AI search reshapes brand discoverability as traditional SEO loses ground to citations

How to check if ChatGPT and other AI tools cite your website - and improve your chances in 2026

Follow ZDNET: Add us as a preferred source on Google. ZDNET's key takeaways * AI traffic grew 66% in 2025 but remains under 0.15% of visits. * AI citations can build exposure even without direct traffic. * These tactics can improve your visibility in AI search. You've been quietly losing traffic from organic search even though your rankings haven't changed. Does that mean traditional SEO no longer works? No. But should you then treat AI as a black box to simply accept and ignore? Also no. All the things that used to score points with traditional search engine algorithms, like backlinks, website authority, performance optimization, and quality content -- they haven't just stopped existing. AI search just treats them very differently, which is at once both better and worse. Also: Tired of AI Overviews? I found 9 Google Search alternatives that showed me links again Sometimes, that means good content is more likely to be cited by AI tools, even if your website doesn't have a high domain authority (DA) ranking. Yet it also means that most visitors will get their questions answered without ever leaving the AI platform, since the AI pulls all the information from your website into its responses without requiring users to click into your site. Luckily, that also means you get more opportunities to show up as a useful resource for your audience, even if they never actually visit your website. As long as you're being cited by AI search engines, people will notice your brand, whether or not they register as inbound traffic. With that in mind, I'm going to share some advice for earning more citations from AI search platforms without throwing SEO to the curb. I'll also share tools to help you measure your AI search visibility without breaking the bank. How much has AI changed search engines? According to Semrush's recent analysis of more than 50,000 websites, AI traffic grew by 66% in 2025 compared to the previous year. But AI still accounts for less than 0.15% of total website visits. That means two things. First, AI is taking a lion's share of search engine traffic away from websites. At the same time, not all of that traffic is being rerouted to websites through AI platforms like ChatGPT, Perplexity, or Google Gemini. Instead, AI platforms now serve as both the first port of call and the final destination for these internet users, enabling them to find everything they need without ever leaving the app. Also: Google's new AI Search box is here - along with agents and 5 more upgrades (Disclosure: Ziff Davis, ZDNET's parent company, filed an April 2025 lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.) What's worse is that websites that have been focusing on traditional SEO are suddenly finding that AI tools don't treat them with the same priority. Search engines used to look for websites with a rich library of content and demonstrated authority in a topic. AI values that too, but more importantly, it looks for text that answers a user's question precisely and immediately. Moreover, AI search engines require more targeted optimization than technical SEO typically provides. Along with a robots.txt and a sitemap, you might also want to consider having a dedicated llms.txt file for agents and bots trying to crawl your site. All of these are separate problems that, together, contribute to lower traffic and visibility from AI tools. But there are ways to solve them. How to check whether AI engines are citing you There are a few ways to assess your visibility on AI search, depending on how much time and money you are prepared to spend. Also: I tried Claude Cowork on my Gmail inbox after Gemini choked - and it saved me hours of work * The easiest way to do this is to go to ChatGPT, Perplexity, or Google AI Mode and ask 10-15 questions that you'd expect your content to show up for. Make a note of who gets cited and how many times. It costs nothing and takes very little time. * Many tools, like HubSpot's AEO Grader, are absolutely free to use for a quick analysis, which can give you a decent idea of your brand's presence in AI search engines. * If you have Google Analytics set up on your site, you can filter your referrals for traffic from chatgpt.com, perplexity.ai, gemini.google.com, etc. If you do this over several months, you can see whether your presence is improving or worsening. * Once you've outgrown free tools, consider investing in a paid AEO analytics platform like Semrush One or Otterly.AI. You can get a limited plan for as little as $29/month to get started. What actually earns an AI citation There are several things you can do to increase your chances of being cited by LLM-based generative AI platforms, according to a study published by Princeton, Georgia Tech, and the Allen Institute for AI at the 2024 KDD Conference. They tested nine content visibility tactics across 10,000 search queries, achieving improvements of up to 40%. Here's what they found to be working: Also: AI agents are getting their own search engine My thoughts on optimizing for AI search As the Semrush study clearly shows, there's a lot of misinformation and propaganda floating around about AI search and SEO. While it's true that websites are losing a lot of traffic to AI platforms, referral traffic from these tools doesn't account for nearly as many clicks as they claim. Still, there are plenty of benefits to being cited by AI, even if that doesn't lead users to visit your website directly. Also: The best SEO reporting software: Expert tested and reviewed If you've been serious about traditional SEO, you'll find that you already have all the things you need to get started with AI search optimization from existing platforms like Semrush or Ahrefs. More dedicated tooling for analytics and visibility also exists, but not everyone will need it. Also, it's worth keeping in mind that the basic principle of creating useful and informative content hasn't changed. But there are things that AI tools approach differently when it comes to researching answers to user queries, which can help you show up in more responses.

Relax. AI Hasn't Changed Search as Much as You Think

If you run marketing, take a breath. The shift to AI search is here, but the work you must do has shifted. Before you tear up your playbook, there are four things to understand about how AI search works: SEO isn't dead, AI search runs on the past, everyone sees a different answer, and you can't measure where you stand by asking AI yourself. Get that straight and the rest gets a lot less scary. For 20 years, search meant Google. You typed in a question or a brand name and got a page of results. A few paid ads sat up top, where companies bid on keywords to grab more share of voice, and then came the blue links. We spent two decades learning how to rank first on that page. Over the last few years, that behavior has moved. People now ask ChatGPT, Claude, Perplexity, Gemini, Grok, and others, the same things they used to type into Google, except now they get about three to four answers instead of 10 links. This isn't a fringe habit. Bain & Company found that about 80 percent of consumers lean on AI-written summaries for at least 40 percent of their searches, and roughly 60 percent of searches now end without anyone clicking through to a website. The answer is the destination now. That's a real change. Here's what to understand before you react. SEO isn't dead You've heard that SEO is dead. I don't agree. The large language models (LLMs) behind AI search are trained on the open web, and they pull from it, and that web is the one SEO built. If your content is structured, credible, and easy to find, you're feeding the same sources these models draw from. If it isn't, you're invisible to them too. What changes is the emphasis, not the work. Ahrefs studied 75,000 brands and found that brand mentions across the web track with AI visibility far more closely than backlinks. Getting talked about in articles, guides, and other people's sites now counts at least as much as your own pages. So, keep doing SEO. Just stop treating your own website as the only thing that matters. AI search runs on the past LLMs learn from existing data, so their knowledge is historical by design. That has a consequence most marketers miss. If you change your positioning today, launch a new message, or fix your site, don't expect AI search to reflect it tomorrow. The models were trained before you made the change, and it takes time for new content to be crawled, absorbed, and surfaced. Plan for the lag. This is a months-long build, not a switch you flip. The brands that appear in AI answers next year are the ones putting in the work right now. Everyone sees a different answer This is the part that trips people up. There's no single fixed ranking in AI search like there was on Google for two reasons. The first is personalization. There's a name for the mechanism behind it: fingerprinting. It's a tracking technique that stitches together small signals about you. These signals include your browser, device, location, time zone, and language, and it is compiled into a profile unique enough to pick you out of millions of people. Your fingerprint follows you even when you're not logged in, and even in incognito or private mode. AI tools tailor their answers off the same idea: what they can tell about who's asking, plus whatever they remember from past conversations. So, if two people ask, "What's the best project management tool for my team," ChatGPT can hand them different brands based on what it already knows about each of them. The recommendation changes depending on who's doing the asking. The second is that these systems aren't deterministic. Open an incognito window, run the same query twice, and you'll often get two different answers. Combine these two factors and LLM answers start to feel like snowflakes. The answer you see isn't the one everyone sees and isn't even the one you'll see again. You can't measure where you stand by asking it yourself The worst way to learn how your brand is performing in AI search is to ask ChatGPT yourself. You'll get one answer, shaped for you, that probably won't repeat if you run it again. It gets worse if you ask about your own brand by name. These models are built to be agreeable, so the moment you suggest your company belongs in the results, it goes along with you. Ask if you're a top three player and it will often just say yes. That's not the truth; it's a flattering, tainted answer. The first step to appearing in AI search is measuring. Before you spend a dollar improving your AI visibility, find out where you stand, and do it at scale, across many runs, so the personalization and randomness average out. Then get specific. Figure out your ideal customer profile, identify the exact prompts that customer would type, and measure how you show up on those. A generic ranking barely tells you anything. The prompts your buyer uses are the only ones that move revenue. For now, sit with the basics: SEO still matters, AI learns from the past, everyone sees something different, and you can't manage what you haven't measured. Get these four principles straight, and you're already ahead of most of the market. Get 1 Smart Business Story delivered straight to your inbox when you subscribe to Inc.'s free daily newsletter.

AI Is Changing How Businesses Are Found Online. That's Why You Need to Rebuild Your Search Strategy.

AI search continues to evolve, and if you don't want to get left behind, there are four signals your business needs to get right to stay at the top of the search results page. Recently, a client came to me with a problem that turned out to be anything but small. On paper, their business was thriving. Their clientele was loyal. The offer was polished, and the team was exceptional at what they did. Yet when people searched online for their business, particularly inside the newer AI tools, they were nowhere to be found. This client did not need another generic marketing checklist. They needed a real strategy to be seen. They needed to appear where people actually search today, not where they searched a decade ago. Today, people are not only typing business names into Google. They are asking ChatGPT. They are turning to Gemini. They are consulting Perplexity. They rely on AI to decide who to trust, where to go and which expert deserves their business. So if your company is built only for old-school search, you are playing yesterday's game. I watch this every single day across all of my businesses. AI search keeps evolving and I have no intention of being left behind. More importantly, I refuse to let my clients be left behind either. Search isn't just ranking anymore -- it's your reputation For a long time, search felt fairly predictable. You chose smart keywords. You placed them across your site. You pursued a few backlinks. But that version of search is no longer the full picture. The bigger question now is not simply, "Where do I rank?" A better question is, "Do new ways people search the internet trust my business enough to recommend me?" That is an entirely different game. Now your business has to be more than findable. It has to be worth recommending. I think of it this way: Old search was about landing on the list. Modern AI search is about earning the introduction. Different search engines want different things One of the most common missteps I see owners make is assuming every search platform behaves the same way. They do not. Google, ChatGPT, Gemini, Perplexity, Claude and the rest each have their own way of finding, reading and sharing information. They overlap, but they are far from identical. Some lean heavily on indexed web content. Some look for trusted sources and citations. Some study reviews and reputation closely. Some want clear, structured details so they understand exactly what you offer. Picture each platform as a different customer. One wants credentials. One wants social proof. One wants receipts. One wants to hear what your clients think. One simply wants everything explained plainly. Your task is to make certain they all leave satisfied. I build genuine proof across the web: clear messaging, strong content, accurate business details, press signals, reviews and a consistent story. When that foundation is right, your visibility begins to travel. The 4 signals I build for every business Your customers look for four signals: trust, authority, relevance and reputation. Get those four things right, and you give every engine more reasons to notice you and recommend you. If they are weak, even a beautiful website can struggle. 1. Trust Trust is the starting line. Before anything recommends you, it needs to feel certain you are real and consistent. Your name, address, phone, website and profiles should match everywhere. You would be amazed how many businesses have mismatched versions of themselves drifting around. To clients, that looks careless. To search tools, it looks risky. 2. Authority Authority is when credible sources vouch for you. Press, interviews, podcasts, articles, partnerships and recognition all help. You can praise yourself all day, but when a respected source says it, that carries real weight. I would rather earn one strong mention in the right place than 50 weak ones nobody trusts. 3. Relevance Relevance is clarity. Engines need to understand what you do, who you serve and where you operate. Vague phrases like "solutions for modern businesses" sound impressive but say nothing. Be clear in your messaging. 4. Reputation Reputation is what people say when you are not in the room. Reviews, testimonials and social proof shape how you are perceived. You cannot fake it for long. You earn it by doing exceptional work, inviting delighted clients to share positive reviews about your business. Why this is so important Here is the part people do not love to hear: AI search is not a fix-it-once-and-forget-it affair. There is no finish line. Platforms change. Results change. Competitors improve. Reviews arrive. Signals shift. So I treat visibility as an ongoing part of every business I touch. AI search evolves daily and I refuse to wake up six months from now to discover a competitor became the answer to their question while I ignored the question. I check. I test. I ask AI tools what they recommend. I watch who appears and why. It is like glancing at your dashboard. You do not stare at it all day, but you want to know the moment the warning light flips on. What this means for you If you own a business, the truth is simple: Your clients already use AI search, ready or not. They ask for recommendations and weigh their options. If the tools they trust never mention you, you may never get the chance to compete. Start by seeing what is actually happening. Ask Google, ChatGPT, Gemini and Perplexity about your industry and local market. Notice who appears. Then strengthen your foundation. Refine your information. Build real reviews. Create clear content. Earn credible mentions. The winners in this new era will not be the loudest. They will be the clearest, the most trusted and the easiest to recommend. I am not chasing rankings like it is 2012. I am building trust across the entire web.

Beyond SEO: The new rules of brand discoverability in the AI era

Brand discoverability is shifting from search engine rankings to AI-driven answers. AI systems now prioritise authoritative third-party signals over traditional keyword optimization. Listen to this article in summarized format Listen × Subscribe to Unlock AI Briefing and Premium Content New Year Offer 24 Hours Left Subscribe Now Already a member? Sign In What's Included * Exclusive Stories * Daily ePaper Access * Smart Market Tools * Curated Investment Ideas * Ad-lite Experience * Subscription For two decades, brand discoverability had a scoreboard. You ranked on Google, tracked your position, and fought for the click. The whole marketing machine was built on one assumption: that discovery happens on a results page, and the click is where the customer journey begins. That assumption is quietly breaking, and most brands have not noticed, because the breakage does not show up in their dashboards. When someone asks ChatGPT, Perplexity, or Google's AI Overviews a question, the answer is composed before that person ever sees a list of links. The system has already retrieved its sources, weighed them, and decided which brands deserve to be in the answer. Authority is inferred, not clicked into. If your brand is not selected at that stage, the click you were optimising for never comes into existence. This is the new top of the funnel: invisible, upstream of your analytics, and already shaping purchase decisions from financial services to enterprise software. The math has changed underneath us I see citation data across dozens of brands, and the ranking logic has completely inverted. Most of what won you rankings in classical SEO now carries little weight with AI systems. Keyword optimisation has collapsed, and what remains works through meaning rather than matching. In its place is a set of signals most brands never deliberately built: authoritative third-party lists, reviews and ratings, directories, awards, case studies, and social sentiment, the nice-to-haves of the SEO era that are now the raw material from which AI builds its view of your brand. The deeper inversion is conceptual. SEO ran on keywords. AI search runs on entities, the identifiable things that live in knowledge graphs with relationships attached. The question is no longer "do you rank for this keyword" but "does the machine know who you are, what you do, and how you relate to everything else in your category." A brand can produce excellent content and still be an unresolved entity, a name the model has seen but never understood, and that brand is invisible no matter how good its blog is. Your content is not the answer. The chunk is. AI does not rank pages; it retrieves, compresses, and decides. The unit of value is no longer your 2,000-word article but the extractable chunk the model can lift from it. So AI penalises much of what brand content celebrates: long introductions, buried definitions, adjectives like "leading" and "best-in-class," inconsistent product naming. What it rewards is almost journalistic: clarity over length, definitions over fluff, stable phrasing it can reuse. Freshness compounds it: AI citations skew far newer than Google's, so a page that ranked number one in 2023 and has sat untouched is decaying in AI visibility even while its Google rank holds. The implication for CMOs is clarifying: content teams are no longer storytellers alone but architects of machine-readable authority. Call it GEO, or answer engine optimisation; it is product marketing for the machines, positioning your brand for an audience of models and, through them, for millions of humans. PR just became a growth function If there is one budget line this era rehabilitates, it is public relations. A large share of what AI models say about a brand is shaped by mentions in trusted editorial media, which makes PR, long treated as a soft and unmeasurable function, one of the biggest drivers of visibility in AI search. Reddit, Quora, Wikipedia, Crunchbase, and YouTube matter for the same reason: they are where machines assemble their understanding of you. There is a dark side. AI answers have a replication effect: a single outdated or negative mention gets amplified across models and persists until fresher signals displace it. Without deliberate hygiene, your worst review can become your defining trait in the medium where a growing share of discovery now happens. What the playbook actually looks like None of this means SEO is dead. It means SEO is no longer sufficient. Journeys are now multi-modal, and the operating model every marketing leader should adopt is Search Everywhere Optimisation: SEO and GEO run as one system. In practice it reduces to a few moves. Expand content coverage across long-tail queries. Refresh relentlessly until content performs. Keep technical hygiene clean so machines can crawl and chunk you. Build authority through digital PR. Invest in social signalling across Reddit, Quora, and LinkedIn. And scale into multimodal formats, video above all. The deeper shift is one of mindset. Discoverability is no longer a channel you buy or a ranking you win. It is the sum of everything the machines can find, trust, and reuse about you. Once in a generation, a technology does not just improve how things work, it changes how we see the world. That is what is happening to search. The brands that treat AI visibility as a strategy, not a side project, will be the ones the machines, and therefore the market, remember. The author is the Co-Founder and CEO of Pepper. (Disclaimer: The opinions expressed in this column are that of the writer. The facts and opinions expressed here do not reflect the views of www.economictimes.com.)

Search Has Become a Brand Problem, Not a Channel Problem

The technology behind AI search will continue to evolve, as it always has. New ways to optimise will emerge, and marketers will adapt as they always do. But the bigger, lasting change probably won't be about technology. Authored by Krithiga Reddy, Co-founder & CEO, OptimizeGEO.ai For a long time, search was one of the most specialised areas of marketing. If rankings fell, the SEO team knew where to look. They would check technical performance, keywords, content, and backlinks, following a playbook that has evolved alongside search engines over the past 20 years. Like PR, branding, or media planning, search had its own experts, its own metrics, and usually its own team. That structure made perfect sense for the internet we knew. But today, the way people look for information is changing. More often than not, they are not just asking where to find something. Instead, they ask AI systems what to choose, trust, or consider. People now expect recommendations, not just information. This might seem like a small difference, but it changes what brands need to do to succeed in search. Traditional search engines were designed to organise information and direct users to relevant webpages. AI systems are expected to interpret information, compare competing claims, and arrive at an answer they can stand behind. That confidence rarely comes from a single webpage. Instead, it is built by combining many signals from across the web. A company's website is just one signal now. Media coverage, executive interviews, customer reviews, independent research, product documentation, and industry discussions all shape how people perceive a brand. On their own, these are just bits of information. Together, they help build credibility. This change affects far more than just SEO. Marketing has been organised around channels because each channel rewards different capabilities. The brand built awareness. PR built credibility. Content demonstrated expertise. Search improved discoverability. Each function had a distinct role and was measured independently. But outside a company, those lines have never really mattered. Customers don't experience a brand through departments. Their opinion is gradually shaped by everything they encounter: an article they read, a colleague's recommendation, a review, a product experience, or a founder interview. AI is beginning to form an understanding in much the same way. Rather than evaluating these signals separately, it combines them into a broader picture of whether a brand appears knowledgeable, credible and worthy of recommendation. Consider two brands competing in the same haircare category. Both have strong traditional SEO, solid rankings, healthy traffic, and well-optimised pages. But when consumers ask an AI system which products to use for frizz control or hair fall, one brand appears consistently and the other barely registers. The difference isn't product quality or even brand recognition. It's context. The brand winning AI recommendations had clearly mapped its products to specific consumer problems, built a credible presence on the platforms AI systems draw from- YouTube, Reddit, and specialist marketplaces- and structured its content to answer questions directly rather than rank for keywords. The other brand had invested heavily in its own site but had neglected the wider ecosystem that AI uses to form its view. We saw exactly this pattern with a global beauty brand, a household name with strong traditional search performance. When we ran a prompt-level AI visibility analysis across 120 high-intent haircare queries, the brand appeared in fewer than 90 mentions across all major AI platforms. Competitors with smaller market share were being recommended more often, not because their products were better known, but because AI systems had clearer signals about what those products were for and where to find trusted references. Within 60 days of fixing those gaps, strengthening category associations, reworking content structure, and building presence on the platforms AI actively cites, the brand grew its AI mentions more than threefold. Technical SEO hadn't caught any of this. Rankings were fine. But discoverability in AI had become a different problem entirely. Many organisations are asking where AI discovery should sit. Is it the next evolution of SEO? Does it belong with the content? Should corporate communications take ownership? These are fair questions, but they show how much we still see marketing through channels. If discoverability now depends on a brand's overall digital reputation rather than on a single place, then no single team can handle it alone. Technical optimisation is still important, but so are clear messaging, proven expertise, external validation, and taking part in industry conversations. These areas don't compete; they increasingly support each other. This doesn't mean marketing teams need to change everything immediately. But it does mean that discoverability isn't just one team's job any more. It's now the result of how well an organisation builds trust wherever its brand appears. In conversations with CMOs at enterprise brands, a consistent pattern is emerging. Most started by asking a narrow question: how do we maintain search visibility as AI changes user behaviour? But the conversation quickly widens. Once they see how AI systems actually generate recommendations by pulling from media coverage, third-party platforms, community discussions, and structured content across the web, the question shifts from "who owns AI search?" to "how do we build a brand that AI can understand and trust?" The organisations making the most progress are the ones that have stopped treating this as an SEO problem handed to a single team, and started treating it as a coordination challenge across brand, content, communications, and digital. They are building shared visibility metrics that cut across functions, not just rankings or traffic, but how consistently and accurately the brand is represented wherever AI systems look. That shift is likely to reshape marketing structures over the next few years, not through dramatic reorganisation, but gradually, as discoverability becomes a shared accountability rather than a channel-specific metric. The teams that adapt fastest won't necessarily be the ones with the most sophisticated AI tools. They'll be the ones that have built enough internal alignment to present a coherent, well-evidenced brand to the world, because that's what AI rewards. The technology behind AI search will continue to evolve, as it always has. New ways to optimise will emerge, and marketers will adapt as they always do. But the bigger, lasting change probably won't be about technology. The real shift is that discoverability and reputation are now closely linked. Brands that are well understood, frequently mentioned, and trusted across the digital world are the ones AI systems are most likely to recommend. Search isn't disappearing as a discipline. It's dissolving into something bigger: the sum of everything a brand has earned the right to be known for.