Macy’s has moved beyond flashy virtual try-ons to embed artificial intelligence directly into its engineering workflows and supply chains. Senior director of engineering Murali Murugan describes this as an “AI-first” approach designed to redesign decision-making processes so the business moves faster and every experience feels more relevant by default.
In this article
Compressing the gap between signal and action
The strategy shifts away from layering tools onto existing workflows. Instead, intelligence is built directly into systems for personalization, search, operational planning, and software development. This reflects a wider trend across retail: moving from isolated pilots toward integrated systems. The goal is to compress the gap between the signal and the action.
Early efforts focused on narrow use cases like search recommendations and customer engagement. Measurable gains in conversion and reduced friction quickly built internal momentum. Once the quick wins were established, scaling became a business decision rather than a technology debate.
“Once we established the quick wins, scaling was a business decision, not a technology debate anymore,” Murugan says.
Conversational commerce
Momentum is now extending into conversational commerce through Ask Macy’s. This AI-powered shopping assistant acts more like a personal stylist than a traditional search bar. Customers can describe needs conversationally for occasions like a prom, a vacation, or a last-minute event. The system returns curated recommendations informed by past purchases, preferences, and context.
The company views AI as an invisible layer augmenting human judgment rather than replacing it. The long-term vision is retail that feels adaptive and personalized, powered by systems customers may never even notice are there.
Continuous improvement
“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.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.




