SEO & AI Industry Update

What January’s Changes Mean for Your Brand

January reinforced a clear pattern. AI-led discovery is becoming a productised infrastructure, not a novelty, and that changes what “visibility” means for brands.

• Google and Microsoft are developing AI assistants that can browse products, compare options and even complete purchases. For retailers, this makes clear and accurate product and policy information a competitive advantage, not just good housekeeping.
• At the same time, the set of websites AI tools rely on for information may not stay fixed. If publishers restrict how their content is used, the mix of sources cited in AI answers can change quickly, which can affect how brands are presented, even without movement in traditional rankings.
• Rankings still matter. But they are no longer the full picture. AI-generated answers and search result layouts can vary depending on the query and context. That means brands need to monitor more than just positions, including mentions, citations, accuracy and overall sentiment.

AI shopping capabilities are expanding across major platforms

Impacts for brands

For e-commerce brands, visibility increasingly depends on how clearly AI systems can interpret product data. If details like availability, variants or delivery information are unclear, AI assistants may struggle to recommend your brand or transact with confidence. If you’re not e-commerce, treat this as signal of direction, not an immediate workstream.

What happened

Google introduced the Universal Commerce Protocol (UCP), designed to help AI agents shop across retailers and platforms.

Google also published further details on AI tools for retailers, while Microsoft launched Copilot Checkout and Brand Agents, signalling similar ambitions.

Why this matters

If an assistant cannot reliably interpret product availability, variants, shipping or returns, it cannot confidently recommend or transact. This also has knock-on effects for reporting, as some journeys may begin or end inside AI-led flows rather than traditional clicks.

What you can do

• Treat structured product data as core SEO infrastructure, not a back-office task
• Run quality checks on product taxonomy, variants, pricing, delivery and policy clarity
• Prepare reporting for more complex journeys, including assistant-led referrals and assisted conversions

Publisher opt-outs from AI features could change who gets cited

Impacts for brands

The set of websites AI tools draw from is not fixed. If publishers restrict access to their content, which brands appear in AI answers, and alongside whom, may shift over time, even without changes to your own site. Expect more churn in the set of citation sources, even without changes to your site.

What happened

Industry reporting suggested Google is exploring ways for publishers to opt out of AI search features. Polling indicated that a meaningful number of publishers would choose to block AI usage if given the option.

Why this matters

If more sites restrict AI access, the pool of available sources could narrow or skew, changing competitive dynamics and citation patterns inside AI answers.

What you can do

• Expect churn in which domains get cited over time, rather than assuming stability
• Make first-party content easier to trust and reference through transparent authorship, clear policies and unambiguous factual statements

Your brand’s appearance in AI-generated local and recommendation results can change day-to-day

Impacts for brands

For businesses that depend on local visibility or “best of” recommendations, AI-driven results can be unpredictable. Being included one day does not guarantee continued visibility, making traditional ranking-style reporting less reliable.

What happened

A 2026 report suggested that gaining visibility in AI-driven local results can be less predictable and less repeatable than classic local rankings.

Separate research found that AI recommendation lists rarely repeat, with less than 1% repetition across outputs.

Why this matters

Local and recommendation-based searches are often high-intent. If results vary significantly, a single snapshot is not a reliable performance indicator. This increases the importance of consistent business information that AI systems can confidently reuse.

What you can do

• Increase monitoring of AI local prompts if relevant to your business, and treat outputs as probabilistic rather than fixed rankings
• Invest in strong entity foundations: consistent business details, authoritative citations and structured data
• Encourage customer reviews, particularly those that reference the location where the service area matters

More people are starting discovery inside AI tools, not Google

Impacts for brands

A growing proportion of customers may encounter your brand for the first time through an AI tool rather than a traditional search results page. That means early perceptions of credibility and relevance may form before someone ever visits your website.

What happened

A study reported that37% of consumers now start searches using AI tools rather than Google.

Why this matters

Even if Google remains dominant overall, early-stage discovery is fragmenting. That changes where brand awareness is built and where trust starts to form, often before someone reaches your website.

What you can do

• Monitor how your brand appears in AI prompts for key searches and how competitors are positioned
• Optimise content for extraction: clear headings, short definitions and specific, verifiable claims that AI tools can quote accurately

Algorithm updates can still reshape visibility across entire sectors

Impacts for brands

Brands that rely on being discovered through news, updates, guides or timely content can see sudden traffic changes, even when nothing on their website has changed. Visibility can rise or fall quickly if platforms reassess how and where that content is surfaced.

What happened

Reporting on Google’s December 2025 core update showed significant visibility drops for some news publishers, particularly across discovery-led areas like Top Stories and Discover. While some large publications saw only small dips, others experienced much larger declines.

Separate industry analysis also suggested publishers are preparing for long-term reductions in search referrals, with projections of a 43% drop by 2029.

Why this matters

For publisher-style businesses, or any site dependent on fresh discovery surfaces, performance can swing sharply without any obvious trigger. This reinforces that relying on a single traffic source, even Google, increases risk during periods of algorithm volatility.

What you can do

• Reduce reliance on one channel by strengthening alternative discovery routes, including AI citations, third-party sites and social platforms
• Strengthen visible trust signals such as clear authorship, sourcing and editorial standards, especially where content influences reputation or purchasing decisions
• Keep technical foundations tight: clean templates, clear indexation controls and minimal technical drift are more likely to hold up when systems change

Bing is pushing AI assistance earlier in the discovery journey

Impacts for brands

AI-led discovery is no longer limited to one platform. Even where the overall market share is smaller, AI assistants are being positioned as the starting point for information and decision-making.

What happened

Bing tested a new homepage layout that gives Copilot more prominence, reinforcing its focus on assistant-led discovery.

Why this matters

While Bing’s market share is smaller, the direction mirrors wider platform trends: AI assistance is becoming the default entry point.

What you can do

• Where audiences skew enterprise or Windows-heavy, include Bing and Copilot prompts in AI visibility and reputation monitoring

AI Overviews are increasingly shaped by core search signals and engagement behaviour

Impacts for brands

For many searches, the AI Overview is now the first thing a potential customer sees. How your brand is described, referenced or framed inside that answer can change over time, even if your rankings remain stable.

What happened

Google confirmed that AI Overviews and AI Mode rely on its core search ranking signals. At the same time, testing suggested that whether an AI Overview appears can vary by context and query, and doesn’t appear consistently every time.

Industry coverage also highlighted risks when AI Overviews misrepresent brands, particularly through opinions or discussions on forums such as Reddit and Quora. Third-party discussion can influence how brands are framed when authoritative first-party pages are thin or ambiguous.

Why this matters

If an AI Overview appears, it often becomes the primary source of information a user sees. Visibility is no longer just about where you rank, but whether your brand is included, accurately represented and framed credibly within that answer.

Engagement-based triggering also introduces volatility: search results can “look different” without a formal update.

What you can do

• Monitor AI answers alongside rankings, including citations, tone, accuracy and brand mentions
• When performance changes, check whether the search layout or AI Overview presence has shifted
• Prioritise content that is easy to cite: concise factual statements, clear sourcing and supporting pages that demonstrate expertise and trust

What This All Means In Practice

Across all of these updates, the theme is consistency and trust. SEO is no longer just about ranking positions. It’s about being represented accurately inside answers, being understandable to AI systems, and having data and content that platforms can safely reuse.

For most brands, the priority is making information clear, verifiable and easy to interpret. That’s what allows both search engines and AI systems to recommend you with confidence.