reassessing the value of companies that rely heavily on selling software or specialist knowledge.
“AI turns once-scarce expertise into output that’s cheaper, faster, and increasingly comparable, which compresses margins long before whole jobs disappear.”
Fears over widespread job losses were amplified this week by a viral essay, penned by AI entrepreneur Matt Shumer, titled: Something big is happening. In it, Shumer purports to explain to the world outside of Silicon Valley that new models will come for coding jobs and then “everything else”, comparing the present moment with the February just before the Covid pandemic.
The post was viewed 80m times on X, triggering fear and fury – including from people pointing out that Shumer has a history of AI hype. (He previously excited the internet by announcing the release of the world’s “top open-source model”, which it was not.)
Shumer and the markets were reacting to the capabilities of recently released models such as Anthropic’s Claude Opus 4.6 and OpenAI’s GPT-5.3-Codex, both improvements on previous, powerful AI products.
But there are other reasons for the febrility of the moment, not least the companies that are building these models. AI “hyperscalers” – the term for the big US tech players in the field – collectively plan to spend $660bn (£484bn) this year. This follows a year of colossal, often circular deals between the world’s biggest tech companies.
However, cracks have appeared in these numbers, as well as questions about what they actually mean. Nvidia and OpenAI recently appeared to drop a $100bn deal, replacing it with an as yet unknown, smaller commitment.
Meanwhile, none of the AI model-builders – not OpenAI, xAI or Anthropic – have a clear path to the enormous revenue that would justify this spend; the revenue from the entire global software sector this year is projected to be just $780bn.
It has appeared this week that both arguments about AI – that it is an unsustainable boom or heralds a destructive revolution in white-collar work – have been entertained by some investors, after shares in Google’s parent company, Alphabet, and Mark Zuckerberg’s Meta were affected by apparent concerns about a spending bubble.
Bluntly, investors expect these companies to recoup their investment via hordes of individuals and businesses paying for their tools, because they allow certain tasks and jobs to be carried out by fewer people or over fewer hours. Or in economic jargon, a productivity boom.
“The two themes are inherently linked but not necessarily contradictory,” says Jason Borbora-Sheen, a portfolio manager at investment management firm Ninety One.
At first, investors backed expenditure by the “hyperscalers” in the initial phase of the AI goldrush. Those concerns have now flipped to cash burn and the sheer scale of investment needed to stay competitive, says Borbora-Sheen, while at the same time the share prices of wealth managers and others have been affected by the perception that AI is “now here, will evolve and can displace”.
Companies have cited AI as an influence on job cutting plans, including British American Tobacco this week, but there has not been a wave of wholesale disruption yet. Greg Thwaites, a research director at the UK thinktank the Resolution Foundation and an associate professor at the University of Nottingham, says evidence of a tangible AI jobs impact on major western economies is “quite ambiguous so far”.
Not all white collar work will be affected, he says, although AI might test axioms around the age-old capitalist concept of “creative destruction”, which involves entirely new jobs replacing outdated ones, like car mechanics replacing farriers. Will AI be a different case because the change has come so fast or because it will be good at absolutely everything?
He adds: “There are some jobs that are going to look very different quite quickly. But the idea that there are going to be bands of unemployed lawyers and accountants roaming around London within a few years seems like a stretch to me.”
Alvin Nguyen, an analyst at Forrester, says the fears that shook the stock market are based on sentiment and not evidence: no one has had time to evaluate the performance of an Opus 4.6-powered wealth manager.
“It’s a knee-jerk reaction,” he said. “How true is it? Look, there’s plenty of leaders out there who thought, I can replace people with AI at the beginning. And a lot of people acted on that. And I think one of the things that’s being found out is that for a lot of cases, no, it hasn’t panned out.”
Aaron Rosenberg, a partner at venture capital firm Radical Ventures, – whose investments include leading AI firm Cohere – and former head of strategy and operations at Google’s AI unit DeepMind, says the impact of AI is being underestimated in the long term but adoption of groundbreaking models will not be uniform.
“History shows a repeated pattern of there being a significant lag between a technology working in a lab and it permeating the wider economy, as well as a chasm between early adopters and the majority of users,” he says.
More new models will come; other huge AI deals could wobble as well. Meanwhile, this month there were low-level rumblings of discontent from high-profile tech workers; a slew of departures from AI companies for reasons as various as boredom, AI doomerism and concerns over the prospect of adult content in ChatGPT.
There is a nervous, unfocused energy afoot. As Borbora-Sheen says: “There is a strong winners versus losers dynamic.”
