AI retail shopping assistants and voice‑powered commerce describe a class of conversational and agentic technologies that guide discovery, complete transactions, and handle post‑purchase support across voice, chat and visual interfaces. As of 2026, retailers and platform providers (AWS/Alexa, Google Shopping AI, Shopify’s AI tooling) are standardizing APIs and models that let merchants embed conversational shopping, voice calling agents and multimodal product experiences into storefronts and contact centers. Key capabilities include contextual recommendations and hyper‑personalization (eBay AI Shopping Agent), real‑time order lookups tied to merchant data (HelloAI for Shopify), autonomous voice interactions for inbound/outbound customer calls (Llamalo), and richer try‑on/visual commerce features that reduce returns and speed decision‑making (LookBook AI, Veesual). These solutions sit across two practical categories: AI Shopping Assistants for product discovery and conversion, and Customer Service Chatbots for tracking, returns and voice support. The topic is timely because advances in large multimodal models, improved speech agents, and tighter integrations with e‑commerce platforms have moved conversational shopping from experimental pilots into production use. Retailers weigh clear benefits—higher conversion, lower support costs and better fit prediction—against implementation considerations such as data privacy, model governance, latency and measurement of customer experience. Successful deployments combine backend integration (inventory, orders, personalization) with UX affordances like avatar try‑ons or voice fallbacks. Understanding the tradeoffs—accuracy, privacy, integration effort and channel fragmentation—is essential for merchants evaluating Alexa/Google/Shopify offerings and specialized tools like HelloAI, Llamalo, LookBook AI, Veesual and eBay’s agent. The space continues to evolve toward unified, multimodal shopping assistants that span discovery, purchase and service.