Key Takeaways:
- Retailers treating AI as a core system, not an add-on, are seeing measurable gains in conversion, revenue per visit and operational efficiency.
- AI-powered search reads shopper intent using session behavior, device type and order history; Macy’s AI assistant drove 4.75 times higher revenue per visit in beta.
- In-store AI tools, including associate coaching, digital twins and demand forecasting, are cutting stock-outs, reducing markdowns and improving floor efficiency.
- Start with three high-ROI use cases: intent-aware search, next-best-action prompts for associates and demand forecasting on high-velocity SKUs.
AI Is Reshaping the Retail Sales Journey
Big retailers are moving past pilots and putting AI to work across search, recommendations and sales tools. Early movers that integrate AI into core workflows, not as a bolt-on, are seeing the clearest gains.
Search now reads intent, not just keywords. Sites factor in device type, session behavior and order history to surface relevant items faster. Macy’s rolled out Ask Macy’s, an interactive assistant that helps shoppers refine budget, occasion, color, style and size. During beta, revenue per visit was 4.75 times higher for users of the tool than for non-users, according to Retail Dive.
Personalization has matured from generic “customers also bought” modules to moment-specific suggestions that reflect behavior, purchase history and context. The implementation lesson: start with clean data governance and clear relevance metrics, then build feedback loops that learn from clicks, dwell time and returns.
How Is AI Changing the Way Sales Teams and Store Operations Work?
AI is making sales teams more consistent and stores more efficient. Tools that coach in the flow of work, suggest next-best actions and route content through CRM platforms help reps stay confident. Field results show meaningful conversion lifts, and at retail scale, even small gains drive material revenue.
In stores, an ICSC and McKinsey report found that 68% of consumers used at least one AI-enabled shopping tool in the past three months. Western wear retailer Tecovas uses an AI-supported Boot Runner program so associates can request specific styles to the floor in about 85 seconds, keeping the associate with the shopper. Retailers can also use digital twins to test layouts and traffic flows before making physical changes, as Lowe’s has shown with 3D simulations.
Forecasting and pricing have also improved. Demand models that include historical sales, seasonality and external signals reduce stock-outs and excess inventory. Dynamic pricing layers can respond to local demand and competitive moves in near real time. Focus first on high-velocity SKUs and categories with volatile demand since the biggest financial wins come from getting fast movers right.
Where Should Retailers Start With AI?
Begin with three high-ROI use cases. First, intent-aware search that improves relevance and reduces bounce on category and long-tail queries. Second, next-best-action prompts for associates that guide objection handling in real time. Third, demand forecasting on top sellers to cut stock-outs and markdowns. Stand up lightweight pilots, align on success criteria and expand only when the data supports it.
Omnichannel execution matters too. Shoppers expect to find an item online, confirm stock and get aisle-level help without having to repeat themselves. Prioritize low-friction UX, clear handoffs between digital and human touchpoints, and visible fallbacks when confidence is low.
Trust and transparency are also non-negotiable. Shoppers accept smarter suggestions when you explain why they’re seeing an item and offer easy ways to adjust their preferences or opt out. Keep model governance tight: define data access rules, retention periods and off-ramps when performance drifts. Measure what matters, including search-to-product-view rates, prompt adoption, forecast error by SKU and markdown rate, then tie wins to financial impact so you know where to scale.
(Note: AI assisted in summarizing the key points for this story.)