Merchandisers turn to trendspotting as AI runs numbers

Humans now set rules and guide AI to protect brand value and pricing.

Retailers are changing the role of merchandisers as artificial intelligence (AI) increasingly handles tasks such as inventory forecasting, product assortment, and stock management.

Juan Pisente Widjaja, a senior partner at Gideon Consulting Group, described the shift as “curatorial strategy,” with humans focusing on trend spotting and brand storytelling whilst AI manages the data analysis.

“The role becomes less about managing spreadsheets and more about managing the AI’s parameters to ensure the product mix aligns with the brand’s long-term vision rather than just short-term volume,” he told Retail Asia.

Almost half of retail and consumer goods companies are already using or evaluating agentic AI, with 21% planning to adopt it within a year, according to Nvidia Corp.

Retailers are applying AI to digital shopping assistants, product catalogue management, and warehouse and supply-chain operations.

A January report by McKinsey & Co. noted that agentic AI could plan, act, and learn independently. Merchants can adjust prices, optimise promotions, and rebalance product ranges almost in real time, replacing slower weekly or monthly review cycles.

Despite growing adoption, challenges remain. The report found 71% of merchants said AI merchandising tools had little impact so far, whilst 61% said their organisations were only slightly prepared or unprepared to scale AI across merchandising functions.

Andrea Carnino, procurement senior manager at Ricegrowers Ltd. (SunRice), said humans should focus on judgement, storytelling, supplier collaboration, and in-store impact.

“Use agentic AI for what it does best—crunch data, spot patterns, test sources, save time, repeat—so people can focus on judgement, storytelling, supplier collaboration, and in‑store/customer impact,” he said in a separate comment.

Analysts cited the need for safeguards in AI-driven pricing. Widjaja recommended strategic guardrails, such as minimum price limits, to prevent a “race to the bottom” that could damage brand reputation.

Autonomous systems should also be audited to avoid favouring low-value, price-sensitive shoppers over loyal, high-margin customers, he added.

“Transparency in how dynamic pricing is applied is essential,” he said. “If a consumer feels exploited by an algorithm, brand trust is lost instantly.”

Carnino said price changes should benefit consumers and avoid constant micro-fluctuations that could confuse shoppers. He cited IKEA’s “new lower price” initiative as a model of justified and stable pricing.

Sharon Iles, a senior apparel analyst at GlobalData Plc, said human merchandisers now act as the ethical and strategic layer guiding AI.

Retailers should set clear brand rules and maintain regular review cycles, with alerts for unusual AI behaviour, to ensure recommendations are audited rather than executed blindly.

"Retailers who thrive will treat AI as a powerful but bounded tool, with empowered human merchandisers serving as the ethical and strategic layer that keeps pricing decisions aligned with long-term brand equity and customer loyalty,” she said in an emailed reply to questions.