AI Builds a New Sourcing and Selling Reality for Fashion

Nearly half of consumers already shop with some kind of AI tool, and traffic arriving at Tapestry's sites through AI tools spends 48 percent longer dwelling there, according to Adobe research cited by Tapestry chief information and digital officer Yang Lu. For fashion brands and retailers, the message is direct: AI-driven discovery is already a measurable channel, and the cost of ignoring it repeats the e-commerce mistake of the 2000s.

Lu, whose company owns Coach, drew the parallel explicitly. "The people who missed the e-commerce boat didn't follow the customer," she said. "That's why we follow our customer." Product discovery has moved from stores to browsers to Instagram and TikTok, and AI is the next shift in that sequence.

How fast does a general-purpose technology pay off?

The McKinsey Global Institute framed AI as the fifth general-purpose technology since the 1770s, after steam, electricity, computers and the internet. The timeline data is sobering for anyone expecting quick returns. Steam took 100 years to reach its peak contribution of 30 percent of per capita GDP growth. Electricity needed 40 years to hit 10 percent of GDP. Computers and the internet together peaked at 50 percent of economic growth.

"General-purpose technologies can transform economies and improve lives, but realizing their full potential takes more than the invention itself. It requires complementary innovation, new infrastructure, new rules, capital and people and organizations willing to change how they work," McKinsey said in a report on the AI economy. It added that "the first uses of major new technologies are rarely the most consequential" — electricity began as a replacement for gas lighting before enabling entirely new economic activity.

What is the investment bill, and who pays?

McKinsey estimated global data center investment will total $7 trillion between 2025 and 2030, with more than 40 percent of it in the U.S. This year alone, U.S. imports of AI-related goods are on track to reach roughly $750 billion — in McKinsey's words, "about as much as its imports of cars, oil and gas, and pharmaceuticals combined."

Jonathan Low, a partner at Predictiv who specializes in the financial impact of intangibles, called the financial projections delusional. "Every human on Earth plus the residents of several other solar systems would all have to be buying AI at a premium to support these growth projections," he said. Implementation costs, he argued, will exceed expectations, returns will arrive slower than promised, and the market is in over-hype mode. His more immediate concern is not extinction-level risk but the possibility that the spending collapses "because nobody's really making money from this right now."

What changes at the brand level?

At Tapestry, Lu said the company refuses to do AI for AI's sake. The operational focus is agentic engine optimization — AEO — built on first-party content, third-party content, technology and measurement. Tapestry is investing in longer editorial content, such as detailed leather-care guides, because AI search rewards depth over short product descriptions.

On governance, Lu noted regulators have not caught up: "The government right now has not figured out really how to regulate AI. Governance is key. Governance is enablement." Her internal posture: "We're OK with failure because it's an important step for learning."

What about factories and jobs?

Marc Palatucci, who leads the fashion, apparel and luxury practice at Future Today Strategy Group, pointed to physical AI as the deeper shift for manufacturing. "Where the industrial revolution allowed productivity to scale, this physical AI revolution is going to allow intelligence to scale," he said. "The factory itself is going to learn as it produces, rather than having a human come in and say, 'Well, what if we tweak this one gear?'"

He called the AI trajectory irreversible — "we can adjust the course, but we cannot un-ring the bell" — and argued the existing economy will absorb the disruption because it relies on money changing hands. For now, fashion companies are closer to growing revenue with the same workforce than to replacing employees with robots.

Where does consumer trust land?

Katie Thomas of the Kearney Consumer Institute said automation freed about 40 minutes per person per day over the past decade and will free roughly 80 minutes over the next ten years, with much of that time going to streaming and scrolling. Kearney estimated that by 2036, $20 trillion in consumer spending will be contestable due to trust failures, as brand inertia stops protecting incumbents and trust shifts from the brand to verifiable product outcomes.

What did the Walmart patent dispute reveal?

Public policy group Groundwork Collaborative flagged Walmart patent applications covering in-store tracking via facial recognition, drones and Wi-Fi signals, plus biometric data such as heart rate and glucose levels to infer preferences, and a dynamic pricing patent enabling customer-by-customer price changes. Walmart executive vice president Dan Bartlett responded that a patent describes potential capability, not deployment, and CEO John Furner committed last month: "We don't set different prices based on who you are or the time of day, and we won't."

The confirmed fact beneath the dispute: retailers are patenting the capability even while disavowing its use, and brands deploying AI shopping agents such as Walmart's Sparky face rising scrutiny over how agent data affects pricing and assortment.

For sourcing and supply-chain executives, the near-term agenda is measurable: invest in AEO-ready content, budget for higher-than-expected implementation costs, and expect the physical-AI factory to arrive later than the hype suggests but earlier than the last technology wave did.