Retail AI is being used to improve personalisation and customer insight

Retail companies are expanding their use of AI to deliver more personalised shopping experiences and faster customer insight. The article says static layouts and broad segmentation are being replaced by systems that can adjust content, copy, and interface elements during a live session based on clickstream, purchase history, and inferred intent. It also describes how retailers are using multimodal analytics to monitor video, audio, and unstructured imagery in addition to text, helping teams spot product usage, brand mentions, and sentiment across digital channels. These tools are presented as a way to improve inventory planning and marketing response times. The piece further covers synthetic user simulations for testing ads, pricing, and user experience changes, as well as edge computing and computer vision for physical retail tasks such as shelf tracking and checkout automation. It ends by discussing Model Context Protocol, which aims to standardise how AI systems connect with retail databases and other business tools.