SEO Fireside Chat: Navigating the Answer Engine Era
Following Google I/O and the rollout of the May 2026 Core Update, search engines are fast evolving into something different: answer engines, and brands must start truly treating them as such if we want to succeed in search.
To explore what these changes mean for our clients across B2B and B2C sectors, the team here at ICS-digital in Leeds recently gathered for an internal fireside chat.
We sat down to dissect and discuss all the latest news: from Generative Engine Optimisation (GEO) to the reality of zero-click searches, cutting through the industry panic to find the practical, data-backed strategies that drive long-term growth.
Here are the core insights and actionable tips we are using to guide our clients through this new era of search.
The Rise of the Answer Engine
Senior SEO Strategist Jonny Hunter, opened the discussion by noting that while Helpful Content has been emphasised by Google for years now, there has been an acceleration towards meeting the needs of customers who are more accustomed to conversational search - "It’s less about keyword insertion and more about genuinely satisfying user intent" he explained.
With clarity in user intent taking centre stage, Google’s E-E-A-T guidelines remain the core principles to follow, even as AI changes the delivery mechanism and AI Overviews take up more and more search real estate.
Our team agrees that in spite of the AI evolution (in capabilities and customer uptake) there hasn’t been a total reset of SEO, but rather an evolution.
Practically all the core mechanics remain rooted in E-E-A-T (Expertise, Experience, Authoritativeness, and Trustworthiness), but SEO success now depends even more on how clearly a brand addresses the user's specific problem and matches their search intent.
Our SEO Lead, James Bellamy, summarised this shift as follows:
"Realistically, whether someone is searching via traditional desktop, mobile, or entering conversational LLM interfaces, these platforms have become answer engines.
Google's ultimate objective has always been to answer the user's question and intent with the best possible solution. The brands that deliver that cleanly are the ones the algorithm rewards, update after update."
Jonny added that this shift makes content quality and originality more critical than ever: derivative content is increasingly penalised, even when it satisfies some form of user intent.
This is one of the reasons why it’s worth being cautious about producing informational content with AI tools. The very nature of these tools is grounded in repackaging existing information without adding anything original, making it very hard for it to rank effectively.
The Zero-Click Reality: A Strategic Opportunity
As far back as 2020, we’ve been seriously exploring zero-click searches as an opportunity - as this article from our marketing director Martin Calvert outlines.
In 2026, user behaviour data - and the changing layout of the SERP - paints a stark picture for traditional traffic acquisition which has been worrying many marketers.
A 2026 study by Similarweb revealed that 68.01% of all Google searches globally now end without a single outbound click to the open web.
However, Data from Semrush’s Search Behavior Report reveals that not all search queries are the same, and the zero-click scenario can vary wildly depending on user intent.
Informational queries are undoubtedly the most impacted by AI tools, triggering AI Overview responses. On the other hand, transactional queries are impacted much less:
Query Intent Type
Zero-Click Rate
Informational Queries (e.g., research, definitions, general facts)
74%
Transactional Queries (e.g., buy, order, register)
31%
While a 74% zero-click rate for informational keywords sounds alarming, Laura Smith, Head of Client Strategy, suggests this is more of a strategic pivot than a commercial disaster, and that it might not be as big a change as it seems:
"We have to ask whether those informational clicks were truly driving direct revenue in the first place. Informational queries signal users who are in a deep research phase, clicking through multiple sites without any immediate intent to buy.
The AI Overview simply fulfills that research step instantly on the SERP, and being cited in that summary is still vital.
It introduces your brand during the critical early research phase, establishing the mental availability and recall needed so the consumer chooses you when they are ready to convert."
James Bellamy expanded on this by highlighting a recurring theme from brightonSEO 2026: the concept of “influence”. In the AI era, brands should aspire to position themselves as authoritative influencers within the SERP ecosystem.
Jonny Hunter suggested that the definition of success in SEO is evolving, at least for informational queries. "The goal for these queries is no longer just fighting for a blue link - it is about being the cited source within the AI response itself" he noted.
"When evaluating content, ask a straightforward question: is this piece written to rank, or is this written to help? It is purely written to hit keyword checkboxes, it may not hold the necessary authority to surface in AI-answers."
The real value of informational content lies in building trust and thought leadership from day one. By capturing the user’s confidence during the research phase, companies position themselves as the preferred choice when the customer is finally ready to buy.
When we look at the big picture, from Helpful Content updates and E-E-A-T to recent core shifts, Google’s ultimate goal has always been about measuring real quality, not just rewarding people for “gaming the system”. In a way, we’re seeing the next phase of this in AI Overviews, AI Mode, and Gemini-driven search, which are forcing companies and creators to prioritise genuine value over algorithmic checkboxes.
Our suggestion to best adapt to new search landscape is content strategy that structures content in different ways, depending on the intended outcome of the individual pages:
- Informational Pages: You want this content to answer user queries as much as possible. In this new era of content, it should be built for high semantic depth and factual authority, explicitly structured to be ingested and cited by AI models.
- Commercial Pages: Trying to rank for LLMs doesn’t really help your end goal here. Commercial pages should be built with flawless user experience to capture the high-intent, high-CTR traffic that allows you to maximise conversions.
AI Reporting: Marketers’ Biggest Challenge?
The elephant in the room for agencies and marketers alike is the evolution of reporting in this new landscape, as it is how we track marketing ROI.
We used to get clicks out of informational content, and that helped us quantify success. In the AI space, you may get the same level of influence in someone’s brain, but you don’t have the same quantifiable number you can put in a report to a client.
As problematic as that may sound, it’s essentially a mentality shift, not an outcome shift: clicks and impressions being down is not the apocalypse many people may think it is.
Because the modern consumer journey jumps between search bars, social feeds, and AI tools, digital marketing reporting must move past linear, impressions-only attribution, and start measuring mental availability and influence.
While reporting in these ever-changing, opaque new tools has been a rough start for marketers, fortunately new tools are emerging to help.
At ICS-digital we are shifting client reporting toward macro business health indicators.
Instead of relying solely on “vanity" traffic metrics that are being muddled by the zero-click transition, we integrate deeply with our clients' internal analytics, and use a blend of first-party and third-party tools.
These include our data-led, custom-made internal reporting dashboards, industry-standard AI-tracking tools like Ahrefs Brand Radar, Google's Gen-AI performance reports and more.
For agencies and marketing teams, great execution is only half the battle; the real goal for any agency is clear attribution. We need comprehensive data to directly link our marketing strategies to bottom-line results
For example, for our international iGaming and e-commerce partners, we track hard bottom-line events like First-Time Deposits (FTDs) and direct transaction completions i.e. sales.
If raw organic traffic pauses due to SERP changes, but total organic conversions and revenues show a positive trend, no panic is needed: the search strategy is performing exactly as intended!
As a great example of the efficiency of our reporting, Paddy shared a great piece of analytical observation regarding search engine behavior:
"During the rollout of the latest update, we tracked distinct ranking volatility for our client [Client] roughly 48 hours before Google officially announced the core update. It is standard algorithmic testing behaviour - the data completely stabilised and recovered a few days later."
The takeaway for any marketer or business owner is simple: when an algorithm update triggers a sudden shift in your tracking tools, do not make reactive, panicky changes based on two or three days of volatile data. The worst thing a brand can do is rip up a sustainable strategy while the digital landscape is still rebalancing.
Technical Changes: Is Llm.txt Worth The Hype?
Any major industry shift comes with a wave of red herrings. Recently, a lot of attention has been given to llm.txt files - a proposed standard allowing webmasters to specify how AI crawlers should interact with their content.
An initial lack of guidance on these files meant all sorts of interpretations were proposed, with some self-proclaimed “GEO experts” claiming it is the key to AI search tools finding your brand.
Google's John Mueller recently clarified that while Google may crawl these files, they are not currently a search ranking factor. Much like a CTA boosts conversion rather than discovery, llm.txt might eventually help AI agents navigate your site, but it isn't a 'quick fix' for visibility.
This means that, while it might be important in a future where AI agents are everywhere, most websites can focus on current, proven needs and opportunities rather than optimising for a future scenario that may or may not materialise.
Our SEO Specialist Patrick Crier advises clients to keep their focus on proven technical signals that will definitely have real-world impact.
"If a client has a queue of development fixes, implementing an unproven text file shouldn't sit at the top. In complex, regulated environments like international finance or iGaming, our technical priority remains on flawless JavaScript rendering and absolute core web vital health. If search crawlers and AI agents cannot render your page seamlessly, no text file will save your visibility."
The bottom line is, llm.txt could have an impact on your website, but as of 2026 it is definitely a low-priority file to optimise. It could be part of a future-proofing strategy, but it isn’t a strategy on its own.
Our team advises focusing on these fundamentals first, like making sure the whole site quality supports the individual page. It’s worth asking yourself: has the technical architecture of the website been optimised for SEO? Has the internal linking? Is the rest of the content semantically related across the entire site?
Structural Clarity for Users and Crawlers
When we look closely at the data behind what these answer engines actually want, it becomes clear that optimising for AI isn't about chasing hidden technical tricks.
Many of the new elements that AI models favour - like upfront facts, transparent source citations, and clear formatting - are fundamentally the exact same things that human readers look for. By structuring a page for ultimate clarity, you serve both audiences at once, naturally guiding the user toward a conversion.
Interestingly, building a page that an AI model loves to cite results in an excellent layout for human users. SEO Specialist, Jacob Manners, highlighted how this structural clarity acts as a proxy for better conversion rates:
"Similarly to humans, AI models favour content that is highly explicit, deeply factual, and directly structured. Placing clear, definitive answers right at the top of the page serves the user and the AI agent simultaneously.
If data shows that top-ranking pages lose over half of their traditional CTR when an AI Overview is present, your copy must be distinct and immediately obvious. When you give users instant clarity about what your business offers, you naturally improve the likelihood of a conversion."
A New Kind Of Reputational Management
Because AI Overviews gathers info from a broad range of web sources, brand protection has expanded beyond standard competitor monitoring.
AI engines frequently cite community-driven platforms like Reddit and YouTube. While exact percentages vary from AI tool to AI tool, up to 30%-40% of queries reference this kind of answers, and they can’t be ignored in any brand’s strategy.
Paddy Crier raised a vital point regarding brand equity protection, and how it has now significantly changed from the pre-AI era:
"Because AI models freely pull from third-party discussions and forums, brands must proactively build reputational management content.
If a disgruntled customer, an independent blogger or a competitor posts a negative thread about your service compliance, and your brand doesn't have an explicit, authoritative page addressing that specific issue, the AI summary may ingest the negative forum post and present it as a factual answer. You have to occupy that data layer yourself."
With community-led directly surfacing in brand queries, it’s not just competitors you need to worry about ranking against you - it’s the whole internet.
Embracing The No-Click Shift With Distinctiveness
Rather than the “death of SEO”, the transition from search engines to answer engines should be seen as an invitation to build distinct, authoritative brands that stand out across every single digital touchpoint.
As detailed in our latest White Paper “The Human-Machine Memory Gap”, achieving this requires a shift toward what we call “Distinctiveness Intelligence™”.
This comprehensive, data-led framework we developed, ensures brands can react efficiently to fast-moving algorithmic changes and stay ahead of the competition in the complex world of AI-driven discovery.
Through this framework, we directly address the "Human-Machine Memory Gap", as it aligns the creative and emotional cues needed for human recognition with the semantic clarity and structured consistency required for machine retrieval.
This ensures you can future-proof your strategy across the shifting AI landscape, and unify it across SEO, Digital PR, and paid media so you are ultimately chosen by both humans and machines.
