AI is dominating tech conversations right now, and fashion is no exception. It’s being hailed for its potential to fix problems that have plagued the industry for decades — from product discovery and personalized marketing to sizing discrepancies among brands. But it costs a lot to invest in, and there are big question marks surrounding whether it can deliver the returns it promises, while its use can also spark consumer backlash. In recent weeks, these questions have intensified at a macro level, too.
Speculation is mounting that we’re living in an AI “bubble”, stoked by soaring tech company valuations, big-ticket deals and record spending on a technology whose promise has not yet translated into significant economic gains. Last week, equity markets in the US, Asia and Europe fell after some of the world’s biggest banks and investors warned that an AI-induced market correction could be on the horizon.
AI stocks — like Palantir, which dropped 8% — were among the hardest hit, after the CEOs of Goldman Sachs and Morgan Stanley said on a panel in Hong Kong on Tuesday that a 10-20% drawdown in equity markets was likely in the next one to two years. It comes after the UK’s central bank warned of a “sudden correction” in global markets due to investors’ increasing concentration on AI-related tech companies whose valuations “appear stretched”, which could leave markets in danger if AI fails to meet its expectations.
Are we in an AI bubble? And if so, what should fashion companies do?
Why a bubble?
Public and private investor enthusiasm for AI’s potential has reached new highs in the last few weeks, as AI chipmaker Nvidia became the world’s first $5 trillion company, and Apple and Microsoft both passed the $4 trillion mark, as share prices climbed. At the same time, private AI companies like OpenAI and Anthropic reached valuations of $500 billion and $183 million, respectively, in the last couple of months. Venture capital investors have now assigned almost 500 AI startups a valuation of $1 billion or more — so-called “unicorn” status — according to CB Insights, and ChatGPT maker OpenAI has signed a string of megadeals in 2025 totaling $1 trillion with other tech companies — including Oracle, AMD, Broadcom, Nvidia, and, this Monday, Amazon — to access their compute power to fuel its AI models.
At the same time, several of the biggest tech companies in the world used their Q3 earnings over the last fortnight to revise their previous AI spending forecasts upwards. All of the so-called “magnificent seven” tech giants increased their capital expenditure figures from previous estimates, telling investors that they will spend tens of billions more than originally planned on AI infrastructure this year. Microsoft said it spent $35 billion on AI infrastructure in the three months to the end of September, Google parent company Alphabet increased its capital expenditure forecasts for 2025 to between $91 billion and $93 billion, up from $75 billion earlier this year, and Meta said its capital expenditure would reach between $70 billion and $72 billion, as CEO Mark Zuckerberg told investors the company s strategy was to “aggressively front-load building capacity” to prepare for the arrival of AI “superintelligence”.
Fears around a potential bubble stem from the sheer speed at which so much money — and market concentration — is focused on AI as an asset, while the technology is yet to deliver on its lofty promises.
“We see a perfect AI bubble forming. Vast, concentrated sums of money are being invested in companies from Nvidia to Microsoft, all feeding off each other, meaning if one fails, they all fail,” says Fiona Harkin, director of foresight at Together Group’s The Future Laboratory. “At the same time, AI is not delivering the results that were promised, or as quickly as everyone thought.”
Prominent investors who were around during the last two major economic bubbles — the dot-com bubble of 2000 and the US housing bubble of 2008 — have begun to draw parallels with certain patterns in the current AI investment spree. James Anderson, a renowned UK investor who founded early Amazon backer Baillie Gifford, recently told the Financial Times that the pace of AI valuation increases was “disconcerting” and recalled the dot-com era pattern of vendor financing — where makers of the equipment that fueled startups’ new tech loaned their startup clients so they could buy their equipment, thus artificially inflating both their own sales and the startups’ perceived viability — when referring to chipmaker Nvidia’s announcement of a $100 billion investment in OpenAI at the end of September.
Meanwhile, hedge fund investor Michael Burry, who predicted the collapse of the US housing market bubble in 2008 and inspired the 2015 film The Big Short, this week announced he’s bet against Nvidia and Palantir shares, writing on X: “Sometimes, we see bubbles. Sometimes, there is something to do about it. Sometimes, the only winning move is not to play.”
What would a bubble mean for fashion?
With AI spend increasing and valuations soaring, these companies are under more pressure to show their returns on investment, while data showing AI-induced productivity gains is still limited. The core question for fashion is: will investments pay off?
Fashion’s experiments with — and investments in — AI are in their infancy, compared to those of adjacent industries like advertising, where major players like WPP and Publicis have upped their AI spending to several millions of dollars in 2025.
So far, only a handful of fashion companies are willing to talk about their investments in AI, but an early adopter in luxury is LVMH, which built out its own “AI Factory” of AI algorithms for use across its brands like Louis Vuitton, Dior and Tiffany Co. last year. In order to deploy AI at scale across the business, the group first went through the cumbersome process of consolidating all its client data from different records into one secure system. It’s been testing different use cases across the business to see whether using AI would actually bring a return on its investments in data and upskilling — something chief data and omnichannel officer Gonzague de Pirey recently noted requires significant ongoing financial commitment.
LVMH’s observations reinforce the importance of discipline when it comes to identifying where AI is actually worth the investment for fashion companies that are earlier in their AI journey — which is most of the industry.
Swarovski has invested in a complete data overhaul, migrating over 1,000 data objects involving enterprise information on multiple systems — including its CRM, ERP, e-commerce and creative assets — into one unified system, in order to set up a new generative AI portal using Google’s AI tools that employees could use across marketing and customer service functions.
Meanwhile, Moncler hired an AI creative agency and is now shooting thousands more photographs of all its products for e-commerce content at the same time as its brand campaigns, in order to produce navigable 3D product videos on its recently re-launched site. The brand tested how these new features impacted customer engagement with the site before launching, and found average engagement time increased 49% among mobile visitors, pages viewed per session rose by 22%, and the bounce rate decreased by 6% on mobile. It hopes this will translate into an increase in sales, on the assumption that customers will buy and keep more products after they’ve previewed them in lifelike detail.
“Calling this a bubble assumes the peak has already been reached, but in fashion, we haven’t even begun. Most brands are still working with fragmented data, legacy systems and pilot-level use cases,” says Matthew Drinkwater, head of the Fashion Innovation Agency at London College of Fashion.
“But the real breakthroughs like autonomous design agents, zero waste dynamic manufacturing, and digital wardrobes are still ahead of us — so the industry isn’t shielded per se, but the biggest opportunities are still unrealised,” he adds. This, Drinkwater notes, is very different from some sectors that are pouring billions into certain AI applications without clear use cases.
Fashion companies that dare to experiment with consumer-facing AI use cases — like AI-generated creative campaigns and chatbot styling tools — are less common than those that are using AI for behind-the-scenes applications. Much of this is down to the perceived brand reputational risk for using controversial AI alternatives to human creativity and interaction.
For internal functions, analysts say some brands are already reporting measurable returns by using AI tools to automate specific workflows across functions such as finance, supply chain and marketing. According to Raakhi Agrawal, partner at Boston Consulting Group, this return on investment so far has taken the form of time savings of up to 58% on employee time, 80% lower costs, and two to 10 times faster asset creation, according to the firm’s recent client research.
“The biggest challenge comes when companies try to do too much at once,” says Agrawal. “Those focusing on a few high-impact use cases and automating end-to-end workflows are the ones realizing real ROI.”
Although data on individual fashion companies’ returns on AI investments is still scarce, there are early signs that consumer behavior, at least, could be fast adapting to the recent commerce-focused AI product rollouts like ChatGPT and Google AI shopping. In a recent Adobe survey of 5,000 US consumers, over a third reported having used an AI-powered service for online shopping, with top use cases including research (53%), product recommendations (40%), finding deals (36%), and gift inspiration (30%). Holiday spending data could reveal the first meaningful data on whether 2025’s AI shopping developments are actually influencing consumer spending.
Experts working with fashion companies on branding and creative say that, unlike previous industry tech crazes like Web3, virtual reality and NFTs, interest in AI is much more universal and linked to everyday use cases that suggest it will stick around longer, both in consumers’ minds and branding strategies.
“No one’s really talking about the fleeting promises of the metaverse and NFTs anymore, but AI feels different,” says Shadeh Kavousian, creative director at creative agency Morning FYI. “It’s less a passing trend and more a fundamental shift, maybe closer in impact to gaming or television, mediums that didn’t just appear and disappear but reshaped culture. Not a fix for something that already exists, but instead something that changes the way we approach everything. That has the potential to last much longer.”
And if the bubble is about to burst, critics say this could be a good thing for the fashion industry.
“A crash will sort the wheat from the chaff, and if the bubble bursts, companies will have to evolve to survive. They will only do that if there is a market need for their product,” says Harkin.
