Google tunes AI Overviews based on engagement and directs follow-up questions to AI Mode
Google is increasingly optimising AI Overviews around observed user behaviour: if people don’t click or engage, Google may remove AI Overviews for those query types and apply that learning across similar searches. At the same time, Google is tightening the loop between AI Overviews and ongoing exploration by sending follow-up questions directly into AI Mode (notably on mobile), encouraging longer, more conversational sessions inside Google’s AI interface rather than back-and-forth between web results and publisher pages. Together, these shifts point to a more dynamic SERP where AI elements expand when they ‘work’ (engagement signals) and recede when they don’t, while successful AI journeys increasingly keep users within Google’s AI experience for subsequent queries.
Why we care: This raises the stakes on content that demonstrably satisfies intent and earns engagement signals that can influence whether AI Overviews appear for your target query sets. It also increases the likelihood that users’ follow-up intent is fulfilled inside AI Mode, potentially reducing repeat clicks back to the web and compressing the discovery journey into fewer external visits. That makes winning initial visibility and designing pages that capture value fast, give clear answers, and compelling next steps more important as follow-up behaviour shifts away from classic SERP clicking patterns.
Apple’s Siri and Google Gemini partnership signals a major AI shift
Apple has entered a multi-year partnership with Google to enhance its AI capabilities, notably upgrading Siri by integrating Google’s Gemini AI models and cloud infrastructure. This collaboration aims to bolster Apple’s AI features, with the revamped Siri expected to launch later this year. Apple selected Google’s Gemini after a thorough evaluation, citing it as the most capable foundation for its AI ambitions, following earlier reports of Apple considering a custom Gemini model and delays to Siri’s AI enhancements.
Why we care: If Siri becomes meaningfully more capable through Gemini, iOS could drive more assistant-led discovery, where answers are synthesised, and fewer clicks reach traditional web listings. Expect greater volatility in referral patterns from Apple surfaces, prioritise content clarity and entity relevance so assistants can confidently summarise and attribute information, and strengthen brand signals that make a site an obvious ‘best source’ when assistants choose what to cite or recommend.
Personalised AI answers meet in-chat commerce: Google AI Mode and Microsoft Copilot push search towards assistant-led journeys
Google is adding “Personal Intelligence” to AI Mode, letting opted-in users connect Gmail and Google Photos so responses can be tailored to personal context, and it’s rolling out to AI Pro and Ultra subscribers in the US. In parallel, Microsoft is expanding Copilot into the transaction and support layer of shopping: Copilot Checkout enables purchases directly within Copilot chat across Bing/MSN/Edge, and Brand Agents let merchants (notably Shopify sellers) deploy AI assistants trained on their product catalogue to answer questions and guide users from discovery to purchase; Microsoft is also tying agent interactions into analytics via Clarity.
Why we care: Organic search visibility is increasingly mediated by assistants that personalise answers and compress the path to conversion. Personal context (Google) can narrow what sources and brands surface, while embedded checkout and brand agents (Microsoft) can reduce downstream site visits even when a brand is chosen.
Yahoo launches Yahoo Scout for AI search and web discovery
Yahoo has launched Yahoo Scout, an AI-powered search and companion experience integrated across Yahoo’s platforms, including News, Finance, Mail, and Search, and is currently in beta for US users. Scout presents suggested searches across topics and pulls in richer, integrated elements such as finance widgets, detailed financial data, weather updates, and news content directly into responses. Yahoo also highlights sources within responses to encourage visits to original content, positioning Scout as both an answer engine and a web discovery tool rather than a closed experience.
Why we care: A resurgent Yahoo discovery layer creates another AI-mediated surface where visibility may depend on how well content fits the entity/vertical needs (finance, news, shopping, travel) and how easily it can be quoted with clear attribution. Yahoo’s vertical integrations should be treated as an opportunity to win qualified traffic where users are already in research mode.
Google’s December 2025 core update: more brands win ‘best of’ queries
Google’s December 2025 core update ran from December 11 to December 29 and drove notable ranking shifts, particularly in ‘best of’ and mid-funnel product queries, where specialist brands often gained visibility over generalist publications and broad retailers. Examples cited include generalist publishers dropping on certain game-related ‘best’ queries while brand/platform pages improved. The reported pattern suggests Google is leaning harder into topical fit and perceived expertise for recommendation-style searches, increasing volatility for broad, list-style content that does not strongly signal authority in the niche.
Why we care: If ‘best of’ SERPs increasingly favour specialists, brands should treat this as an opportunity: strong category pages and product-led content can outrank generalist roundups when they better match intent. The strategic takeaway is to align content format and depth with commercial research intent, rather than relying on broad, catch-all recommendations.
