AI Hype Fuels Trillion-Dollar Software Selloff as Investors Overbet on Tech Winners

Market participants experienced significant volatility last week while grappling with the profound disruptions that artificial intelligence is poised to unleash across various global sectors. Additional challenges could surface throughout this week as well. However, according to a recent client note from Deutsche Bank, this kind of market correction was entirely foreseeable, representing a necessary recalibration of expectations that may have been excessively rosy in the past.

Particularly hard-hit were software companies, which faced a dramatic downturn fueled by growing fears that advanced large language models could supplant existing service-based products. The fallout extended beyond tech into areas like legal services, information technology support, management consulting, and logistics operations, where firms also saw substantial declines in their valuations. Analysts at JP Morgan estimated just last week that approximately $2 trillion in market capitalization had evaporated from the software sector alone due to these AI-driven pressures—a development that, prior to the past two weeks, Deutsche Bank’s Jim Reid described as more theoretical than actual.

Reid, who has long anticipated a sell-off of this magnitude, shared with clients that for several months, his consistent perspective has been that the ultimate victors and vanquished in this revolutionary technology remain shrouded in uncertainty. Nevertheless, as late as October, financial markets were effectively embedding assumptions of a scenario in which virtually all technology firms would emerge triumphant.

In the ensuing weeks, a more grounded assessment has begun to take shape within the technology space, fostering clearer distinctions between outperformers and underperformers. Yet, this revaluation process is now extending rapidly into wider economic segments, catching many off guard with its velocity.

Reid is far from the only voice cautioning that investors might have been applying an overly uniform layer of optimism across the entire equity landscape and even the broader economy. Certain market observers have advanced sweeping claims that AI’s productivity enhancements would deliver advantages to nearly all enterprises. Meanwhile, others maintain that although the AI phenomenon does not constitute a full-blown bubble, specific areas of excessive enthusiasm could still deflate abruptly.

JPMorgan Chase CEO Jamie Dimon exemplifies this balanced viewpoint. During his remarks at last year’s Fortune Most Powerful Women Summit, he urged businesses to actively integrate AI into their operations. That said, he offered a tempered perspective, drawing parallels to 1996 when the internet’s potential was genuine but often misconstrued as a bubble. Dimon highlighted a crucial differentiation between general AI advancements and generative AI specifically, noting that while some asset valuations have climbed into bubble-like territory, the foundational technology holds substantial promise.

Emeritus Finance Professor Jeremy Siegel from The Wharton School at the University of Pennsylvania similarly views these market movements as a healthy sign of discernment. In a recent commentary for WisdomTree, where he holds a senior economist role, Siegel emphasized that when corporations announce massive capital outlays—such as $200 billion—investors ought to rigorously evaluate return timelines, competitive landscapes, and the feasibility of establishing lasting competitive advantages amid hyper-rapid technological evolution. This dynamic, he explained, underpins ongoing shifts in market leadership, even as the overarching AI narrative endures.

Nevertheless, Reid posits that the current adjustments might be veering into overreaction territory, particularly in traditional or ‘old economy’ industries, where the extent of disruption appears exaggerated. He contends that even by year’s end, definitive data on enduring winners and losers will remain elusive, leaving ample space for investor sentiment to swing wildly between euphoria and despair. Consequently, pronounced fluctuations in market mood are likely to persist as the dominant pattern.

Thin ice

The trepidation surrounding AI’s disruptive potential stands in stark contrast to other forms of market recalibrations, according to economist Ed Yardeni, as it creates a self-perpetuating cycle of caution and selling pressure. Yardeni, president of the respected Yardeni Research firm, likened AI’s trajectory over the weekend to ‘speed skating on thin ice.’ Although technological breakthroughs routinely upend established norms, he warned, AI possesses a unique capacity to undermine even its own progenitors.

This stems from AI’s proficiency in generating software code, encompassing AI-specific code, enabling it to cannibalize prior iterations and render them obsolete at an unprecedented pace. The velocity of depreciation is accelerating dramatically for both AI hardware components and software solutions, especially large language models. This rapid obsolescence has lately unnerved investors, prompting widespread sell-offs targeting any enterprise potentially vulnerable to AI-induced transformations.