This month, a definitive message has emerged from investors to industries like software, wealth management, legal services, and logistics: the rise of AI is set to disrupt your business landscape.
The introduction of increasingly sophisticated AI tools coincides with a downturn in the stock market, impacting diverse sectors, including drug distribution, commercial real estate, and price comparison websites. As technology advances, alarming predictions suggest that millions of white-collar jobs could be at risk of becoming obsolete or that established companies’ profits may take a significant hit.
Carl Benedikt Frey, author of *How Progress Ends* and an associate professor of AI and work at the University of Oxford, notes that investors are reevaluating the worth of firms that heavily rely on software or specialized knowledge.
“AI transforms formerly rare expertise into output that is cheaper, faster, and more widely comparable, which ultimately compresses profit margins even before jobs disappear,” he observes.
Concerns about widespread job losses gained traction this week with the circulation of a viral essay by AI entrepreneur Matt Shumer, titled *Something Big Is Happening*. In this piece, Shumer warns that new models will encroach on coding jobs and subsequently “everything else,” likening the current situation to the period just before the COVID pandemic hit.
The post gained 80 million views on X, stirring fear and outrage, especially from those pointing out Shumer’s history of overstating AI advancements. (Previously, he garnered attention by announcing the release of the world’s “top open-source model,” which turned out to be not as groundbreaking as touted.)
Both Shumer and market analysts are reacting to the capabilities of new models such as Anthropic’s Claude Opus 4.6 and OpenAI’s GPT-5.3-Codex, which represent significant upgrades to existing AI technologies.
However, there are deeper factors contributing to the current anxieties, particularly regarding the firms developing these models. Known as “AI hyperscalers” — the major US tech players in this domain — they collectively plan to spend a staggering $660 billion (£484 billion) this year, following a year marked by extravagant, often circular partnerships between the largest tech corporations.
Yet, discrepancies have surfaced, raising questions about the true implications of these figures. Recently, Nvidia and OpenAI appeared to abandon a $100 billion deal, opting instead for a smaller, undisclosed commitment.
Despite this, none of the AI model creators, including OpenAI, xAI, or Anthropic, have a transparent pathway to the immense revenue required to sustain this investment; the entire global software sector’s projected revenue for this year stands at merely $780 billion.
Investor sentiments hint at both fears of an unsustainable boom and a revolutionary shift in white-collar jobs, with shares in Google’s parent company, Alphabet, and Mark Zuckerberg’s Meta feeling the strain due to worries about a potential investment bubble.
Simply put, investors anticipate that these companies will recover their investments as individuals and businesses increasingly turn to their tools, which allow certain tasks to be executed by fewer people or over shorter periods. This phenomenon is termed a productivity boom.
“The two themes are inherently linked but not necessarily contradictory,” explains Jason Borbora-Sheen, a portfolio manager at investment management firm Ninety One.
Initially, investors supported the expenditures of the “hyperscalers” during the early AI gold rush. However, concerns have shifted towards cash burn and the substantial investment required to maintain competitiveness, as share prices for wealth management and similar industries have declined due to perceptions that AI has arrived and has the potential to replace existing jobs.
Some companies have cited AI as a factor in their plans for job cuts, including British American Tobacco this week; however, a broad wave of disruption has yet to materialize. Greg Thwaites, a research director at the UK think tank the Resolution Foundation and an associate professor at the University of Nottingham, mentions that concrete evidence of AI’s impact on employment in large Western economies remains “quite ambiguous at this stage.”
Not all white-collar jobs will be affected, he argues, noting that AI might challenge traditional notions of “creative destruction” in capitalism — where fresh roles replace outdated ones, akin to car mechanics taking the place of farriers. Will AI prove to be an exception due to the speed of change or its capability across various tasks?
He further adds, “Some jobs will inevitably transform rapidly. Yet, the notion of hordes of unemployed lawyers and accountants roaming London within a few years seems far-fetched.”
Alvin Nguyen, an analyst at Forrester, suggests that the stock market jitters stem from sentiment rather than concrete evidence: no one has had the chance to assess the performance of a wealth manager operating on Opus 4.6.
“It’s a knee-jerk reaction,” he states. “To what extent is this valid? Many leaders initially thought they could replace staff with AI. While some acted on this belief, it is becoming evident that, in many instances, it hasn’t played out as expected.”
Aaron Rosenberg, a partner at venture capital firm Radical Ventures — which includes notable AI company Cohere among its investments and is a former head of strategy and operations at Google’s AI unit DeepMind — asserts that the long-term effects of AI are often underestimated. However, the adoption of groundbreaking models will likely be gradual.
“History has shown a recurring pattern of a significant delay between a technology proving successful in a lab and its widespread implementation in the economy. There is also a gap between early adopters and the majority of users,” he states.
More new models will emerge, and other significant AI partnerships may also falter. Meanwhile, recent reports indicate a wave of discontent among prominent tech workers, with a series of departures from AI companies due to various factors, including boredom, concerns about AI doomsday scenarios, and the potential for adult content in ChatGPT.
A palpable, unspecific anxiety fills the air. As Borbora-Sheen remarks, “There’s a strong dynamic at play between potential winners and losers.”
In summary, the AI revolution is reshaping industries in unforeseen ways, prompting investors to reevaluate the landscape profoundly. While speculation abounds regarding its long-term impact on employment and the economy, it is essential to tread cautiously, as the full consequences remain to be seen.
