UBS chief executive Sergio Ermotti said investors in artificial intelligence had pushed company share prices to levels that assumed all was well before a recent market downturn forced a reality check.
Speaking at a financial industry conference in Sydney, Australia, Ermotti said the recent drop in AI-related shares was a healthy correction to unrealistic expectations. For months, buyers have been pouring capital into technology companies developing generative AI tools, computer chips and data facilities, pushing valuations to historic highs. Ermotti said that before the pullback, markets had essentially been “pricing perfection”, valuing companies as if commercial profits and wide-scale adoption would come without political, technical or regulatory hurdles.
For the lay reader, who doesn’t know investment jargon, “pricing perfection” means stock prices have climbed so high that companies have to meet impossible financial targets to justify what buyers paid for them. When a company is priced for perfection, even small delays, rising development costs or minor policy shifts can spark broad selloffs. When share values fall 10% or more from a recent peak, analysts call the decline a “correction”.
Ermotti said he believes artificial intelligence will eventually deliver strong economic benefits, but the timeline public markets expect for those financial gains is unrealistic. Building the physical infrastructure needed to run complex AI models – specialised semiconductors, energy-hungry data warehouses, and stable electrical grids, for instance – takes a lot of time and capital.
Political and regulatory uncertainty has further complicated the immediate outlook. Ermotti pointed to the recent US midterm election results and a growing international discussion about the safety, governance and infrastructure demands of deploying AI. Investors were unnerved by political changes in Washington that raised the prospect of stricter regulatory oversight, more antitrust scrutiny and possible curbs on exports of advanced computing hardware. Those worries sparked a sell-off that erased trillions of dollars in paper value from global stock exchanges before equity markets partially steadied late in the week.
The chief executive also provided insight into how technology integration works in large financial institutions. UBS’s own rollout of artificial intelligence tools had slowed because of the giant corporate integration of Credit Suisse, Ermotti said. UBS agreed in 2023 to buy its former domestic rival in an emergency rescue orchestrated by Swiss authorities. UBS has had to spend major operational resources merging two global banking systems, reconciling balance sheets and managing separate corporate IT architectures, which has delayed the bank’s own technology upgrade schedules.
The collapse and emergency rescue of Credit Suisse also triggered political debate in Switzerland about the long-term stability of the financial system. Swiss lawmakers and financial regulators have proposed tougher capital rules and stricter compliance requirements for UBS to prevent future taxpayer bailouts. The Zurich-based institution is now looking into how these regulatory requirements could affect its competitiveness against rival investment banks in New York, London and Singapore.
Speaking about the domestic political environment in Switzerland, Ermotti said the Swiss reaction had been unusually emotional and different from that of other international financial centres. He noted that in the US and the European Union, regulatory agencies have generally been more cognisant of the unintended consequences excessive statutory rules can have on business lending and global competitiveness.
The rout in tech stocks points to a pattern that repeats in major industrial revolutions. From the earliest days of personal computing to the explosion of internet commerce, new technologies experience an early phase of feverish investor speculation, followed by sharp market declines as the logistical hurdles to commercial application become apparent. Ermotti’s comments reflect a common sentiment among institutional investors: as artificial intelligence continues to reshape corporate productivity, the journey from lab breakthroughs to steady corporate profits will likely be longer and more volatile than the giddy stock market valuations initially implied.
