Freshness describes how current a piece of content is and how recognisable that currency is to search engines and AI systems. The two belong together: an updated text without a visible date looks old, and a new date above an old text does not help. AI systems cite older content significantly less often; a page marked “as of 2023” loses to a page with current figures.
How does freshness work?
For questions that demand currency, AI systems fall back on web search because their model knowledge ends at the knowledge cut-off. When selecting sources, they prefer content whose currency is substantiated — through the date in the text, through datePublished and dateModified in the schema, through the lastmod in the sitemap and through the years of the statistics cited. Studies by aiboost.co.uk and Ryan Shojae on update frequency for AI search show that regularly maintained content is cited more often.
Why does freshness matter for AI visibility?
Because an AI answer is only as current as its sources — and the systems know this. Of two passages with comparable relevance, the more recent one wins. For questions about prices, dates, versions and market data, an outdated figure is even a reason to discard a source. Freshness also affects indexing: a sitemap in which all pages report the same date gives Google no reason to read them again.
What does this mean for your website?
Update existing content regularly, keep statistics and years current, and make that currency technically visible: publication and modification date on the page, in the schema and in the sitemap — derived from the actual change, not hard-coded. Prioritise the pages that answer the most important questions in your prompt set.