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Nestlé, L'Oréal, ASOS show AI success hinges on people, not tech | AI Best Practices for Commerce | AI Best Practices for Commerce
  1. News
  2. › Bridging AI Adoption Gap in Retail Implementation
  3. › Jul 1, 2026
Bridging AI Adoption Gap in Retail ImplementationWednesday, July 1, 2026
  • Retail / DTC › Department Stores
  • Retail / DTC › Grocery and Convenience Retailers › Supermarkets and Other Grocery Retailers (except Convenience Retailers)
LLMASOSAmazonL'OréalNestléWalmartSparky · walmart

Nestlé, L'Oréal, ASOS show AI success hinges on people, not tech

Nestlé deployed over 100,000 daily Copilot users, L'Oréal shifted from organic experimentation to systematic AI adoption, and ASOS replaced disconnected agents with hybrid teams designed around human-AI collaboration. For commerce leaders, the lesson is clear: technology readiness outpaces organizational readiness, and managing change management and ways of working is more critical than the AI itself.

AI-generated. Summaries are AI-generated from cited sources. Click through for the original report.

At ShopTalk Europe, executives from Nestlé, L'Oréal, and ASOS revealed that successful AI adoption in retail depends far more on organizational design and change management than on technology maturity. Nestlé has deployed more than 100,000 colleagues using Copilot daily through an internal tool called NesGPT (RetailNews.ai), and has seen AI-generated product content outperform human-created alternatives while cutting content production time from months to days. Nestlé's virtual sales assistant reduces administrative work by 30 to 40%, freeing teams to focus on customer engagement (RetailNews.ai). L'Oréal evolved from organic, function-led experimentation to a more structured model where AI engagement is mandatory across the organization, learning that bottom-up exploration revealed genuine use cases before scaling (RetailNews.ai). ASOS abandoned its initial approach of building disconnected AI agents scattered across the organization and instead redesigned entire teams and workflows—including a new contact centre and merchandising function—to embed AI agents directly into business processes alongside humans (RetailNews.ai).

The critical insight across all three companies is that resistance to AI rarely stems from the technology itself, but from organizational anxiety about role survival and value. L'Oréal's Beauty Genius tool, trained on over 150,000 dermatologist annotations, succeeded not because of algorithmic superiority but because internal teams restructured how they work once they could see real-time feedback loops (RetailNews.ai). ASOS has trained close to 1,000 citizen developers—non-engineering employees—to build agents, proving that the right environment and incentives turn AI from a threat into an augmentation tool (RetailNews.ai). For commerce practitioners, the takeaway is that change management, organizational design, and ways of working must precede technology implementation; without these foundations, even effective AI initiatives remain isolated improvements that fail to drive enterprise-wide value.

The competitive stakes are rising sharply. Digital-native retailers like Amazon and Alibaba have inherent advantages in AI adoption, while traditional retailers like Walmart are building comprehensive digital ecosystems spanning stores, financial services, and agentic commerce capabilities (RetailNews.ai). As agentic commerce becomes standard—where AI agents increasingly make purchasing decisions on behalf of consumers—the gap between leaders and laggards is widening faster than expected (RetailNews.ai). Organizations already prepared for transformation will extend their advantage; those without strong foundations face mounting competitive risk.

Sources:1 report
  • RetailNews.ai
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