SEOFOMO’s Organic Traditional & AI Search Trends for 2026: Top Challenges, Expectations & Actions

Over 60 SEO professionals responded to SEOFOMO’s 2026 Organic Search Trends Survey, and the results paint a clear, refreshingly pragmatic picture of where organic search is heading across both traditional search and AI-powered discovery, as well as what it will take to stay competitive. Thank you to everyone who participated, and congratulations to Emina Demiri-Watson, the winner of the SEOFOMO mug and hoodie giveaway.

This is a very experienced group: around 70% have 10+ years in SEO, with most respondents based in the UK, the US, India, Spain, and Germany, and working across ecommerce, marketplaces, publishing, and travel. Here are the key findings.

If there’s one takeaway that shows up again and again, it’s this: AI search isn’t “killing SEO”. The real problem is the amount of confusion (and hype) around what AI search actually changes, especially when it comes to visibility, attribution, and how people make decisions online.

• Many SEOs describe 2025 as the year discovery shifted upstream. AI summaries absorbed a lot of the early-funnel exploration and comparison… while traditional search increasingly became the place users go to validate, dig deeper, and ultimately decide.

• That shift is already changing strategy. The focus is moving away from pure rankings-and-clicks growth and toward recognition and credibility: building strong brands and entities that show up consistently across platforms, creating citation-ready content that’s structured, evidence-led, and easy for systems to summarize accurately, and expanding beyond on-site SEO into broader visibility work: PR, community, reviews, and social/video.

• Measurement is evolving too. Teams are rebuilding reporting away from last-click and “prompt rank” thinking and toward visibility and influence signals: mentions/citations, branded demand lift, assisted impact, and business outcomes—while being honest that the tooling is still messy and far from perfect.

• Looking at 2026, the expectations are consistent: more AI blended into the SERP, fewer informational clicks, heavier monetization inside AI experiences, and intensifying competition around quality. Which is why the fundamentals that actually compound—technical clarity, authority, originality, and stakeholder communication—are showing up as the most durable advantages for SEO teams next year.

Experienced SEO specialists and digital marketers have shared their thoughts about these outcomes.

Lily Ray, Vice President, SEO Strategy & Research at Amsive: 

“As OpenAI and Google launched new models of ChatGPT and Gemini throughout 2025, I think one thing became clear: large language models are highly reliant on up-to-date information from search engines to provide accurate answers. Therefore, one of the best ways to drive visibility from AI search is to be among the chosen results when LLMs use web search – and that boils down to having solid SEO, strong brand awareness and a positive reputation.”

Mark Williams-Cook, Director at Candour and Founder of AlsoAsked: 

“It’s fascinating that the data clearly shows the disparity that we’ve anecdotally seen ‘on the ground’. That is, the overwhelming majority of experts are saying that the primary drivers for AI visibility are still the foundational SEO strategies that we have used for years, and while there is a new paradigm to consider, ‘GEO’ is not some standalone concept.This isn’t the story that budget allocation is telling, with many teams reporting traditional SEO spends being flat or down, and more spend going on the AI tooling land grab.While I don’t see any real resistance to the idea that AI has changed the interaction paradigm, or that there is now technically another ‘layer’ on top of search, my experience tells me that “shiny thing” has eaten up more than a reasonable share of budget. Over 2026, I think we’ll see a rebalance of budget, where organisations investing in strong brand, PR, and original content will start to pull away from those that are chunking their budget into ‘engineering’ what they have to try and improve visibility, which will eventually move on.”

Barry Adams, SEO & Audience Growth Consultant at Polemic Digital: 

“The SEO industry has always been about adapting to the latest trends and technology innovations. This is certainly the period of most radical change we’ve seen in SEO and user behaviour, and as a result our industry has experienced a separation of the wheat from the chaff. 2026 will be a continuation of that trend. SEOs who can adapt will thrive. Those who can’t will abandon SEO or try to prey on uncertainty and ignorance by embracing the ‘GEO’ hype. AI search is real but it is also underpinned by classic SEO. To approach AI search optimisation as anything other than an extension of SEO is folly – to optimise for AI without SEO is like building a castle on quicksand. At the same time, the business value in optimising for AI has yet to be proven. Shifting all your efforts into AI and neglecting the channels and tactics that have provided your success to date is extremely short-sighted and likely a road to ruin.”

Let’s go through the 13 top organic search trends with comments and insights from experienced search professionals:

1. The biggest misconception about traditional or AI search

The main misconception is that AI search is “replacing” traditional search and that SEO is therefore dead or fundamentally obsolete. Across responses, this belief is described as overhyped, premature, and strategically dangerous.

The shared expert view is that the real danger isn’t AI replacing search; it’s misinterpreting what AI search actually is.

• SEO is not dead
• Fundamentals still matter
• Brand, trust, and multi-channel presence matter more than ever
• AI search and traditional search are complementary systems, serving different stages of the user journey

The biggest misconception, ultimately, is confusing confidence with correctness; and novelty with strategy.

About this, Gianluca Fiorelli, International SEO Consultant, says: 

“SEO never really was about “optimizing search engines” (how can we possibly do it?), but about optimizing brands digital presence for findability in the right place and moment. Because of this SEO also is News SEO, Local SEO, Marketplace SEO, SEO for Social Media… and now it is also SEO for AI Search. Each one has its own characteristics and even quite different algorithms. So, GEO (or AEO or LLMO or AIVO) is not a substitute for SEO but a complement of SEO.”

Dave Peiris, technical SEO consultant, says: 

“The biggest misconception I see – especially at the C-suite level – is the idea that AI search is something completely separate from traditional SEO, and therefore needs an entirely new approach. It’s a misconception that’s led to regular SEO budgets being squeezed, but “AI work” being much easier to get resource for. In reality, for the kinds of commercial queries most businesses care about, AI search is still built on top of the same underlying ecosystem. Tools like ChatGPT very frequently search Google and use the results to build its responses. If you don’t rank well in traditional search results, you’re unlikely to be represented well – or at all – in those answers. It’s not accurate to say AI search is “just SEO”, because there are real differences in how content is discovered and surfaced, but good SEO has never been more important. Not only does it influence how you appear in traditional search results – for many sites their largest revenue-driving channel – but it’s also the foundation on which AI responses are built.”

Sophie Brannon, Co-Founder & Director of StudioHawk US, says: 

“SEO has evolved considerably over the years but the fundamentals will always remain the same. While AI search is not replacing SEO, we are entering the new consideration era where people are using multiple platforms including LLMs, social media platforms, forums and more, meaning there are even more touch points than ever before for your brand to be seen. If anything, this enhances the need for a strong website that’s well optimized, fast and has amazing content and authority, while also tying SEO more into the overall marketing funnel rather than floating on its own. Now it’s important to be everywhere and SEO plays a big role in that”

1.1 “AI Search Replaces SEO / Traditional Search”

The most repeated misconception is that:

• AI search will fully replace Google and stop sending clicks
• SEO no longer works
• GEO / AI SEO is a completely separate discipline

Consensus reality:

AI search sits on top of traditional search, not instead of it. It still depends on:

• Crawlability
• Content quality
• Strong entities and brands
• Authority and trust signals (E-E-A-T)

SEO fundamentals remain the backbone; shortcuts and “AI hacks” do not replace them.

About this, Arnout Hellemans, freelance SEO, PPC and analytics consultant, says: 

“AI doesn’t replace all searches, but for certain ‘solved queries’ this definitely is happening. Because when there is massive consensus it makes answering very easy for an LLM based model. But my biggest eye opening moment was that for a lot of the unsolved queries need an index of ranked documents (for instance a search index). Google is battling the freeloading of their search index by different other companies. So IMHO things have changed but fundamentally a search index is very needed. Just way less visible than the previous rankings and clicks we used to track.”

Gus Pelogia, Sr. SEO and AI Product Manager at Indeed, says: 

“AI-powered search is still using many elements of “traditional” SEO. I understand some professionals trying to give new names for different reasons, but for me it’s clear this is an evolution of SEO. Metrics and goals are changing, just as they changed in the past. Regardless of names, search professionals will remain relevant in 2026.”

Iva Jovanovic, SEO and Content Specialist & Conference Organizer: 

“There is a certain obsession with AI trending, burying search (and SEO) in its grave without any proof of it happening. Yes, there is a shift in how search is now. It is no longer about rankings and showing links to websites – it is about answers, summaries, and recommendations shaped by LLMs that happen before a user ever reaches a website. Organic search isn’t disappearing. It’s moving downstream into visibility, brand influence, and decision-making, and the strongest strategies are the ones that adapt measurement and strategy accordingly. The biggest challenge that is already happening and will probably continue, is businesses misreading and overinvesting in unstable shortcuts and fake trends, while neglecting their brand and technical foundations. AI isn’t replacing search. GEO isn’t replacing SEO. ChatGPT doesn’t get all the traffic. AI in SEO is about having another medium/channel where results will be displayed. Your strategy and way of thinking should not have LLMs and AIs as the sole focus – but it shouldn’t forget about them either. It should include the new medium, but with the focus being on delivering good websites with good content and a good technical foundation. Build websites that clearly represent what the business is, what it does, and why it is credible. No shortcuts and generic AI content. Gaining temporary wins through cheats, exploits, and misuses will collapse as soon as algorithms change. To me, SEO was always more than adding keywords, I looked at it as a whole system. And, in my opinion, SEO in 2026 needs to be a system that connects different aspects. You have to have a strong technical foundation, provide content with intent, and align the strategy with the rest of the marketing team.”

1.2. “AI SEO Is a Totally New, Separate Skillset”

Many respondents push back against the explosion of new acronyms (GEO, AISEO, AIO, etc.) being marketed as entirely new strategies.

Consensus reality:

AI search optimization is an evolution, not a new species:

• Core SEO principles still apply
• The variables and emphasis have shifted (brand, authority, multi-channel signals)
• Treating AI search as a standalone service leads to bad decisions and wasted effort

About this, Myriam Jessier, SEO & Technical Brand Visibility Consultant, says:

“AI SEO isn’t a new vertical; it’s an exaptation of the SEO skillset that turns search expertise into AI visibility, giving SEOs the strategic leverage to finally demand the budget, support, and seat at the table they’ve always deserved. We didn’t build structured data (Schema) or high-quality authoritative blogs so that a chatbot could summarize them; we built them to get more traffic and brand recall from Google. Now, those same assets are the primary fuel for LLM visibility and RAG. That’s called exaptation or co-option, a shift in the function of a trait during evolution.”

Roxana Stingu, Head of Search & SEO at Alamy, says: 

“SEO has been declared dead many times, yet it keeps evolving as search engines do. Word2vec didn’t end SEO. Semantic search didn’t either. Nor did machine learning. Each step simply improved how search engines understand language and intent and we SEOs just adapted every time. The same is true today with the shift to LLMs and RAG. This isn’t a new area altogether, it’s still search, just powered by more advanced retrieval and interpretation. The fundamentals of a search engine don’t really change because that’s what makes it a search engine in the first place. SEO is still about optimising for these systems but we do need to take higher jumps in our learning and adaptability to keep up with the faster, bigger leaps in the technology behind search.”

1.3. “AI Search Is Always Accurate, Real-Time, and Objective”

Another major misconception is assuming AI answers are:

• Always factual
• Always up to date
• Verified because they cite sources

Consensus reality:

AI systems:

• Synthesize, they don’t verify
• Can hallucinate or misrepresent sources
• Collapse uncertainty into a single, confident-sounding answer

Traditional search still plays a critical role by preserving disagreement, multiple perspectives, and user judgment.

About this, Myriam Jessier, SEO & Technical Brand Visibility Consultant, says: 

“The user used to own the synthesis, opening 5 tabs to compare multiple products. Our goal was to be one of those tabs. Today, AI owns the synthesis: the user asks a question and relies on LLMs to do the legwork. AI reconstructs your brand from all accessible brand layers: 1) Known brand: what you say about yourself as a company. 2) Latent brand: what people say about you online (Reddit, forums, social media). 3) Shadow brand: outdated documents, rumors, leaked memos – everything that lives in the shadows of your official brand can be surfaced. 4) AI-narrated brand: AI co-authors brand narratives and sometimes drifts, making things up as it goes.  Your brand drift crisis can take on different forms: made up features, hallucinated secret menu items, phony login URLs, etc. The less AI knows about your brand, the more it may “fill in the blanks”.”

1.4. “Traffic, Rankings, and Prompt Tracking Are the Right Metrics”

Many responses criticize:

• Treating AI answers like SERPs with “rankings”
• Measuring success via prompt tracking alone
• Assuming AI search is a major direct traffic or conversion channel

Consensus reality:

AI search primarily impacts:

• Discovery
• Research
• Consideration

Success is less about clicks and more about being cited, trusted, and recognized as a credible entity upstream.

About this, Natalia Witczyk, International SEO Consultant and CEO at Mosquita Digital, says: 

“AI Chatbots have turned traditional digital marketing thinking upside down. There is no funnel anymore as we know it, and there aren’t positions to track either. While it will take time for marketers to adjust, the new outlook on metrics and attribution is inevitable. SEOs have a lot of client education to do in this matter. My prediction is that 2026 will see many AI visibility tools being wiped out, which will speed up the process of understanding that AI position tracking is a bad idea.”

Mordy Oberstein, Head of Brand, SE Ranking, says: 

1.5. “More Content and Faster Output Wins”

Respondents repeatedly call out the belief that:

• Volume beats quality
• Velocity leads to visibility
• AI rewards mass content production

Consensus reality:

AI raises the bar:

• Clarity > volume
• Authority > speed
• Consistency > scale

Weak foundations are exposed faster by AI—they are not rescued by it.

Chris Green, Technical Director at Torque Partnership, says: 

“Doing more content faster with AI “feels” like it’s checking all the right boxes, but it’s not what people think.  Whilst some have seen that “fresh” content works better in AI Overviews and ChatGPT, the effect is temporal and the easily-trackable benefits are not enough. Meanwhile, the risk is that actual high-touch content has been neglected and we KNOW that Google is aiming on focusing on original ideas as a marker of quality.”

1.6. “AI Understands Like a Human”

Several answers stress that AI is often misunderstood as a reasoning or truth engine.

Consensus reality:

AI:

• Predicts text; it doesn’t understand intent
• Produces confident outputs that can mask uncertainty
• Shifts judgment from the user to the system, which changes trust dynamics

2. Biggest Organic Search Challenges in 2025 & How They Were Addressed

The defining organic search challenge of 2025 was not rankings loss; it was visibility, attribution, and trust in a world where AI absorbed clicks without removing influence. Organic search didn’t disappear in 2025; it moved downstream.

• AI absorbed: Discovery, basic explanation and early comparison
• Traditional SEO still powers: Judgment, commitment, trust and conversion.

The teams that succeeded were those who:

• Stopped optimizing for attention
• Started optimizing for decision-making
• Treated AI visibility as influence, not traffic
• Rebuilt measurement, communication, and expectations accordingly

The real challenge of 2025 was not AI itself, it was learning how to operate when influence no longer looks like clicks.

Clara Soteras, News SEO Consultant, says: 

“The survey results reveal a strong consensus among SEO professionals that the biggest challenge of 2026 will not be technical optimization, algorithm updates, or radical changes in content production or Google policies, but rather the need to educate and “evangelize” clients about a fundamental shift in attribution models and success metrics. This sentiment is powerfully captured in the idea that “The teams that adapted best were those who stopped asking: ‘What got the click?’ and started asking: ‘What shaped the decision?’ That mental shift—not any tool—was the real measurement evolution of 2025,” a statement that clearly reflects the shared mindset of the SEO community.”

Tom Capper, Senior Search Scientist at STAT & Moz, says: 

“I’m optimistic about CTR erosion. AI Overviews have plateaued or are perhaps even on the decline, and the big feature in Search Labs is the far more click-friendly Web Guides. Google’s monetisation model also still relies, for now, on a user journey that clicks out to external sites further down the funnel. At the same time, ranking has become increasingly poorly correlated with CTR. We’re encouraging customers to measure pixel-depth SERP metrics and tag by intent or by features alongside, to get a more meaningful picture.”

Across responses, five major challenge themes consistently emerged:

2.1. Click & Traffic Erosion from AI Overviews and Zero-Click Search

Most frequently cited challenge

• Stable rankings and impressions, but collapsing CTR
• AI Overviews, AI Mode, SERP features, and ads pushing organic results off-screen
• Informational and top-of-funnel content hit hardest
• Panic triggered by “traffic down” narratives despite stable revenue or conversions

How it was addressed

• Reframing organic search as a visibility and influence channel, not just traffic
• Shifting KPIs from clicks to:
  • Brand mentions
  • Citations in AI answers
  • Assisted conversions
  • Branded search lift
• Targeting mid-funnel, high-intent, and post-synthesis queries
• Designing content meant to be used after AI summaries, not consumed instead of them

Nitin Manchanda, Founder & Chief SEO Consultant at Botpresso: 

“It’s now evident that traffic metrics alone no longer tell the story. Visibility, citations, brand mention lift, and assisted conversions are becoming the real KPIs. AI summaries and zero-click experiences are eroding CTR even when rankings remain stable, pushing us to rethink “success.” This aligns with what many are observing that organic traffic is declining not because SEO is failing, but because search interfaces are changing.”

2.2. Measurement, Attribution & Data Loss

Second most common challenge

• Reduced data in Google Search Console
• Removal of parameters like num=100
• GDPR and privacy limitations
• Lack of reliable visibility into AI-driven discovery
• Expensive, immature, or noisy AI tools
• Difficulty forecasting AI Search impact

How it was addressed

• Combining imperfect signals:
  • Traditional SEO metrics
  • On-site behavior
  • Brand mentions
  • Qualitative insights
• Rebuilding reporting frameworks:
  • Early directional KPIs
  • Influence and visibility metrics
  • Cross-channel attribution narratives
• Abandoning “rankings alone” as a success proxy

2.3. Client, Leadership & Stakeholder Education

A major operational challenge

• Leadership misunderstanding AI search
• Panic-driven requests to “switch to AI”
• Difficulty getting buy-in for SEO declared “dead”
• Overconfidence in GEO as a shortcut or rebrand

How it was addressed

• Heavy education and expectation-setting
• Explaining what changed vs what didn’t
• Repositioning SEO as part of a broader marketing ecosystem
• Updating sales decks, pitches, and internal communication
• Framing AI Search as complementary, not competitive

About this, Eli Schwartz, Growth Advisor and SEO Strategic Consultant at Product Led SEO, says:

“I loved the data on the mismatched expectations between reality and management and I think this will be a big theme in 2026. Many companies dove into AI out of FOMO, but the reality is that the returns and outcomes of what is happening with AI haven’t really met the expectations. I think SEO teams will need to get much better at understanding the underlying motivations of what leaders are looking to accomplish, rather than just throwing tools at their requests (something I discussed in a post I wrote about pitching HIPPOS).”

2.4. Constant Volatility: Updates, SERP Shifts & Technical Constraints

Persistent background pressure

• Frequent core updates
• AI-driven SERP volatility
• Indexing slowdowns
• Technical debt and legacy platforms
• UX/CRO becoming a ranking differentiator
• Governance and security blocking LLM crawlers

How it was addressed

• Doubling down on: Technical clarity, crawlability, site structure, internal linking.
• Rewriting frontends and optimizing performance
• Building governance cases for LLM access
• Prioritizing execution and stakeholder alignment over theory

2.5. Shift from Keywords to Brand, Entities & Authority

Strategic evolution across responses

• Keyword volume and rankings becoming less predictive
• AI rewarding brand presence across the web, not just on-site SEO
• LLMs synthesizing from: Mentions, reviews, PR, community discussions, local and contextual signals.

How it was addressed

• Entity-led content strategies
• Stronger topical authority
• Original data, definitions, tables, comparisons
• Multi-channel visibility (PR, community, brand)
• Geo-legibility strategies for international SEO to prevent AI “geo-drift”

About this, Silvia Martin, SEO Consultant and Founder at Trebole, says: 

“SEO has been moving away from keyword matching towards brands and entities for a long time. AI search is not changing the direction, but it is turning up the volume. AI search doesn’t retrieve pages, it generates answers from training data and online sources. These systems rely on brand mentions, citations, and consistent visibility across different platforms. This makes branding an essential SEO factor, not just a marketing exercise. For international SEO, the stakes are higher: without clear country and language signals, AI may surface the strongest or most cited brand globally, even if it is not the most relevant locally.”

Gianluca Fiorelli, International SEO Consultant, says: 

“The classic “do keyword research, find low hanging fruits (low kw difficulty and significative search traffic), create content, and pass to a new keyword” is not working anymore. With AI we definitely entered in the age of Entity Search and Topical Authority. In a zero click search, the main objective is to be visible everywhere, at every stage of the search journey, being memorable, and considered such a source of truth that AI models cannot but cite us (aka link to us) or at least mention (unlinked brand mention). This can only be achieved: 1) perfectly knowing our targets. 2) perfectly knowing the topics targeted by our business. 3) engineering content hubs covering the potential search journey our targets can do for our topics. 4) creating resources that AI cannot (easily) replicate.”

3. Most Significant Change to Organic Search Strategy & Goals in 2025 and Why?

The most significant change was a broad move away from “rankings + traffic growth” as the primary objective, toward “visibility, citations, and brand-driven influence across surfaces” in both traditional and AI search.

2025 strategy shifted from “win rankings” to “win recognition.” In practice, that meant:

• Building stronger brands/entities
• Optimizing for citations and correct framing in AI answers
• Measuring success beyond clicks
• Expanding SEO into multi-channel reputation + visibility work

The “why” is consistent across answers: users now discover and decide across AI tools, Google, and social/community platforms simultaneously, so organic success requires showing up credibly everywhere, not just ranking in one place.

About this, James Norquay – Founder Prosperity Media & Sydney SEO Conference, says: 

“Agree with the findings in the report that the mandate for SEOs has shifted from mere ‘ranking’ to comprehensive brand protection. The ‘Search Everywhere’ trend isn’t just a prediction; it’s a strategy we’ve been executing for years by providing holistic SEO advisory across Google, YouTube, TikTok, Reddit, and brand-owned ecosystems. It is no longer enough to be visible; we must ensure that every touchpoint serves as an authoritative source of truth. Furthermore, as LLMs become primary discovery engines, we are leveraging Digital PR at scale to secure visibility within AI citations. Tier 1 media coverage is now a dual-purpose asset: it drives traditional search authority and ensures brand prominence within the LLM landscape.”

Across responses, six major shifts show up repeatedly.

3.1. From Traffic Growth to Traffic Protection (and Accepting Flat YoY)

A recurring theme, especially among SEO-mature orgs—was resetting expectations:

• From “grow organic” to “maintain / defend”
• From top-line sessions to business outcomes (leads, revenue, activation)

Why:
AI Overviews and zero-click experiences commoditized broad informational demand; growth became less predictable and less efficient.

3.2. From Keyword-First to Entity, Intent Clusters, and Topic Authority

Many teams shifted planning away from individual keywords toward:

• Topic clusters
• Intent journeys
• Entity relationships
• “Core journeys” tied directly to revenue-relevant outcomes

Why:

It’s impossible to optimize for every question that triggers an AI answer, and AI systems surface entities and trust, not just exact-match strings.

About this, Amanda King, SEO, Growth Consultant and Founder at Floq, says: 

“This is something we’ve been moving towards since RankBrain, BERT and MUM. Until both reporting tools and research tools catch up, a topical rather than keyword focus may be a hard sell to internal stakeholders because it’s less easily measurable. Generally the way I approach it is to ask folks who they would trust: someone who was a foodie and yet never mentioned the croissants in France or the gelato in Italy, or someone who did. The context we as humans explicitly understand as trustworthy is something that Google and other search engines need to learn and encode, which is why covering a full topic rather than focussing on individual keywords is important – but we can’t report on it for pretty much the same reason: our reporting tools can’t understand context like a human does, so we have to use keywords as a representative measure. I also shift the conversation away from keyword volume to business-led metrics like TAM and SAM.”

3.3. From “Rank on Google” to “Be Cited / Understood in AI Answers”

A major strategic goal change was optimizing content to be:

• Summarizable
• Quotable
• Structured for AI retrieval and synthesis

Common tactics mentioned:

• Direct answers per section
• Definitions, bullets, tables, comparisons
• FAQs + schema as “must-have”
• Proof-led / original data to earn citations
• Clear E-E-A-T signals (authors, tone, freshness)

Why:

Visibility increasingly happens inside AI answers where users may never click—but brands still need to be the referenced source.

About this, Melissa Popp, VP of Content Strategy & Innovation at RicketyRoo, says: 

“This shift feels new only if you were optimizing for rankings instead of comprehension. If your content already answered real questions clearly, cited its sources, and showed who was behind it, AI didn’t change your strategy. It validated it. Teams that focused on being understood, not just indexed, are already ahead. AI pulls from clarity, proof, and credibility. Not tricks.”

3.4. From On-Site SEO Alone to “Search Everywhere” / Multi-Channel Visibility

Many respondents described expanding beyond Google into:

• YouTube, LinkedIn, Reddit, Quora, communities, UGC platforms
• PR, reviews, sponsorships, influencers
• Reputation and sentiment management

This was often framed as “search everywhere optimization” or ecosystem-level SEO.

Why:

AI systems learn from and retrieve from the broader web; mentions and citations across trusted platforms increasingly shape visibility, recall, and sentiment.

Gerry White, independent SEO consultant, says: 

“Today’s consumer journey isn’t a straight line; it’s a hop across platforms, starting with a discovery on TikTok, a deep-dive on YouTube, a query to ChatGPT, and finally a navigational search on Google. Omnichannel SEO is critical because if you only optimise for the final click, you’ve already lost the battle to highlight the brand for the user’s intent. In a world where search is everywhere, our job is to ensure the brand’s ‘entity’ is consistent, authoritative, and present at every single touchpoint, regardless of the app or interface they choose”

3.5. From Traditional KPIs to New Measurement Models

Goal-setting and reporting evolved:

• From clicks/CTR/avg position to impressions, lift, conversions, assisted impact
• From “organic vs referral” to clearer paid vs non-paid, cross-platform visibility
• Adoption of AI visibility metrics and sentiment tracking (mentions/citations)

Why:

Classic SEO metrics no longer fully reflect discovery journeys fragmented across AIOs, AI Mode, and chat interfaces.

About this, Bengü Sarıca Dinçer, SEO Manager at Designmodo, says: 

“Owning presence matters more now because information about brands is coming from all over the web by a growing number of AI features and platforms that keep changing every day. So, people form opinions through social posts, communities, reviews, videos, and conversations with others, often without ever visiting a brand’s website. What’s still underestimated is how much this affects trust. From a user’s perspective, multi-channel visibility is simply how credibility is built.  Looking ahead to 2026, I expect to see a clear split between brands that show up where their audiences already are and those still focused on getting traffic from a single channel. The ones that win won’t just rank better, they’ll feel familiar and reliable.”

Nick LeRoy, Enterprise SEO Consultant and Owner of SEOJobs.com, says: 

“Organic search, historically, has always been treated (and measured) as a performance marketing channel.  In this case, traffic/rankings/impressions were all good SECONDARY metrics but the top KPI always has been (and should always be Revenue/leads). In our new AI focused world, I’ve been pushing for a “KPI+” approach. This means blending concrete data (referral revenue/clicks) with softer secondary KPIs, such as citations and mentions.  Personally, I don’t care about prompts because they’re hyper-personalized and results change every day.”

3.6. Operational Acceleration: Automation, Faster Iteration, Workflow Modernization

Many mentioned:

• Using AI to automate manual work
• Faster testing and iteration
• Better audience research with LLMs
• Report overhauls and tooling investments

Why:

Volatility increased, budgets tightened, and teams needed speed—while still maintaining quality and credibility signals.

4. How did resources for organic search -both traditional and AI search- change in 2025?

The main pattern in 2025 was not resource growth, but resource reallocation. 2025 did not bring more SEO resources, it forced better resource discipline.

Budgets and headcount rarely increased; instead, teams were forced to do less, but do it more deliberately, while absorbing AI experimentation on top of existing SEO work. Organic search resourcing shifted:

• From scaling output to controlling meaning
• From production to judgment
• From rigid roadmaps to adaptive systems
• From traffic growth to sustained visibility and influence

SEO still required ownership and expertise, but it stopped looking like a production line and started behaving like a continuously adaptive system under constraint.

The teams that held or gained trust were those who:

• Ruthlessly prioritized
• Educated stakeholders
• Used AI to eliminate low-value work
• Reinvested time into strategy, clarity, and credibility

Across responses, six consistent shifts emerge.

4. 1. Budgets Were Flat or Down  Especially for Traditional SEO

Most respondents reported:

• Flat or reduced SEO budgets
• Clients diverting spend to AI tools or content automation
• Reduced appetite for long-term SEO investment due to traffic declines and attribution uncertainty

Several noted this as short-sighted, especially where AI visibility still depends on traditional SEO fundamentals.

Where budgets did increase, it was usually for:

• AI tooling / APIs
• Original research
• First-party data
• Selective experimentation

About this, Melissa Popp, VP of Content Strategy & Innovation at RicketyRoo, says: 

“Clients keep chasing whatever looks new and measurable, and too many marketers are letting them. Cutting foundational SEO to fund AI tools feels proactive, but it’s usually just a budget reshuffle that ignores how AI visibility actually works. The teams making smart moves are still investing in fundamentals, then layering AI on top. They’re not treating it like a replacement for the work that made them visible.”

4. 2. Spend Shifted from Volume Production to Quality, Research & Maintenance

A strong reallocation pattern emerged:

Less spend on:

• High-volume content outsourcing
• Generic informational pages
• Broad link-building

More spend on:

• Updating and tightening existing content
• Technical SEO and crawlability
• Digital PR, authority, and trust signals
• Expert input, SME time, and original data

“One strong page replaced five new articles” became a recurring theme.

About this, Melissa Popp, VP of Content Strategy & Innovation at RicketyRoo, says: 

“This isn’t really a pivot. It’s a correction. A single, well-researched page maintained over time does more work than five rushed articles ever did. Teams are finally putting money back into expertise, upkeep, and authority. That’s where durable performance has always come from.”

Nick LeRoy, Enterprise SEO Consultant and Owner of SEOJobs.com, says: 

“Sites that “won” in Google found the perfect balance of quality AND volume.  As we shift to an AI focused search experience, volume provides even less value unless quality standards are met.  The cruel reality is that in 2026, SEO isn’t for everyone anymore. The cruel reality, as I wrote a few weeks ago is that if SEO/AI efforts aren’t time consuming / expensive or high friction, it probably isn’t going to work.”

4. 3. Time Pressure Increased Even When Budgets Didn’t

Even where budgets stayed flat:

• Time investment increased
• SEO teams absorbed:
  • AI learning curves
  • Testing and R&D
  • Client education
  • New reporting and KPI frameworks

AI efficiencies helped automate low-value tasks (proofreading, drafts, analysis), but freed time was reinvested into strategy, research, and judgment, not reduced workload.

4. 4. Support Shifted Toward Cross-Functional & Higher-Skill Roles

Support structures evolved:

Less reliance on:

• Pure “SEO executors”
• Manual production roles

More reliance on:

• Editorial judgment
• Technical SEO
• Data analysis
• Community and off-site contributors
• Product, UX, and engineering collaboration

Hiring shifted toward strategic and expert profiles, as AI automated low-skill execution.

4. 5. Flexibility Increased Out of Necessity, Not Abundance

While budgets were constrained, flexibility improved:

• Shorter planning cycles
• Faster iteration and refreshes
• Rolling roadmaps replacing rigid quarterly plans
• Greater openness to experimentation with AI search

This flexibility was often earned through prioritization, not extra funding.

About this, Gerry White, independent SEO consultant, says: 

“There’s a certain thrill in the fact that the 18-month SEO planning cycle is dead. We’ve been forced into a 6-week reality where agility is our primary currency. I love this shift because it rewards the experts who can interpret data and pivot rapidly over the ones who just follow a static checklist. In today’s market, if your SEO strategy hasn’t evolved in the last two months, you aren’t just standing still, you’re falling behind. The ‘necessity’ of this Flexibility has finally made SEO as dynamic as the technology that powers it.”

4. 6. Measurement Uncertainty Drove Conservative Investment

A recurring tension:

• Harder to prove ROI due to:
  • CTR decline
  • Zero-click search
  • Fragmented discovery across AI tools
• Result:
  • More scrutiny on spend
  • Fewer “big bets”
  • Higher demand for measurable, modular, reversible projects

Some teams struggled with reduced client buy-in, while others gained trust by reframing SEO as visibility, influence, and decision support.

5. How have SEOs adapted measurement and attribution for traditional and AI search after the shifts in 2025?

From click attribution to visibility, influence and decision contribution. The single biggest change in 2025 was abandoning the idea that organic search can still be accurately measured through clicks, rankings, or last-click attribution alone. Measurement became messier, but strategically more honest.

2025 forced SEO to admit what had long been true: organic search is not a click channel; it’s a distributed influence system.

Measurement adapted by:

• Letting go of false precision
• Focusing on visibility, brand, and decision impact
• Accepting fuzzier data in exchange for truer insight
• Measuring patterns, not isolated events

The teams that adapted best were those who stopped asking: “What got the click?” and started asking: “What shaped the decision?”. That mental shift—not any tool—was the real measurement evolution of 2025.

Chris Green, Technical Director at Torque Partnership, says: 

“Tracked AI responses are far less representative of real user experiences than traditional rank tracking ever was, so trying to treat them the same way is a mistake. That said, writing off prompt tracking entirely is short-sighted, especially when clicks and attribution start disappearing and impressions may have already been dismissed as meaningless. The metrics are imperfect, but they still have value when used properly. Right now we are in an education phase, and the tooling landscape is going through a necessary recalibration rather than proving the whole exercise pointless. Directionality of the data is key, education is our core focus now, we need a better-than-working knowledge of these services/tools in order to stay ahead.”

Kevin Indig, Growth Advisor and Writer of Growth Memo, says:

“The measurement section nails the core issue: last-click is now systematically undercounting organic influence, and AI makes the path even darker. The pragmatic move is to treat attribution as triangulation: combine visibility signals (mentions, citations, share of voice) with business outcomes (self-reported attribution) and then validate with periodic lift tests where you can.”

Across responses, seven consistent adaptations stand out.

5. 1. Rankings & Traffic Lost Their Role as Primary KPIs

Most respondents explicitly deprioritized:

• Head-term rank tracking
• Raw organic traffic
• CTR as a success proxy

Instead, rankings are now treated as directional context, not performance truth—especially in crowded SERPs and AI-assisted results.

5. 2. Visibility Became the Core Metric (Especially for AI Search)

A broad shift toward visibility-based measurement emerged, including:

• AI citations and mentions
• Inclusion in AI Overviews and chat answers
• “Share of answer” / “share of model”
• Presence in comparisons, FAQs, and “best of” results
• Frequency and consistency of brand appearance across AI tools

For many, presence itself is the KPI, even when it produces no measurable clicks.

5. 3. Brand Signals Replaced Link-Centric Thinking

Measurement evolved from:

• Backlinks to brand mentions
• Anchor text to branded search lift
• Domain authority to entity recall and sentiment

Branded search, direct traffic, and brand impression growth are now used as proxies for AI-driven discovery and influence.

5. 4. Attribution Shifted Away from Last-Click Models

Respondents widely acknowledged that:

• Last-click attribution now systematically undervalues organic search
• AI search breaks traditional attribution entirely

Common adaptations:

• Assisted and multi-touch attribution
• First-touch discovery credit
• View-through and lift-based models
• Cluster-level attribution instead of keyword-level

Several teams explicitly reframed attribution around decision shaping, not click ownership.

5. 5. Business Impact Metrics Took Priority

Measurement moved closer to the business:

• Qualified traffic over volume
• Conversion quality and rate
• Sales cycle length
• Lead quality
• Revenue influence rather than channel credit

Pages are now judged by whether they:

• Increase branded demand later
• Improve downstream conversion
• Shorten decision time

If not, traffic alone is no longer considered success.

5. 6. Tooling Is Immature, Cross-Checking Is the Norm

Nearly everyone acknowledged:

• AI measurement is still a grey area
• No tool gets it fully right yet
• High cost, low confidence in many platforms

Current reality:

• Manual spot checks + tools
• GA4 + GSC + log files + Cloudflare
• Directional dashboards, not precision analytics
• Heavy client education to manage expectations

Many accepted that perfect attribution is not currently achievable.

5. 7. Qualitative Signals Filled the Gaps

To compensate for missing data, teams added:

• Self-reported attribution (“How did you hear about us?”)
• Sales and support feedback loops
• Monitoring how AI summarizes and frames content
• Tracking whether AI preserves nuance, constraints, and positioning

Measurement expanded beyond numbers into judgment quality.

About this, Jonathan Moore, Technical SEO and Analytics Consultant, says: 

“The survey identifies a new reality where user decisions are increasingly shaped by surfaces that sit upstream of any measurable click. Trust is now being built long before a session is recorded. Yet most organisations are still judging performance through tools and KPIs built for a click-led web. This measurement chasm is widened by prompt tracking, which assumes AI behaves consistently when it does not. The adjustment is to double down on first-party data that can still be measured with relative confidence: combining GA4 and GSC via BigQuery to analyse downstream behaviour and branded demand, and pairing this with qualitative feedback to understand how decisions are being shaped rather than merely where clicks appear.”

6. Which SEO or AI search related tools or features became essential for SEOs workflow in 2025 and why?

The “Core Stack” stayed, AI tools layered on (selectively).  Most respondents did not replace their SEO stack in 2025. Instead, they kept the traditional “source of truth” tools and added AI visibility / automation / research layers where they provided real leverage.

2025 didn’t create one new must-have SEO tool. It created one new must-have capability: understanding and monitoring AI visibility while still relying on first-party data and technical diagnostics.

The “winning” stacks were the ones that:

• Kept GSC/GA4 + crawling as the foundation
• Layered AI visibility tracking where it mattered
• Used LLMs to automate grunt work and scale analysis
• Avoided paying for expensive AI tools that didn’t outperform manual + first-party validation

What “Essential” Meant in 2025

A consistent pattern across answers:

• First-party measurement remained the backbone
• Technical crawling/logs remained the truth serum
• Traditional suites remained necessary for coverage
• AI tools were adopted for visibility/mentions, but mistrust + cost are barriers
• Many found news/learning inputs (industry newsletters, research habits) as important as tools, because the landscape changed faster than software.

About this, MJ Cachón, SEO Consultant and Director at Laika, says:

“In addition to all the traditional and emerging quantitative tools, in these volatile and noisy times, it’s time to go back to the source: people. How? 1. By embracing UX methodologies and delving deeper into user research, focus groups, and surveys. 2. ⁠By adopting CRO methodologies and recording sessions to learn more about user behavior, using the scientific method for testing, etc. 3. ⁠By considering neuromarketing techniques to gain a deeper understanding of consumer behavior and psychology, such as eye-tracking techniques that measure their actual attention span and identify patterns in their behavior on each platform. Many tools are available in disciplines related to SEO that can minimize the noise and give us greater clarity about people and their needs. After all, what is the goal of SEO if not to provide what people need in the best possible way?.”

Geoff Kennedy, SEO & Digital Marketing Consultant, says: 

“It’s reassuring to see the survey confirming that SEOs are still valuing first-party data and haven’t abandoned their base toolset. It feels increasingly easy to get caught up in ‘shiny object syndrome’, especially with the rise of AI tools and the promise of ‘automating everything’. Admittedly, there have been some great developments recently, and AI has brought with it additional needs. But the ability to go back to basics and understand the data behind the tools is still essential, and increasingly getting overlooked by some – this is where good SEOs can shine.”

Across responses, five main “essential tool” buckets emerged.

6.1. The Non-Negotiables: First-Party Google Data

The most consistently “essential” tools were still:

• Google Search Console (performance + indexing diagnostics)
• GA4 (engagement, conversions, assisted impact)
• Looker Studio / dashboards (blending GSC + GA4, cluster monitoring)
• In some cases: BigQuery or more advanced analytics setups

Why: AI and SERP changes reduced click clarity; teams leaned harder on first-party data to understand what was actually happening (impressions vs clicks patterns, landing behavior, assisted conversions, indexing).

6. 2. Technical SEO Workhorses Still Dominated

Widely cited essentials:

• Screaming Frog (audits, indexability, internal linking, diagnostics)
• Ongoing use of crawlers + log analysis (often described as increasingly important)

Why: As visibility got harder, teams doubled down on technical clarity and crawl reality—what bots actually see and access.

6.3. Enterprise SEO Suites Stayed Central, Now With “AI Modules”

Most frequently mentioned platforms:

• Semrush (including AIO trackers / AI features)
• Ahrefs
• Sistrix
• seoClarity / Wincher / SERanking 
• Bing Webmaster Tools (in some workflows)

Why: These tools remained useful for:

• Monitoring trend shifts and SERP feature changes
• Diagnosing volatility
• Mapping where AI features dominate and where not to compete
• Baseline visibility tracking when attribution is messy

But the tone was consistent: they’re still necessary, not always loved—and AI add-ons are still maturing.

6.4. AI Visibility / Brand Mention Tracking Became the New Layer

Tools and approaches mentioned:

• Peec AI, Waikay, Gumshoe, Rankscale, AccuRanker AI tracking, “LLM brand monitors”
• Proprietary/internal tools that convert queries into prompts and audit what chatbots say
• Manual checking across ChatGPT, Gemini, Perplexity, plus prompt-set runners

Why: Many teams accepted that AI surfaces often drive little to no measurable traffic, so the essential measurement became:

• mentions/citations
• “share of answer / share of model”
• brand inclusion and framing inside AI outputs
• competitor framing comparisons

6.5. AI Assistants + Automation Became Workflow Infrastructure

Frequently referenced:

• ChatGPT / Claude / Gemini / AI Studio / NotebookLM
• Automation tools (e.g., n8n, workflow automation, “vibe coding” internal tools)
• LLM APIs + light coding to run audits at scale

Used for:

• Audience research and context documents
• Bulk analysis (logs, content audits, opportunity analysis)
• Content operations (briefs, outlines, refreshes, ALT text) with human QA
• Turning internal ideas into small internal tools, replacing slow manual work

Why: AI’s biggest immediate impact was speed and scale of analysis/ops, not “auto-SEO.”

7. How do SEOs expect traditional search to evolve in 2026?

Traditional Search” Becomes a Hybrid Layer: Fewer Clicks, More AI, More Brand Bias. In 2026, “traditional search” is expected to narrow in role but increase in importance at the moment of commitment.

• AI shapes the first answer and compresses the funnel
• Traditional organic results become the trust infrastructure: validation, comparison, and transaction support
• Winning shifts from “rank #1 for a keyword” to “be the trusted entity users and systems rely on when the decision matters.”

The main expectation is that 2026 “traditional search” will look less like 10 blue links and more like a hybrid experience where AI layers mediate discovery, and classic organic results act as validation, depth, and transaction infrastructure.

Across responses, seven themes repeat.

7.1. More AI in the SERP (AI Mode / AI Overviews Expand)

Most respondents expect:

• AI Overviews to expand to more queries
• AI Mode-style experiences to become more prominent (some predict default or near-default)
• A further blend where it becomes hard to distinguish “AI search” from “traditional search”

Net: the SERP becomes more answer-first and more conversational.

7.2. Fewer Organic Clicks, Especially for Informational Queries

A very consistent prediction:

• CTR continues to decline
• Informational queries are increasingly answered in-line
• “Impressions up, clicks down” becomes even more common

Several also expect ads to move deeper into AI experiences, increasing the click squeeze further.

7. 3. Organic Shifts Down the Funnel: Verification, Comparison, Transactions

Many respondents described a role change:

• AI handles discovery + synthesis
• Traditional search becomes the place users go to confirm, compare, and commit

Expected query patterns:

• “compare X vs Y”
• “is this accurate?”
• “sources”
• “edge cases”
• “best option for my situation”
• transactional and navigational intent

In short: organic becomes decision validation, not first-touch discovery.

7. 4. Stronger Emphasis on Brands, Entities, and Real-World Credibility

A repeated expectation:

• Search becomes more brand-biased/selective
• Entities become the retrieval unit more than keywords
• The winners are brands with:
  • consistent messaging
  • clear expertise
  • trust signals beyond the site

Multiple answers explicitly predicted:

• E-E-A-T enforcement increasing, becoming more systemic
• thin, generic, or anonymous content losing durability

7. 5. More SERP Features + Multimodal + Social Integration

Respondents anticipate:

• more rich results and interactive elements
• more multimodal journeys (voice, images, uploads)
• increasing visibility of social and video content in SERPs (short video surfaces were cited)

Publishers in particular expect:

• shrinking/transforming SERP features like Top Stories
• greater need for distribution beyond the SERP

About this, Myriam Jessier, SEO & Technical Brand Visibility Consultant, says:

“Search is a behavior, not a platform. Multimodal search aligns more naturally with the way humans search: we can show a “thing”, talk and type questions all in one query. This means that you have to design for a context, not for a full experience the way we used to. AI infers context, such as price point and target audience, from the objects in each frame of a video. It can read the packaging of a product when a user snaps a photo to ask a question before deciding to buy.”

7. 6. Data / Index / Retrieval Models Evolve (Less Reliance on Classic Index)

A minority but notable view:

• retrieval improves
• systems become less dependent on the classic index alone
• traditional search may evolve into “deep research” or “verified experience” mode

Some referenced experimental directions like Web Guides as a possible signal of how this hybrid SERP could look.

7. 7. The Industry Response: Some Give Up, Strong Teams Double Down

Several answers noted a market dynamic: some sites/teams will reduce SEO investment due to declining clicks. But “smart” organizations will double down, focusing on: quality, trust, technical excellence, brand authority, mid/bottom funnel performance.

8. How do SEOs expect AI search to evolve in 2026?

AI Search Shifts from “Answer Engines” to “Action + Monetization Layers”. The dominant expectation is that AI search in 2026 becomes more integrated, more transactional, more personalized, and more heavily monetized; while also being forced to improve trust, grounding, and measurement.

In 2026, AI search is expected to become a decision-and-action layer:

• It will recommend, justify, and increasingly execute
• It will monetize aggressively (ads, commerce, commissions)
• It will be forced to improve trust (citations, safeguards, YMYL controls)
• Visibility shifts further from “rank + click” to eligibility, authority, and repeated reference across the web

In short: AI search becomes less like a search box and more like a guided operating system for decisions.

Several respondents predict increased competition and potential shifts in leadership:

• Some expect Google/Gemini to gain due to indexing infrastructure
• Others expect multiple players to coexist (ChatGPT, Perplexity, etc.)
• A minority expect a “bubble pop” or retrenchment if economics don’t work—but most expect continued growth.

About this, Yordan Dimitrov, SEO Manager at Reflect Digital, says: 

“SEO is far from dead; it is, in fact, evolving at a rapid pace. However, our approach to AI search needs to adapt to those changes in both technology and user behaviour shifts which come with it. In the discovery stage, users are now getting answers without having to click through to a website, which makes click-based metrics less reliable. The modern consumer journey is non-linear, meaning that we need to have our brand present across various platforms where our target audience is. Furthermore, we need to ensure that our websites are prepared for agentic browsers, so that we can cater for both humans and AI agents alike, offering a seamless journey and helping aid conversions.”

Cindy Krum, CEO and Founder of MobileMoxie, says: 

“The growth of AI integrations in search will push SEOs to start optimize earlier in the search funnel. Since most AI utilities are using a set group of platforms to mine information from, SEOs will begin to focus on getting content to rank well in search in those platforms, so that it can be picked up by the AI searches. Since rank-tracking with AI is hard, rank tracking tools may also shift to tracking rank in these up-stream sources. I also think that we will start seeing more visual and interactive assets in the AI results. Some will be cited assets, and some will be AI generated assets, like the Google turkey recipe that got so much attention for US Thanksgiving. More images, videos and maybe even interactive graphs, maps and mini-utilities. MUM was all about connecting textual understanding with multi-modal understanding, to answer questions more comprehensively, but the AI results still include a lot of text. Google wants users to like the results and stay in the results, so they will do it by making them more visual and interactive.”

Steve Toth, CEO at Notebook Agency and creator of the Trust Alignment Framework, says: 

“Up until now, Answer Engine Optimization has lived almost exclusively in the SEO line item, which made sense since SEOs were the ones who spotted the shift first and began experimenting. As broader marketing organizations start paying attention to how LLMs affect their performance, budgets will begin to flow in from new places in 2026. PR teams will realize that LLM representation is now part of their KPIs. Sales leaders will begin to realize that a poor AI recommendation can kill deals before they even start, and they will demand help. Brand teams have already begun to acknowledge that what ChatGPT says about you is as important as the copy on the website. SEOs have the opportunity to guide their orgs and clients into a new cross-disciplinary function and, in doing so, discover new ways to measure success beyond brand-mention tracking. The question that matters is not just ‘are we mentioned?’ but ‘are we being recommended when customers ask dealbreaker questions that influence buying decisions?’ The next phase of Answer Engine Optimization will not be owned by a single team. It will sit at the intersection of SEO, PR, brand, and sales, because that is where buying decisions are now being shaped. The SEOs who step up will not just report on visibility. They will help define what “good” looks like in AI answers, align teams around it, and turn LLM behavior into a more measurable growth lever.”

Across responses, eight themes repeat.

8.1. Deeper Integration Into Google and “Traditional” Search Journeys

Many expect AI to become an invisible default layer:

• AI integrated more tightly into Google results
• Interfaces blending AI + classic links more seamlessly
• Users increasingly “don’t notice the boundary” between AI and search

8.2. From Answering to Doing: Agentic, Task-Oriented Search

A major predicted shift:

• AI moves beyond summarizing to executing tasks
• Multi-step flows inside the AI interface:
  • compare, shortlist, book, buy
  • connect to calendar/email/apps
  • guided journeys rather than one-off queries

Implication: funnel compression accelerates; fewer website visits are required to convert.

8.3. More Transactional + Commerce-Native Experiences

Many expect:

• Shopping embedded directly in LLMs and AI interfaces
• AI Overviews triggering more on transactional queries
• Growth of “agentic e-commerce” with inventory/APIs becoming key inputs

Several explicitly predict an “SEM equivalent” for AI search: ads + commerce rollouts inside AI.

8.4. Monetization Becomes a Big (and Disruptive) Story

Repeated expectations:

• More ads in AI experiences
• New ad formats
• Commission/affiliate-style models and paid placements
• Marketing mix and measurement complexity increasing as spend follows inventory

Some anticipate user pushback once ads expand, but still expect monetization to drive platform behavior.

8.5. Trust, Grounding, and YMYL Safeguards Increase

A strong theme: AI search must get safer and more reliable:

• Better citations and provenance
• Stronger quality filters
• More reliance on trusted sources for YMYL (finance/health/legal)
• Pressure (legal, reputational, competitive) to reduce hallucinations

Many believe AI will adopt more “search-like” algorithmic safeguards to resist misinformation and manipulation.

8.6. Spam, Manipulation, and a “Quality Arms Race”

Multiple respondents expect:

• Heavy gaming/spam attempts in AI answers
• Brands pushing “fake” tactics until platforms clamp down
• A move toward ranking-like systems or quality thresholds

Net: a familiar cycle—growth, exploitation, then enforcement.

8.7. Personalization Becomes Contextual and Situational

Many expect AI search to be:

• More personalized
• More thread-based (ongoing intent, not isolated queries)
• More device-integrated (multimodal: text, image, video, audio; possibly wearables)

This implies different users asking the “same” question may get meaningfully different answers.

8.8. Measurement Improves (Because Money Requires It)

A recurring hope/prediction:

• AI platforms will expose more tracking and analytics (mentions to conversions)
• Not necessarily for SEOs, but because advertisers and enterprises will demand it
• New metrics emerge: share of model/answer, citations, influence, conversion assist

About this, Andrea Volpini, Co-founder and CEO at Wordlift, says: 

“The survey captures the real change in 2025: discovery is being compressed, so the battle moved from rankings to visibility, attribution, and trust. This is why a context graph matters. When clicks fade as the primary signal, what counts is repeated reference, provenance, and machine-readable entities that systems can reliably reuse. In 2026, AI will move from synthesis to action. Agents will book, buy, and plan on our behalf, so brands need infrastructure that makes their knowledge callable, not only crawlable.”

Crystal Carter, Head of AI Search & SEO Communications at Wix, says: 

“I expect AI agents to drive, further and faster diversification of the search and brand discovery in 2026. In the last year search professionals have been very invested in being more visible in AI answers via ‘GEO’ but we are now seeing Gemini, OpenAI, other AI platforms, brands and CMSs, become directly involved with agentic solutions for purchases and transactions.This means making them intuitive, frictionless, integrated parts of the user journey. From agentic browsers to personal agents, marketers should prepare for this new user group.”

9. What’s the most important action SEOs are planning to take in 2026 to win in organic search (traditional and AI search)?

Build a Brand + Authority Moat, Engineer Citation-Ready Content, and Reframe SEO as Cross-Channel “Findability”. 

The 2026 playbook respondents are converging on is:

• Win trust, not just rankings
• Be the cited, remembered entity across platforms
• Publish less, but make it structurally and evidentially stronger
• Treat SEO as a cross-channel system tied to business outcomes
• Use better measurement to sustain investment through the click squeeze

About this, Jono Alderson, SEO consultant, says:

“I’m excited to see us explicitly expanding our remit to include proactive, positive reputation management across a wider set of surfaces. People have always formed opinions based on what they see, hear, and read outside the SERP. We’ve largely ignored that reality because it was messy to measure and hard to operationalise. Now, if we care about ‘ranking’ in any meaningful sense, we have to shape how brands, products, and services show up across the whole web, not just on our own domains. That means spending less energy on producing on-site content and link building, and more focus on actual marketing: influence, visibility, credibility, and demand. Brands that get this right, while also competing on technology and platform fundamentals, will win. Those that don’t will keep producing content that technically ranks, but increasingly fails to matter.”

Yagmur Simsek, SEO Consultant and Founder of “Search ‘n Stuff”, says: 

“This confirms what I’ve been seeing in real work for a while now: SEO in 2026 isn’t about winning rankings, it’s about winning trust. AI didn’t kill SEO, it exposed weak brands. If you’re not being mentioned, cited, or remembered outside your own website, technical excellence alone won’t carry you in an answer-first world. What resonates most for me is the shift toward brand, community, and citation-ready content. The strongest results I’ve seen come from treating SEO as cross-channel findability: aligning content, PR, product, social, and real human conversations. That’s where authority actually compounds. Publishing less but standing firmly behind every page, with experience, evidence, and a clear point of view, is the real upgrade. Communities amplify what they trust, and AI follows those signals. 2026 won’t reward who scales fastest. It’ll reward brands people recognise, reference, and recommend, even when no click happens.”

Across responses, the “one most important action” clusters into six dominant priorities.

9.1. Double Down on SEO While Others Pull Back

A notable mindset: competitors will quit; winners will persist.

• “Work harder/smarter”
• Stay current, keep learning, keep testing
• Treat volatility and change as an advantage for disciplined teams

Why: fewer serious competitors + higher bar = opportunity for those who keep investing.

9.2. Brand Building + Mentions/Citations as the Core Growth Lever

The most repeated single priority:

• Build brand authority that travels across platforms
• Increase mentions and citations (often via PR, thought leadership, influencers, UGC, community)

Many explicitly framed 2026 as: “there’s a new flywheel: brand.”

9.3. Create “Citation-Ready” / Answer-First Content with Strong E-E-A-T

A very common concrete action:

• Restructure content to be easily extracted/summarized:
  • clear definitions, summaries, tables, FAQs
  • evidence, comparisons, original data
  • schema + internal linking + entity clarity
• Build fewer, stronger pages instead of scaling output

Goal shift: from ranking/clicks to being the trusted source included in AI answers.

About this, Arsen Rabinovich, Founder & President at Top Hat Rank, says:   

“Unique perspective is the moat right now, for both organic rankings and AI Overviews. If your page is mostly a procedural rewrite of what already exists, it is interchangeable. Interchangeable content gets summarized, not cited. The goal is to make the page a source. Add firsthand experience, specific examples, real tradeoffs, and what you learned doing it. Show proof on the page, not just opinions. That is what makes the content feel credible, aligns with E-E-A-T, and increases the odds it gets picked up and referenced in AI answers. The play is fewer “me too” pages and more pages that are built to be referenced. Clear structure, direct answers, and evidence that only you can provide.”

9.4. Expand Beyond SEO: Multi-Platform / Omnichannel Search Strategy

Many described the key action as:

• Making SEO a company-wide, cross-team system
• Aligning with product, content, PR, social, support, CRO/UX
• Optimizing for discovery across Google, AI tools, and social/community platforms

This includes “search everywhere” execution and change management with leadership/CEOs.

9.5. Improve Measurement: Lift-Based, Business-First KPIs

A repeated action is to fix what success means:

• Move away from vanity metrics (pageviews, head-term rankings)
• Focus on:
  • lead quality, conversions, assisted impact
  • lift-based measurement
  • attribution models that reflect multi-touch journeys

Several explicitly said measurement education is the lever for continued buy-in.

9.6. Harden Foundations: Technical SEO, UX/CRO, and “Lean Sites”

A persistent tactical focus:

• Technical cleanup for crawl efficiency + structured data
• Logfiles/bot behavior monitoring
• UX/CRO improvements as competitive differentiators
• “Clean house” and make sites lean, consistent, and fast

About this, Amanda King, SEO, Growth Consultant and Founder at Floq, says: 

“We’ve been coasting on “good enough” for the technical foundations of our websites for at least the last five years because we were confident Google could connect enough of the dots to be able to fully read the website and understand it. LLM’s aren’t at that point. They’re much stricter. Much more black-and-white. Much more yes or no — particularly for agentic search. Which means we’re really going to have to get back to the basics and make sure we’re hitting all the correct compliance, that we don’t have deprecated or vulnerable JavaScript (or maybe that we use less JavaScript at all), etc. etc. I imagine we’ll be having a lot more conversations in the coming years with our developers around managing and clearing tech debt. Which is absolutely a good thing, and something we’ll want to account for in our planning as agentic search grows.”

Long-Tail Actions Mentioned

• More video content and stronger multi-format distribution
• Audience research (customer service, reviews, user language)
• Fan-out / query expansion content strategies
• Integrating paid + organic (AI ads experimentation)
• Building proprietary data “moats” (original studies, interviews, case studies)
• Community-led “un-AI-able” experiences (podcasts, communities, real human content)

About this, Carolyn Shelby, SEO Consultant & Principal SEO and Strategic Advisor at Yoast, says: 

“SEO in 2026 requires stronger systems thinking. Practitioners need to understand how information architecture, entities, content relationships, and technical signals work together across an entire site (*and how they support or advance the overall business goals!*) not just how to optimize individual URLs.”

10. When do SEOs expect Google to release AI Mode as a default search experience for users? 

Respondents don’t expect a single “flip the switch” moment. The dominant view is a gradual, segmented rollout where AI Mode becomes the default for some query types, users, or regions first—while classic/hybrid SERPs remain for high-commercial or high-risk queries.

Most respondents expect Google to normalize AI answers quietly through deeper blending and query-based defaults, then relabel that reality as “default”—with 2026 as the most likely inflection year, but full universal default (if ever) pushed to 2027+ due to monetization, trust, and risk.

10.1. What timeline respondents predict

10.1.1. Never / unlikely to be the default

A meaningful group says “never” (or “not as AI Mode as we know it”), arguing:

• Users won’t want it by default
• It’s too disruptive
• It’s hard to monetize without harming ad performance
• Google will prefer a blended “Web Guides / Web Mode / hybrid” default instead of a pure AI Mode tab

10.1.2. Mid–late 2026 is the most common prediction

The most frequent answer window is sometime in 2026, with many clustering around:

• H1 2026 (some saying “6 months,” “early next year,” “before summer”)
• Q2–Q3 2026 (often cited as a realistic “default-by-segments” moment)
• Late 2026 (often framed as when it becomes the “standard” experience publicly)

10.1.3. 2027+ for a full default

Another sizable group thinks well into 2027, mainly due to:

• Monetization still unproven for LLM-style interfaces
• Trust/quality and legal risk not “boring enough” yet
• Regulatory and publisher pressure still unresolved

About this, Amanda King, SEO, Growth Consultant and Founder at Floq, says: 

“A full default to AI mode is going to take time for a few reasons – first off, as we’ve said, there is less uptake for AI/LLM search than we like to think there is, so it’s an entirely new way of search folks will have to get used to, and that takes time. Second, I think implementing (fully) a new processing mode like Muvera to make AI search less expensive and generally take up less space I think will still take time.”

10.2. The “why” behind the predictions (recurring reasons)

10.2.1. Monetization is the gating factor

By far the most repeated constraint:

• AI Mode becomes default when Google can protect or improve PPC economics
• Respondents repeatedly tied the switch to ads + shopping/product feeds being integrated cleanly

10.2.2. Cost and unit economics

Some explicitly point to inference cost and scalability:

• AI Mode is expensive, so Google will default it only where it’s “worth it”

10.2.3. User trust + backlash risk

Many expect resistance if users must “opt out”:

• Google needs higher trust, fewer errors, and a smoother UX
• Expect testing before wider defaulting

10.2.4. Legal/regulatory/publisher risk

Frequently mentioned:

• YMYL and misinformation liability
• Attribution and market impact concerns
• Publisher ecosystem fallout (especially for media sites)

10.2.5. Default by query class, not globally

A very common “best prediction” structure:

• AI Mode default for informational/exploratory/deep research
• Hybrid/classic SERPs remain default for navigational and transactional queries (where ads and clicks are critical)

11. What’s something SEOs wish Google and Bing addressed, improved or changed in traditional search in 2026?

Respondents mainly want search engines to stop forcing everyone to operate blind: separate AI vs traditional performance clearly, reduce SERP clutter/ads, reward original creators, and provide transparent diagnostics that make optimization and ROI defensible.

About this, Alex Moss, Principal SEO at Yoast, Director of FireCask, says: 

“Measurement and success metrics will continue to be covered in smoke and mirrors as we navigate changes in search behaviour. This is difficult not only because these behavioural shifts make our native metrics less accurate and change the value of the metrics themselves, but also because the search platforms still seem nowhere near providing a direct solution for us, beyond adding a little more insight into Google Search Console and Bing Webmaster Tools. Until this happens, we will have to rely more on third-party tools to provide relatable value. However, fear not. Whilst we have less accurate attributable data to provide to stakeholders, we must use third-party platforms to enrich what we can, and focus on how we communicate that value. SEO itself is proving to be of more value to businesses, and it is part of our role to ensure this is illustrated properly.”

11.1. Much better transparency + reporting (the #1 request)

The most common ask is to end the “black box,” especially now that AI features and zero-click are expanding. Respondents repeatedly want:

• Clearer why something ranks / drops (at least directional signals)
• Clear separation in tooling (GSC/Bing Webmaster Tools/GA4) between:
  • traditional organic vs AI Overviews / AI Mode / generative surfaces
  • impressions, clicks, citations, and referral data
• Better diagnostics for sitewide quality issues (not vague guidance)

In short: “Show us the data” and make it usable.

11.2. Dedicated AI feature measurement in GSC/BWT

A very specific, repeated request:

• Add AI Overview / AI Mode metrics directly into Search Console / Bing Webmaster Tools
• Provide citation click data, visibility, and position evolution for AI features
• Fix the messy/unclear attribution of LLM traffic in analytics (GA4 is called out often)

11.3. Reduce ad dominance and improve SERP layout

Many want a rebalance of the results page:

• Fewer ads (especially above the fold)
• Clearer ad labeling (ads looking like organic is a trust issue)
• Ads moved aside / less real-estate takeover
• Less “forced” paid behavior (e.g., broad match frustrations)

11.4. Reward original creators; fight plagiarism, spam, and parasites

A strong theme is quality enforcement:

• More visibility for original content producers
• Less room for republishers/plagiarists
• Better spam/parasite SEO control and de-duplication
• Cleaner, more trustworthy local results (less spam wiping out real businesses)

11.5. Fix the “value exchange” for AI answers

Several respondents framed AI features as breaking the publisher contract:

• If engines use site content to answer directly, publishers want:
  • better attribution/visibility, and/or
  • compensation or a fairer trade (data/ROI clarity at minimum)
• Some explicitly want AI Overviews removed (even if they think it won’t happen)

11.6. User control over AI features

A recurring user-centric request: Ability to opt out / hide AI-powered features (AIO, AI Mode tab), at least for some users or contexts.

11.7. Better intent understanding + richer multi-format integration

A smaller but thoughtful set of asks:

• Better understanding of intent depth (beginner vs practitioner vs strategist)
• More proactive clarification for ambiguous queries
• Stronger integration of video/audio/visual content with semantic understanding (transcripts, multimodal blending)

12. What’s something SEOs wish AI search platforms addressed, improved or changed in 2026?

Respondents want AI search to mature from “confident answers” into a measurable, citable, correctable, and accountable discovery system, where publishers/brands can track impact, users can trust what they see, and platforms resist spam while being transparent about sources and uncertainty.

About this, Estela Franco, Web Performance and Technical SEO consultant”, says: 

“The biggest challenge companies face today in AI Search is shifting the mindset of traditional SEO toward a more strategic goal: becoming the reference source that AIs recognize and replicate for their core knowledge or expertise. Being cited by an AI does not guarantee you are truly a source. What matters is that your conceptual framework, definitions, and way of explaining a topic are consolidated and reproduced. Prompt-tracking tools may create the illusion of control, but they are rarely aligned with this goal, and many companies end up chasing metrics that do not reflect real authority. Looking ahead to 2026, I expect AI platforms to provide new metrics and insights that finally give us (some) clarity on influence and citations”. 

The dominant request is platform-native measurement, comparable to GSC/Bing Webmaster Tools:

• Visibility into what users asked (prompt/query themes + volume)
• How/when brands and pages were mentioned/cited
• Better referral instrumentation (e.g., consistent UTM/referrer tagging)
• Reporting that’s affordable and reliable (many call current tools expensive and/or noisy)

12.2. Stronger source transparency + consistent citations

Respondents want citations to be:

• Clear, in-line, easy to click (not hidden UI)
• More consistent across platforms (some ask for a standardized citations protocol)
• Explicit about which parts of an answer come from which sources
• Better at distinguishing authoritative sources vs unverified UGC

12.3. Fewer hallucinations + clearer confidence / “what’s fact vs synthesis”

A major theme is trust:

• Reduce hallucinations and misrepresentation
• Add clearer indicators of certainty, assumptions, and grounding
• Better safeguards for YMYL topics (health/finance/legal), including transparency on how safety is handled

12.4. Creator/publisher fairness and control

Many want a healthier ecosystem:

• Better attribution for publishers/creators
• Some form of compensation or fair value exchange for summarized/scraped content
• More control/feedback loops for brands and publishers (e.g., opt-in/opt-out, visibility into reuse)

12.5. Entity correction workflows (“claim your entity”)

A repeated operational pain:

• A way for verified brands to see what the model “believes”, flag wrong info, fix geo-drift, and submit “source of truth” URLs.

12.6. Spam resistance + quality filters

Respondents expect AI search to be increasingly gamed and want:

• Algorithmic anti-spam measures (“AI Florida update” style)
• Less manipulation via low-quality citations/listicles
• More emphasis on first-hand expertise and durable trust signals

12.7. Better product direction and UX behaviors

Smaller but recurring asks:

• Less “sycophantic” agreement; more neutral, critical behavior
• Better intent clarification (ask follow-ups when ambiguous)
• Personalization controls and privacy transparency
• Freshness signals/timestamps and better recency handling
• Encourage deeper exploration (recommend visiting sources for depth)

13. What new skills or capabilities do SEOs believe they will need the most in 2026 and why?

In 2026, the SEOs who win won’t be the ones who just “know the latest tactic,” but the ones who can operate across a messier, AI-mediated discovery journey.

That means combining real AI/LLM literacy with stronger technical and data skills, structuring content for entity understanding and citation readiness, and proving impact through first-party measurement that goes beyond clicks.

Just as importantly, SEO becomes more cross-functional: brand, digital PR, UX/CRO, product, and social signals increasingly shape visibility, so communication, stakeholder education, and an experimentation mindset are no longer “nice to have”—they’re core to the job.

Judith Lewis, SEO Consultant and Founder at Decabbit Consultancy, says: 

“Reporting on things that make a real difference to the client/boss/business is more important than ever. I sometimes worry that we have gotten too complacent reporting on rankings without really thinking about the why behind it. Rankings relate to clicks, which relate to conversions/leads, which relate to revenue. Instead of just reporting on rankings, which we won’t have for AI, report on your positive impact on the business. Reporting on keywords is complex and only part of the story now with prompts and conversational queries.We need to refocus on building brands and becoming recognised for specific expertise – something I’ve been speaking at conferences about for over a decade. SEO isn’t just non-branded keyword rankings anymore – we need to think about the full digital marketing suite and how we compliment each one and can work synergistically with them to boost positive brand awareness and visibility.”

Emina Demiri-Watson, Head of Digital Marketing at Vixen Digital, says:

“The other quiet pressure point that’s great to see mentioned here is UX and CRO. It will be interesting to see if and how the importance of it changes in next year’s survey, considering the move towards agentic systems.  Humans might tolerate friction, agents won’t. If agentic behaviour accelerates, UX and CRO stop being differentiators and become table stakes. There’s far less forgiveness built into these systems. As a human you might tolerate friction in an ecommerce purchase journey. You’ll try again because you might love the brand or want that specific product. An agent is there to complete the task. The intent is far less simple and friction tolerance far lower because of it. And, when crawling is expensive and at a premium, a few of these failed completion might just be enough for a system to quietly deprioritise you altogether.”

Let’s go through each:

13.1. AI/LLM literacy (beyond buzzwords)

A working understanding of how LLMs generate answers, their limits, and how visibility happens in AI surfaces. This includes things like query/prompt simulation, “fan-out” thinking, and AEO/GEO fundamentals—so SEOs can optimize for selection/citation, not just rankings.

13.2. Measurement, analytics, and “business proof”

Better data literacy to move beyond vanity metrics:

• first-party analytics, attribution nuances, assisted conversions
• dashboards, segmentation, interpreting noisy signals
• turning analysis into a clear business narrative for leadership

13.3. Technical + data capabilities (more “engineering-adjacent”)

Stronger technical SEO remains a separator: crawl behavior, internal architecture, indexing, logs, structured data/schema. Many also expect more comfort with APIs, automation, Python/ML basics and workflow building.

About these results, Will Kennard, Digital Marketer and Director at Very Good Digital, says: 

“The need for technical SEO is only going to grow as the pace of implementation increases from AI tools such as Cursor assisting developers. Technical SEOs will need to understand development subjects like framework specific nuances & development pipelines more deeply so they can work closer than ever with developers. Using AI tools to crate briefs with code examples for devs can be extremely helpful – and understanding code is more important than ever.”

13.4. Content structuring for machines + entities

Not just writing content, but structuring it so systems can extract and trust it:

• entity-first content design, internal consistency, “citation-ready” clarity
• E-E-A-T/real expertise signals
• original insights/data to avoid commodity content

13.5. Brand, Digital PR, and storytelling

As generic content gets commoditized, respondents emphasize:

• brand building, narrative, trust, and reputation signals
• digital PR/earned media and community/influencer citations
• human creativity and point of view as differentiation

13.6. Cross-functional collaboration and full-stack mindset

SEOs need to work effectively with product, dev, UX/CRO, PR, social, paid—because organic outcomes are now shaped across the whole journey, not just “SEO work.”

13.7. Soft skills for volatility

Repeatedly mentioned: adaptability, experimentation, critical thinking (filter hype), resilience/patience, and especially communication/education to calm stakeholders and align decisions.

13.8. Multimodal skills

Some call out capability in video creation/editing (short-form), plus understanding how content appears across social-heavy SERPs and multimodal AI experiences.

Wrapping Up: Organic search isn’t collapsing, it’s fragmenting and maturing.

In 2025, AI didn’t “replace” SEO; it compressed early discovery and moved a chunk of influence upstream, while traditional search became the validation and decision layer closer to conversion.

That’s why the winning approach going into 2026 looks less like chasing rankings at scale and more like building durable eligibility: a clearly understood entity and brand across the web, content that’s structurally easy to extract and trust (evidence-led, citation-ready, technically clean), and a measurement model that reflects influence and assisted impact—not just clicks.

In short: fewer shortcuts, more fundamentals, and a broader “search everywhere” remit where PR, community, UX, and first-party data are now part of the SEO job if you want to stay competitive.

About this, John Shehata CEO and Founder of NewzDash, GDdash, and NESS.

“AI search didn’t replace SEO; it exposed what SEO has always been: sustained trust and entity authority. For publishers, Discover, Top Stories, and AI Overviews are just different doors into the same building. When a site loses credibility signals in Search, it usually shows up everywhere: weaker Discover performance, less Top Stories stability, and fewer opportunities to be cited in AI answers. That’s why the winners in 2026 won’t be the teams chasing prompts or rebranding SEO into new acronyms. They’ll be the teams engineering trust at scale and across surfaces: real-time visibility feedback loops, clear entity signals, strong authorship, original reporting, unique data, and content that’s structured to be summarized and cited accurately. Engineering trust across surfaces also requires a mindset shift. The biggest SEO mistake has been treating “Search” like a single channel, instead of treating search as a behavior that happens everywhere. Users search in Google, in YouTube, in social feeds, in forums, and now inside AI platforms, often in different formats and with different intent at each step. Content and data have always been the product, our job as SEOs is to connect that product to a qualified audience in the right format, on the right surface, at the right moment. In 2026, that means optimizing for visibility and understanding across every surface that matters to your audience, not just the ten blue links. And we’ve seen this movie before. Marketers and CEOs chase the shiny new channel, budgets shift fast, vanity metrics become KPIs, and SEO gets declared “dead” all over again. We saw it during the social-first budget wave in the mid-2010s. The lesson from 20 years of SEO is not to minimize the moment, AI is real and it’s changing discovery, but to avoid the panic pivot. Fundamentals still compound, and now they matter across more surfaces than ever.”

Dawn Anderson, International SEO Consultant and Managing Director at Bertey, says: 

“As we move forward into 2026 it is clear the mask is removed on the initial charade of AI Search and GEO as a separate discipline to SEO, and hopefully, we are setting down to a new, yet improved and exciting, stage of ‘Business As Usual’.  SEO is merely evolving as it always has, and this is yet another layer or morphism of our trade, although we are possibly in our steepest learning curve ever as an industry.  Nothing here is saying that search has not changed.  It has. But it is always changing, and change must be embraced, with adaptation as necessary. Last year at SEOFOMO London Meetup the panel discussed the changes coming and I noted the complete paradigm shift and whole system rebuild which generative information retrieval represented, requiring some recalibrating and re-educating for SEOs to go through.  It is interesting to see that the trends survey illustrates there is concern that some will simply give up on SEO as ‘too difficult’, and this was touched on in my comments at SEOFOMO London.  However, we have been here before with both Penguin and Panda and we must persist.  Many left SEO in those days, but the resilient ones remained and this is happening once more, but on a larger scale.  The recalibration will continue into 2026 but we should all be a step closer to understanding what these changes truly mean for search professionals, which is still boundless opportunity across a digital channel spectrum, with SEO playing a key role and additional surfaces to optimise for, plus a potentially longer, multi-point, multi-discipline digital decision-making journey.  The data points to more searches rather than fewer, and whilst many will be deemed to be within a ‘walled garden’ of SERPs, this largely constitutes query refinement processes with a final, more qualified click.  It will be interesting to see conversion data studies combined with SEO into 2026 and beyond since we do not see enough of these.”

Tory Gray, CEO & Founder at The Gray Dot Company, says: 

“2025 brought meaningful change to SEO, and that pace of evolution isn’t slowing in 2026. That said, some clear patterns are starting to take shape: 1) Search behavior has been expanding beyond “just Google” for quite some time. People discover information across many platforms and tools, and – as an industry – our measurement approaches and strategies need to evolve to reflect how audiences actually behave. 2) Brand awareness is becoming increasingly important. As AI Overviews reduce top-of-funnel clicks, brands have fewer opportunities to show up and positively influence early-stage decision-making through search alone. Investing in brand visibility growth helps fill that gap. 3) Visibility in LLMs builds on familiar foundations. No matter what we call it, success draws from both established SEO best practices and coordinated, multi-channel marketing. Collaboration across teams has never been more important. 4) Change will continue—but so will our understanding. As SEOs learn more about how LLM visibility works, and as these tools evolve to address quality and spam concerns, strategies will continue to adapt alongside them. 2026 is shaping up to be an exciting year!”

Garrett Sussman, Director of Marketing at iPullRank, says: 

“When it comes to AI Search, SEO, and user behavior in 2026, the default is not changing. Google is still the default search engine. People are using other channels to search, and that matters, but Google still owns close to 90 percent of the market. Reddit, TikTok, and ChatGPT continue to grow as discovery surfaces, and ignoring them puts you in a bubble. At the same time, whatever Google does still ripples across the entire SEO industry. As long as Google remains the primary gateway, its decisions shape how search works everywhere else. Personalization adds another layer of complexity. As people get more familiar with conversational search, the shift is not just about AI-curated results. It is about language. People are using natural language, and they are infusing personal bias into their queries. That leads to answers shaped by rankings, models, and editorial decisions inside LLMs and search engines. Search engines and LLMs are editorial by nature. This keeps the question of quality content very much alive. That question is not going away. Google is moving toward more hyper-personalized results, even if it has not figured it out perfectly yet. It may still struggle with this in 2026, but the direction is clear and gradual. Search behavior itself is not slowing down. People are not stopping their searches. That keeps pressure on businesses to figure out how to present information clearly and consistently across surfaces. Your site still needs to communicate what it does, who it serves, and why it matters in a way that machines and people can interpret. That remains foundational, even as the interfaces change. The last point is instability. Nothing stays the same for long. One day, ChatGPT relies on Bing’s index. Another day it leans on Google. At some point, it will likely build its own index. Google moved from classic organic results to AI Overviews, this year we’ll likely see AI Mode or Web Guide as a default experience. Even things like llms.txt, which are easy to dismiss, have already shown signs of being referenced. Large language models are probabilistic and unpredictable. They are dynamic systems. You cannot rely on what worked yesterday to hold tomorrow. Adaptation is no longer optional, and waiting for stability is a losing strategy. For businesses, opting out, doing nothing, or clinging to an outdated mindset could actually do damage to your business.” 

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