In recent years, the way people search for information online has shifted dramatically. Instead of relying solely on traditional search engines, more users are turning to large language models (LLMs) such as ChatGPT, Gemini, Claude, and Perplexity. Unlike traditional search, which delivers a list of ranked links, LLMs provide direct, conversational answers that feel more natural and personalised. This makes them especially appealing for users who want clarity, context, and quick solutions without having to sift through multiple websites.
Businesses are beginning to adapt to this change, recognising that visibility in search is no longer just about Google rankings. With AI-powered assistants becoming a first stop for information, product research, and decision-making, brands need to ensure their content is structured and optimised for LLM discovery. Structured data, schema markup, and entity-driven strategies are becoming critical tools to help companies appear in AI-generated answers. As adoption grows, optimising for LLMs is quickly moving from an experimental advantage to a core part of any AI digital marketing strategy.