Ai’s quiet takeover: how fashion buyers are trading instinct for data
The scent of a desirable garment – that’s what buyers have always relied on, a sixth sense predicting trends before they materialize. Now, a seismic shift is underway as artificial intelligence begins to reshape the industry, moving beyond simple sales forecasts to fundamentally alter how assortments are built, refined, and scaled.
Data-driven decisions: a new era for retail
Fashion buyers are increasingly turning to AI-powered tools to dissect massive datasets – encompassing search behavior, click patterns, regional preferences, and product performance across global markets. This isn’t about replacing human judgment, but augmenting it, offering a sharper, more immediate view of consumer demand than ever before. It’s a subtle, yet profound, evolution.
“AI is more of a tool that extends their reach,” explains Rich Shepherd, VP of product at Lyst. “The best buyers still lead with instinct – AI just gives them a clearer view of where that instinct might resonate most strongly.”
Tapestry, the parent company of Coach, Kate Spade, and Stuart Weitzman, has invested heavily in a centralized ‘proprietary data fabric’ – a sophisticated system allowing real-time data sharing and analysis. Fabio Luzzi, their Chief Data and Analytics Officer, emphasizes the strategic imperative: “We always understood that to digitalize this process and scale fast, we had to build a capability to host and share data easily across the business.” This allows them to react with unprecedented speed to emerging shifts in consumer interest.
But the transformation isn’t limited to large corporations. Lyst, the Fashion aggregator, is leveraging AI to move beyond simple catalog rankings, offering personalized style recommendations based on individual taste and purchase history. The McQueen skull scarf’s recent resurgence, fueled by celebrity sightings, exemplifies this shift – a trend identified far earlier than historical sales data would have indicated.
Miyon Im, VP of product design and editorial at Lyst, notes, “Before, merchandising was just about what the first six products you’d see in a feed were. But with AI, we can get more sophisticated – around styling, outfitting, or even event-based suggestions.” This translates to data briefs delivered regularly, highlighting surprising spikes in searches or saves, prompting a deeper investigation into their underlying cultural context.
Experts caution that AI’s efficacy hinges on the quality of the data it receives. Historical biases – concerning sizing, representation, and geographic preferences – can be inadvertently amplified. Julie Gilhart, a former buying executive at Barneys New York, asserts, “The brands that get it right will let creativity lead, with AI enhancing the vision rather than replacing human touch.”
The challenge, then, lies in balancing the analytical power of AI with the nuanced understanding of human taste and intuition. Ultimately, the future of Fashion retail won’t be dictated by algorithms alone, but by a strategic partnership between data-driven insights and the enduring wisdom of experienced buyers.