Our SEO expert, Andrea Winterhoff, shares the latest news and updates across SEO:
Google rolls out Gemini 3 Flash in AI Mode in Search globally
Google is positioning the Gemini 3 Flash as an upgrade that improves speed and reasoning for AI-generated responses. The update aims to support AI Mode’s growing focus on handling more complex intents such as comparisons and planning workflows. Additionally, users in the U.S. have the option to select “Thinking with 3 Pro” for more in-depth assistance, and an image generation/editing feature available within AI Mode through a Pro-powered image tool.
Why we care: A global default-model upgrade in AI Mode can change how often AI results appear, how they’re composed, and which sources get surfaced, affecting click-through and content visibility. This is why it’s important to continue to evaluate how content is represented in AI summaries, and tighten information architecture so key facts, comparisons, and step-by-step guidance are easy for AI systems to extract and present.
Google Search adds “read more” links to search result snippets
Google is adding “read more” links at the end of some search snippets. When clicked, the link takes users to a specific section of the destination page (anchored to where the snippet text is sourced), rather than just loading the top of the page. The feature was tested earlier in 2025 and now appears to be rolling out more broadly, though it is not present on every result.
Why we care: This changes how users land on pages and can shift engagement patterns, because visitors may bypass introductions and jump straight into the excerpted section. To benefit, ensure key sections are well-structured with clear headings, scannable formatting, and strong context around commonly extracted passages, so the “landing section” stands on its own and guides users toward next steps.
Google December 2025 core update rollout is now complete
Google’s December 2025 core update began December 11 and completed on December 29. Google positioned it as a broad core update intended to improve relevance and user satisfaction across results, with impact varying widely by site. The rollout showed clear periods of heightened volatility (with notable spikes around December 13 and December 20), reinforcing that meaningful ranking shifts can occur mid-rollout and not just at the start or end.
Google also announced that smaller core updates will be rolled out continuously, meaning that rankings can shift outside announced core update dates.
Why we care: When a core update rolls out over multiple weeks, diagnosis and decision-making need discipline: compare performance across meaningful time windows, avoid reactive changes during peak turbulence, and prioritise longer-term content and site quality improvements aligned with “helpful, reliable, people-first” guidance rather than quick fixes.
Microsoft Bing explains how duplicate content can hurt your visibility in AI search
Bing’s guidance frames duplicate content as more than a traditional indexing/cannibalisation issue: when many pages look the same, AI systems struggle to interpret intent signals and confidently select the best version to surface in AI-driven experiences. This can cause the “wrong” variant to be summarised or cited (e.g., outdated, less specific, or not the preferred market/version), and it can reduce overall visibility because the system has less clarity about which page is authoritative for a given intent. The recommended path is to reduce near-duplicates and make remaining variants meaningfully distinct, especially across localisation or templated pages.
Why we care: AI answers and AI-driven SERP features reward clarity. If your site offers many near-identical URLs, you dilute the signals that help engines choose a canonical “best” source for summaries and citations. Consolidation, canonicalisation, redirects, and intent-first page differentiation become direct levers for earning AI visibility, not just for avoiding keyword cannibalisation.
Optimizing for AI search: why classic SEO principles still apply
Classic SEO remains the primary lever for AI search visibility because AI answers heavily cite pages that already rank highly in traditional results. Higher-ranking pages often have a materially higher chance of appearing in AI outputs, with E‑E‑A‑T signals further increasing the chances for being cited. With AI-referred visits converting better than typical organic traffic, it suggests that AI searchers may arrive with stronger intent, making technical prerequisites (crawlability, performance, structured data) the enabling factors for AI systems to access and interpret content.
Why we care: The practical SEO takeaway is to avoid chasing “AI-only” tactics while neglecting baseline ranking drivers, because the easiest path to AI inclusion is often to win (or maintain) top 10 visibility and publish content that demonstrates clear expertise and trust. Invest in technical hygiene and structured data to improve machine readability and prioritise topic coverage and helpfulness so your pages are both rank-competitive and easy for AI systems to cite accurately.
