Practical insights from the front lines of AI-driven marketing. No fluff.
Research tracking nearly 1,900 pages found that adding schema markup produced almost no meaningful movement in AI citation rates. The gap between cited and non-cited pages tells a more complicated story than the structured data evangelists would have you believe.
There is a striking parallel between how humans and AI models extract meaning from text - and it has direct implications for how brands structure content to earn citations. Getting your writing right at the page level is increasingly where AI visibility is won or lost.
Google is rolling out Smart Bidding Exploration to Performance Max with product feeds and Shopping campaigns, alongside budget pacing for Search and Shopping. The question for advertisers is not whether these tools work - it is what you give up when you let them run.
Google AI Overviews is now surfacing author names alongside source platforms like LinkedIn and Medium in its citations. This shift changes who gets credited in AI search - and how brands should think about the people behind their content.
Microsoft has confirmed Bing now has 1 billion monthly active human users - a milestone that reframes the platform as a serious channel for AI search visibility. For UK brands focused on GEO, ignoring Bing's AI ecosystem is no longer a defensible position.
Giving AI agents access to your data is only half the problem - defining what they are actually authorised to do with it is the part most marketing teams have not figured out yet. As agentic systems move from passive analysis to active execution, the question of decision authority is becoming a practical operational concern, not a theoretical one.
Google appears to be testing more links and citations within AI Mode results, following a similar move made with AI Overviews roughly a year ago. For brands investing in AI visibility, this signals a real shift in how citation real estate is distributed across generative search.