Retail’s New Blueprint for the AI Era
▼ Summary
– AI is reshaping retail primarily through backend operations like search, supply chain, and code deployment, not through flashy consumer-facing features.
– Macy’s employs an “AI-first” approach that embeds intelligence directly into systems for personalization, search, and planning, rather than layering AI onto existing workflows.
– The company scaled AI after initial successes in search recommendations and customer engagement, making further adoption a business decision rather than a technology debate.
– Ask Macy’s is a conversational AI shopping assistant that provides curated recommendations based on customer descriptions, past purchases, and context.
– Macy’s views AI as an invisible layer that augments human judgment, aiming for seamless, adaptive, and personalized retail experiences through continuous improvement.
Artificial intelligence is quietly rewriting the rules of retail, but not through the flashy consumer-facing gimmicks many might expect. The real revolution is happening behind the scenes: how products rank in search results, how inventory flows through supply chains, how engineers accelerate code deployment, and how retailers adapt to customer behavior in real time. As legacy retailers fight for relevance in a fragmented, hyper-competitive market, AI is evolving from a tool into an operating philosophy.
At Macy’s, this philosophy is anchored in what senior director of engineering Murali Murugan calls an “AI-first” approach. “AI first isn’t about adding intelligence on top,” Murugan explains. “It’s about redesigning how decisions happen so the business moves faster and every experience feels more relevant by default.” Instead of grafting AI onto existing processes, Macy’s is embedding intelligence directly into core systems: personalization, search, operational planning, and even software development itself.
This strategy mirrors a broader industry shift: moving from isolated AI experiments toward integrated systems that shrink what Murugan calls “the gap between the signal and the action.” Early wins came from targeted use cases like search recommendations and customer engagement, where measurable boosts in conversion and reduced friction built internal buy-in. “Once we established the quick wins, scaling was a business decision, not a technology debate anymore,” he says.
That momentum now fuels conversational commerce through tools like Ask Macy’s, an AI-powered shopping assistant designed to function more like a personal stylist than a conventional search bar. Whether a customer needs an outfit for prom, a vacation, or a last-minute event, they can describe their needs conversationally and receive curated recommendations informed by past purchases, preferences, and context.
Still, Macy’s views AI as an invisible layer that amplifies human judgment rather than replacing it. The long-term vision is retail that feels increasingly seamless, adaptive, and personalized, powered by systems customers may never even notice are there.
“The real transformation in this all comes from continuous improvement,” Murugan says. “It’s about learning from the mistakes, quickly adapting to the newer technology standards that are coming into play, timing, and execution which compound into a meaningfully better customer experience.”
This webcast is produced in partnership with Infosys.
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(Source: MIT Technology Review)
