LLMs for Retail Customer Service

About LLMs for Retail Customer Service

Large language models are revolutionising how retailers interact with customers at every touchpoint. The shift from rule-based chatbots to generative AI assistants represents the biggest transformation in retail customer service since the call centre moved online - and the implications extend far beyond cost reduction.

In 2026, leading retailers are deploying LLM-powered systems that can handle complex queries about product specifications, process returns conversationally, provide styling advice based on purchase history, and escalate to human agents seamlessly when the conversation requires empathy or judgement. The technology has moved beyond simple FAQ automation into genuine virtual selling, where AI assistants proactively recommend products, handle objections, and close sales across chat, voice, and messaging platforms.

This pillar covers the deployment of LLM-powered chatbots, virtual shopping assistants, product recommendation engines, and automated support systems across retail. We examine vendor platforms from Salesforce, Google, and specialised retail AI companies alongside retailer case studies that reveal real-world performance metrics. We also address the critical challenges: hallucination risks that can erode customer trust, the cost economics of running large models at scale, data privacy considerations, and the organisational change management required to integrate AI into existing service operations. From conversational commerce to AI-powered clienteling, this hub tracks how generative AI is blurring the line between customer service and personalised selling.