Target has appointed Chandhu Nair as its first chief artificial intelligence officer, a move that places AI strategy directly in the C-suite as the retailer pushes the technology across shopping, inventory, and internal operations. Nair will oversee a centralized effort to deploy AI everywhere from customer experiences and employee tools to inventory tracking and corporate forecasting.
The appointment comes as major retailers expand far beyond customer service chatbots, using AI to tackle supply chain management, product design, and backend logistics. Target's AI push includes Trend Brain, a generative AI platform that analyzes emerging styles, colors, and materials to speed up product development. The chain has also launched conversational shopping and gift-selection tools and integrated its catalog into external AI platforms.
For product development teams, the shift in mass-market retail is notably visible in how major chains are adopting the same kinds of tools that were once limited to tech platforms.
Retail's AI buildout reaches deep into the product cycle
Target's new strategy maps adoption across shopping, inventory management, and internal decision-making under Nair's leadership. The retailer has already put its catalog to work in third-party AI platforms, expanding the reach of its products beyond its own storefronts.
Walmart has built retail-specific AI agents for product comparisons, personalized recommendations, customer support, supply-chain management, and inventory analysis. Its consumer-facing assistant walks shoppers from discovery to purchase while internal tools help store associates manage stock. Walmart has also teamed up with OpenAI and Google to offer shopping through ChatGPT and Gemini.
Gap is using Google Cloud's Gemini and Vertex AI to power product design, planning, pricing, and marketing - including furniture for its product lines. Amazon introduced Alexa for Shopping in May 2025, combining its Rufus shopping assistant with a new system that compares products and monitors price. Amazon said Rufus helped more than 300 million customers research, compare, and buy products in 2025.
European retailers are integrating AI deeper into grocery and home shopping as well. Carrefour became the first big European grocer to allow customers to build shopping baskets through ChatGPT, and IKEA now recommends furniture based on room dimensions, budget, and sustainability preferences.
What counts as "AI" in a product development context
These implementations share a common theme: they treat AI as a layer that sits between product developers and product and delivery. Carrefour's ChatGPT integration, built on its Hopla assistant, lets customers filter products by dietary needs and check availability before payment. IKEA uses AI drones alongside its request-suggestion engine-and acquired logistics software company Locus in 2025 to optimize delivery scheduling.
Alibaba has embedded AI shopping assistants into its Taobao and Tmall platforms, and during the 2025 Singles' Day campaign, an AI customer-service assistant handled 300 million queries. The company said AI-assisted support helped merchants increase conversion rates by 30% year-on-year.
If you build or oversee AI-powered product features, the practical takeaway is not about a new company or assistant feature. What matters is the infrastructure under the surface. The tools flowing through these retailers are not general-purpose AI chatbots-they are purpose-built AI agents that handle product selection, price monitoring, logistics, and conversion. A lot of the work that is one idea per paragraph in internal decision-making is becoming the product development model at scale, so product teams with to expect assistant-style AI interfaces in every category from grocery to furniture-and place their future build work on the interfaces and the models that connect a product to the cash register.
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