AI shopping assistants and conversational commerce platforms combine natural-language interfaces, commerce plugins, and backend orchestration to let customers discover, compare, buy and get support inside chat and commerce touchpoints. As of 2026, major trajectories include chat-native checkout integrations (e.g., Klarna in ChatGPT), cloud-delivered retail assistants (AWS Retail AI Assistant), and a growing ecosystem of specialized plugins that surface catalogs, availability and payments inside conversations. This topic spans several tool categories: AI shopping assistants and browser extensions that surface product-specific insights (ShopGuru analyzes Amazon reviews on-page); customer service chatbots and accessible live chat (Olark) that augment agents with AI; CX automation and marketing platforms (HubSpot’s Breeze, Brevo, Smarketly) that embed context-aware assistants across CRM and messaging channels; and vertical visual-commerce tools (Veesual, YesPlz) that drive discovery with on-model imagery and fashion-trained vision models. Supporting infrastructure and optimization tools (LandLyze for landing-page conversion, Xilos for agentic orchestration) address integration, routing and reliability. Relevance and timeliness: retailers are prioritizing conversational checkout, personalization, and seamless support as consumers expect instant, contextual experiences across web, social and chat platforms. Practical considerations include data privacy, catalog/inventory synchronization, fallback to human agents, and guardrails against AI errors. Evaluations should consider integration surface (plugins/APIs), domain specialization (fashion vs. general retail), accessibility, and how assistants connect to payments, fulfillment and CRM. Together these tools form the operational layers for conversational commerce — enabling discoverability, conversion and post‑purchase care while raising new integration and governance tradeoffs for retail teams.