Macy's Embeds AI Into Core Operations Rather Than Layering It Atop Legacy Systems

Macy’s Embeds AI Into Core Operations Rather Than Layering It Atop Legacy Systems

Retail’s AI transformation is happening in the back office, not the storefront. According to MIT Technology Review AI, Macy’s has adopted what Senior Director of Engineering Murali Murugan calls an “AI-first” operating philosophy—one that redesigns how the business makes decisions across search, inventory management, personalization, and software development, rather than simply grafting AI onto existing workflows. This represents a strategic shift from isolated pilot programs to integrated systems designed to compress what Murugan describes as “the gap between the signal and the action.”

How Macy’s Built Momentum for AI Adoption

The path to enterprise-wide integration began with surgical precision. Macy’s initially focused on narrow, high-impact use cases—search recommendations and customer engagement—where quantifiable wins in conversion rates and friction reduction created proof points that transformed scaling into a business imperative. According to Murugan, “Once we established the quick wins, scaling was a business decision, not a technology debate anymore.” This bottom-up approach prevented the common pitfall of AI rollouts: enterprise resistance grounded in theoretical concerns rather than demonstrated value.

Conversational Commerce as the Visible Layer

The public-facing manifestation of Macy’s AI infrastructure is Ask Macy’s, a conversational shopping assistant that repositions search as a dialogue. Instead of keyword-based querying, customers describe contextual needs—styling for a prom, vacation, or last-minute event—and receive recommendations informed by purchase history and stated preferences. The tool functions as a digital personal stylist rather than a traditional search bar, collapsing the step between intent and curation.

The Philosophy of Invisible Augmentation

Macy’s explicitly rejects AI-as-replacement framing. The company views intelligence systems as augmenting human judgment, with the aspiration that optimal experiences feel seamless because the decision infrastructure remains imperceptible to the end user. According to Murugan, continuous improvement—learning from failures, adapting to emerging technology standards, and compounding execution gains—drives the long-term vision of retail that feels increasingly personalized without customers recognizing the systems beneath it.

Why This Matters

The Macy’s case study illustrates how mature retailers are competing in an AI-saturated market: not through flashy consumer-facing features, but through operational redesign that accelerates decision-making velocity across the organization. Retail teams evaluating their own AI roadmaps will likely find the “AI-first” framing—redesigning workflows rather than layering algorithms—more durable than point-solution pilots. As legacy retailers face margin pressure from born-digital competitors, this philosophy of embedding intelligence into core operations rather than bolting it on top may determine which incumbents retain relevance. The continued invisibility of these systems also reduces customer friction; conversational tools like Ask Macy’s work because they sit atop trusted, optimized infrastructure, not because they are inherently novel.