Traditional search, like Google Search as of December 2025, primarily matches keywords in a query to keywords on webpages, ranking results based on factors like link authority and content relevance. AI search, however, aims to *understand* the intent behind a query and provide a direct answer or synthesised overview, rather than just a list of links.

Currently, AI search features – prominently seen in Google’s Search Generative Experience (SGE), now widely available to Australian users – leverage Large Language Models (LLMs). These models analyse vast datasets to generate responses. For example, a query like “best accounting software for tradies in Melbourne” won’t just return links to software websites; it will generate a summary comparing options, potentially including pricing tiers (where publicly available) and key features. Platforms like Microsoft Bing Chat also utilise similar AI-powered summarisation. In 2026, we’re seeing increased integration of multimodal AI, meaning searches can incorporate images and voice, further refining understanding. Australian data privacy regulations are being factored into LLM training and response generation, ensuring compliance with the Privacy Act 1988. Google has announced that in 2027, AI Overviews will become even more personalised based on user search history and location data.

Essentially, traditional search *finds* information, while AI search *creates* an answer based on the information it has processed.