AI slashes inventory waste in fashion e-commerce

Smarter forecasting and personalisation sharpen retailers’ edge.

Artificial intelligence is delivering gains across both fashion e-commerce’s back-end operations and customer-facing experiences.

On the supply side, AI is helping fashion retailers overcome one of their most persistent challenges: inventory inefficiencies caused by poor demand forecasting and the bullwhip effect—where minor shifts in consumer demand ripple through the supply chain, causing major disruptions.

“Advanced forecasting methods can improve demand prediction, reduce inventory issues and mitigate the bullwhip effect,” said Allison Chong, Regional Head of Apparel at ZALORA.

“Conversational AI assistant virtual stylists provide personalised recommendation, styling advice and product searches, enriching customer experience and ultimately driving conversion,” she added.

Chong noted that AI’s impact spans multiple stages of the value chain—from supply and demand forecasting to inventory and pricing strategy, as well as marketing and sales.

To stay competitive in an AI-driven fashion market, Chong said retailers are adopting several strategies, including dynamic pricing, visual search, augmented reality, sustainability initiatives, and omni-channel integration. But personalisation stands out as a core focus.

ZALORA is prioritizing four key areas in personalisation: customer insights, product recommendations, customized marketing, and user experience.

“Customised marketing campaigns are crafted based on customer segments, ensuring that messages resonate with the target audience,” Chong explained. “[AI] makes the shopping experience more engaging, intuitive, and most importantly, relevant to the customer itself,” she said.