Marketers Shift Budgets to AI Search as Generative Engine Optimization Overtakes Traditional SEO

How AI Search Will Change in the Second Half of 2026 -- and What It Means for Your Visibility

"AI search" is no longer one thing: only 11% of domains are cited by both ChatGPT and Perplexity, so each engine has to be treated as its own ecosystem. On January 27, 2026, the visibility of thousands of businesses changed overnight -- and almost nobody noticed why. That day, Google quietly swapped a new model, Gemini 3, into AI Overviews and AI Mode. There was no "core update" announcement and no warning to site owners. Yet according to an analysis of the aftermath, the number of cited sources per AI answer jumped by roughly a third, freshness suddenly carried more weight and entity-rich websites gained share at the expense of thinner ones. ChatGPT, running on an entirely separate pipeline, was completely unaffected. I have come to think of this event as the template for the second half of 2026. The first half made AI search official. Google published its first optimization documentation. Marketers began allocating more budget to AI search than to traditional SEO. The discipline of generative engine optimization moved from experiment to expectation. The second half will be defined by something less visible but more consequential: the engines themselves are changing underneath us. Model upgrades are the new algorithm updates For two decades, marketers learned to brace for Google's algorithm updates. The AI-era equivalent is the model swap -- and unlike Google's updates, these arrive unannounced, undocumented and on multiple platforms at once. The mechanics explain why each one matters so much. Modern AI search systems do not process your question as a single query. They fan it out into many parallel sub-queries -- often eight to twelve, and in ChatGPT's case up to twenty -- retrieve sources for each, verify claims and synthesize an answer. As models become more capable, this process grows more thorough and, crucially, less gameable. Research already shows that only a quarter to a third of AI citations come from pages ranking in the traditional top ten. The newest models reason more, check more and trust selectively. In our own client work, we observed this firsthand around the release of GPT-5.4: noticeably increased volatility in AI recommendations across accounts. Not necessarily steep drops, but a constant reshuffling that would have been unthinkable in the comparatively stable world of classic search rankings. With Gemini 3.5 Pro arriving and further flagship releases expected from every major lab before year's end, businesses should plan for several more of these invisible resets in the second half. The only durable hedge is content that survives machine scrutiny: verifiable claims, named expertise and consistent factual signals about who you are and what you do. Three platforms, three different games The second thing to understand about the coming months is that "AI search" is no longer one thing. The three dominant assistants are diverging into fundamentally different strategies. ChatGPT is doubling down on personalization and monetization: its memory features are maturing rapidly, and its advertising pilot is expanding internationally to the UK, Mexico, Brazil, Japan and South Korea. Gemini is fusing Google's retrieval and trust infrastructure with in-chat commerce, letting users complete purchases without ever leaving the conversation. Claude, by contrast, has positioned itself as the ad-free option focused on professional and agent-driven work. The consequence is measurable: one large-scale citation study found that only 11% of domains are cited by both ChatGPT and Perplexity, and brand recommendations can differ by 40 to 60% across platforms for identical queries. Each engine is its own ecosystem, with its own biases and blind spots. What makes this genuinely workable, however, is that the models will often tell you about those blind spots -- if you ask. When we run AI visibility audits, we routinely ask the models directly why a client was not included in a recommendation. These explanations should be taken with a grain of salt, since we cannot rule out that they are post-hoc rationalizations. But they frequently surface actionable insights. One example: a dropshipping platform we work with was being recommended heavily by Gemini as a top option, yet had vanished entirely from certain ChatGPT recommendations -- despite having been ChatGPT's number-one pick for the same prompts just two months earlier. When we asked why, ChatGPT explained that the platform was not known for working well with Shopify, even though our prompt had never mentioned Shopify at all. The model had silently made ecosystem compatibility part of its decision. After the client published substantial content addressing Shopify integration specifically, they reappeared in those recommendations. That is the texture of GEO in late 2026: less about rankings, more about understanding -- and correcting -- what each model believes about you. The personalization endgame There is a deeper shift hiding inside the memory race. As ChatGPT, Gemini and Claude all build systems that remember individual users -- their preferences, their history, their context -- two people asking the identical question will increasingly receive different recommendations. I argued recently that AI visibility is a winner-takes-all game, because most users simply accept an assistant's initial recommendation rather than browsing alternatives. Personalization extends that logic to its conclusion: the contest becomes winner-takes-all per user. A brand that wins the early interactions with a customer's assistant gets reinforced within that relationship, query after query, while competitors become progressively harder to surface. It also means third-party visibility tools, which track generic prompts from anonymous accounts, will capture an ever-smaller slice of reality. Expect measurement to get harder in the second half, not easier -- and expect the premium on being a customer's first AI-recommended choice to keep rising. The web starts charging admission The final trend on the horizon concerns the infrastructure beneath all of this. Publishers and infrastructure providers are erecting toll booths. Cloudflare now blocks declared AI crawlers by default and offers a pay-per-crawl model, millions of sites have opted out of AI training, and licensing intermediaries are signing up mid-sized publishers. Every business now faces a strategic question that did not exist two years ago: open your content to AI systems and compete for citations, or block them and protect your work at the cost of invisibility. My view -- informed by having sat on the publisher side of the table as well as the marketer's -- is that history overwhelmingly favors staying open. When Spotify effectively killed CD revenues, the music industry did not die. It restructured. Artists today earn far more from live events than their predecessors did, and smaller acts can build an audience and income through self-publishing at a speed that was impossible in the label-gatekeeper era. AI will impose a similar restructuring on many industries, and not all of it will be comfortable -- but businesses that withdraw from the new distribution layer to protect old revenue lines have rarely ended up on the winning side of such transitions. Adaptation, not retreat, is the historical pattern. One practical aside: despite the hype, the llms.txt file -- often sold as a quick AI visibility fix -- is still used by no major AI provider in production, and Google has said on record it does not support it. For now at least, you can spend your energy elsewhere.

How Google Is Rewriting Search -- and What Entrepreneurs Must Do Before Their Competitors Do

Google has published the rulebook for AI visibility, and the entrepreneurs who read it before their competitors do will own the recommendations everyone else is fighting to enter. PMG, one of the world's largest independent marketing agencies, now advises clients to pilot generative engine optimization at 1.5 to two times their existing search budget, according to Matt Allfrey, its head of SEO EMEA. PMG is hardly an outlier. A June 2026 Semrush study of nearly 500 marketing professionals found that more respondents plan to invest in AI search optimization (38%) than in traditional SEO (36%) -- a quiet crossover moment for an industry that treated GEO as a curiosity just two years ago. In the same survey, 85% of marketers said AI has already changed how they approach search. Over the past several weeks, Google has made a series of announcements that, taken together, amount to the most significant restructuring of Search since its inception. The company has redesigned how its AI features present the web to users and, in a notable first, published official documentation explaining how businesses can optimize for the new environment. For entrepreneurs, understanding both moves is no longer optional. Search is becoming an answer engine In early May, Google announced updates to AI Mode and AI Overviews, the AI-powered layers that now sit on top of traditional search results. The changes include suggested follow-up angles at the end of AI responses, website previews that appear when users hover over links, highlighted results from news publications a user subscribes to, and citations placed directly beside the relevant text. On the surface, these look like small interface refinements. In reality, they confirm a structural shift: the AI-generated answer, not the list of links, is now the primary product. Users receive a synthesized response first and decide afterwards -- if at all -- whether to click through. The consequences are already measurable. According to reporting by Nieman Lab, referral traffic from search engines has fallen by roughly 60% for small publishers and 47% for medium-sized ones over the past two years. This mirrors what I see in my own work: across virtually all of our clients, Google traffic has declined sharply, regardless of industry or content quality. The question is no longer how to recover that volume -- it is how to keep conversion rates high as AI referrals gradually pick up the slack. In our experience, visitors arriving from an AI recommendation tend to be further along in their decision-making, which makes each of those clicks considerably more valuable than a casual search visit ever was. Google publishes the rulebook What makes this moment different from previous search upheavals is that Google is, for once, showing its hand. In mid-May, the company released its first official guide to optimizing for generative AI features -- a document that addresses, in plain language, what influences visibility in AI Overviews and AI Mode, and what does not. The guide's central message is that optimizing for generative AI search is, from Google's perspective, still SEO. But it goes further, explicitly debunking several practices sold aggressively under the "generative engine optimization" banner over the past two years. There is no special schema markup that unlocks AI visibility, Google states, and chasing inauthentic mentions of your brand across the web is far less effective than it appears. What the guide consistently rewards instead is unique, non-commodity content -- material grounded in genuine expertise that an AI system cannot source anywhere else. In early June, Google followed up by updating its long-standing guidance on hiring SEO help, adding a new document on evaluating third-party tools and services and explicitly naming GEO and AEO as service categories for the first time. The updated guidance even supplies vetting questions for business owners: Does the provider cite official Google documentation? Is their AI optimization advice aligned with Google's published guidance? For anyone who has sat through a sales pitch promising guaranteed placements in AI answers, this is a long-overdue corrective. A winner-takes-all game Here is what entrepreneurs must understand about the new landscape, and it is the point most coverage misses: AI visibility, far more than classic Google search, is a winner-takes-all game. In the old model, a business ranking fifth -- or even fifteenth -- still captured meaningful traffic, because users browsed, compared and formed their own shortlists. That behavior is disappearing. When an AI assistant recommends two or three options in a conversational answer, most users simply accept them. They do not scroll through alternatives, open ten tabs or venture to page two, because there is no page two. The recommendation is the market. This dynamic means the gap between being cited and not being cited is no longer a difference in degree but a difference in kind. A brand that appears in AI answers compounds its advantage with every query; a brand that does not is, for a growing share of customers, effectively invisible. Google's recent changes only sharpen the trend. Features like suggested angles and community perspectives create a handful of additional slots inside the answer -- but they remain a handful, contested by everyone in your category. What entrepreneurs should do now The practical response follows directly from this logic. First, read Google's optimization guide yourself before commissioning any external help. It is short, written for non-specialists, and now serves as the standard against which every GEO pitch should be measured. If a vendor's recommendations contradict it, walk away. Second, shift your content strategy from volume to depth and authenticity. The new AI surfaces visibly reward subtopic depth and first-hand experience -- original research, real case studies, perspectives only you can provide. Commodity content, which AI systems can synthesize from a thousand interchangeable sources, no longer earns citations, links or trust. Third, rethink your metrics. If your dashboards still treat raw traffic as the headline number, you are measuring a shrinking game. Track how often your brand appears in AI-generated answers for the queries that matter commercially, and watch the conversion rate of AI-referred visitors. In most cases, you will find fewer clicks doing more work. Search as we knew it is not coming back, and waiting for the dust to settle is a strategy with an expiry date. The businesses that treat AI visibility as the winner-takes-all contest it has become -- and act while their competitors are still mourning their traffic reports -- will own the recommendations everyone else is fighting to enter.

Why Regulated Businesses Have an Unfair Advantage in AI Search

Put the credentials forward, name who stands behind the answer, pursue the third-party validation, answer real questions accurately, and keep your public information consistent everywhere it appears. Founders in healthcare and law tend to describe regulation as the thing that slows their marketing down -- every claim reviewed, every credential checked, every word lawyered. In traditional search, that caution felt like a tax. In AI search, it is an advantage, and most regulated businesses are not using the one edge their industry handed them. The short version: The caution you are forced to carry -- named experts, verified claims, outside validation -- is the exact signal AI answer engines look for when they decide whom to cite. The constraint is the moat. Your competitors in unregulated fields have to manufacture that credibility. You are required to keep it on file. Why is AI search cautious about health and legal answers? Health and legal questions are consequential. A wrong answer can hurt someone, and the engines know it. An early Stanford audit of generative search engines found that only about half of their generated sentences were fully supported by the citations attached to them, and only around three in four citations actually backed the statement they sat beside. Those specific systems have improved since. The lesson they taught did not go away. When the cost of being wrong is high, the engine hedges toward sources that lower its risk, favoring accuracy, credentials and outside validation, because citing a careful source is safer than citing a confident one. This is sharpest in what search systems classify as YMYL, your money or your life -- the health, legal and financial queries where a bad answer does real damage. The citation bar in those categories is higher than anywhere else. That higher bar is not working against a regulated firm. It is the filter that clears out everyone who cannot meet it. What does AI search actually reward in regulated industries? Look at what gets a source surfaced in these fields. In law, AI tends to name firms with peer recognition, presence in the directories the profession already trusts and consistent public information across the web. In healthcare, it favors content with named clinicians, visible medical review, real credentials and information that is current and accurate. Underneath both sits one more thing the engines quietly weigh: consistency. Your name, your people and your core facts have to read the same everywhere they appear -- on your site, in the directories, on the review platforms -- because a machine treats contradiction as doubt. Notice that none of these are marketing tricks. They are the exact things a regulated business already has to maintain. The compliance file and the credibility signal are the same file. There is a deeper version of this that goes past AI search. Specificity is what earns belief from a skeptical, high-stakes buyer, and generality is what erodes it. As I argued in The Credibility GTM, the healthcare buyer is evaluating risk, not scrolling a feed, and a generic proof point reads as a hedge. The instinct an engine uses to decide whom to cite is the same instinct a physician or a general counsel uses to decide whom to trust. Win one, and you are most of the way to the other. How regulated firms waste the advantage They hide it. They publish the same generic, anonymous content as everyone else, strip the personality and the credentials out in the name of caution and end up indistinguishable from a content farm. The reviewed expertise that would make them citeable sits in a drawer while the website says comprehensive solutions for all your needs. They confuse being careful with being faceless, and the engines cannot cite a face that is not there. Picture two orthopedic practices. One page says our board-certified surgeons deliver exceptional outcomes, with no names, no links, nothing to check. The other names the surgeon, links her board certification and answers what recovery from a specific procedure actually looks like week by week. Ask an engine which one to trust, and it has exactly one real option. The first practice did the harder clinical work and then made itself invisible, which is the whole problem in one page. But doesn't more content win? There is a real objection here, so name it. In classic SEO, volume often did win -- more pages, more keywords, more surface area -- and it is tempting to port that logic into AI search and publish at scale. In a regulated field, that is a mistake, and a costly one. Volume without accuracy is not neutral. It is a liability, because a single wrong claim in a health or legal context is the kind of error that erodes credibility and sometimes carries real exposure. You do not need a large content operation. You need your most important pages, the handful your buyers actually ask about, to answer real questions accurately, name who is answering and stay consistent. Depth on what matters beats farmed volume, and in these verticals, it is the only version that is safe. The move is to lean in, not apologize Put the credentials forward. Name the clinician or the attorney who stands behind the answer. Pursue the third-party validation your field already respects. Answer real questions accurately, and keep your public information consistent everywhere it appears. The rigor was never the obstacle. It is the asset, and the firms that treat it that way will be the ones AI recommends while their competitors keep filing it away. What to do this quarter You can start small and still move ahead of most of your category, because the bar right now is low. Here are a few concrete moves, in order of leverage: * Put a named, credentialed expert behind each of your most important pages, with their real title and a link to their credentials. Anonymous authority does not survive an engine's scrutiny. * Answer the specific questions your buyers actually ask, in their words, on their own pages. Not a service line. The question itself. * Earn the outside validation your field respects (medical review in healthcare, peer recognition and trusted directories in law), and maintain consistent listings everywhere your business appears. * Make the machine's job easy. That means clean headings, plain language and structured markup that labels who wrote a page and what it answers. Four moves, on the pages that matter, done accurately. That is the whole early game. Trust is what converts Across five stages of growth -- visibility, credibility, authority, adoption and scale -- regulated businesses are built to win the middle three, the trust stages, if they stop hiding what makes them trustworthy. Visibility is a cost until it converts, and in high-stakes fields, the thing that converts it is exactly the rigor you already carry. One compounding effect is worth naming. Citation authority behaves the way domain authority did a decade ago. The sources an engine learns to trust this year are the ones it reaches for next year, so the regulated firm that leans in now builds a lead that late movers pay far more to close. Stop treating your strongest asset like a liability. Start putting it on the page. Frequently asked questions Does AI search favor big brands over smaller regulated firms? Not the way traditional search rewarded big ad budgets. Engines weight credibility signals, named experts, verified claims and third-party validation over spend. A small firm with real credentials and consistent, accurate information can be cited ahead of a larger competitor that publishes anonymous, generic content. How long until a regulated business shows up in AI answers? For engines that pull live sources, like Perplexity and Google's AI answers, content and structural changes can surface in weeks rather than months. The trust built through credentials and third-party validation compounds more slowly, which is the point. It is also what makes the position hard for a competitor to take back. What is GEO, and how is it different from SEO? SEO gets your page ranked in a list of links. GEO, generative engine optimization, gets your business named inside the answer an AI system writes, in ChatGPT, Perplexity, Claude or Google's AI overviews. The two overlap, since clean structure and consistent information help both. GEO simply leans harder on the credibility signals a regulated firm is already required to keep, which is why these fields are positioned to win it.

Generative Engine Optimization (GEO): How LLM Retrieval Changes Impact AI Visibility

Generative Engine Optimization, or GEO, has become one of the fastest-growing areas in digital marketing. Traditional search engine optimization focuses on higher positions in search results. GEO follows a different goal. It helps brands appear inside AI-generated answers from platforms such as ChatGPT, Google AI Overviews, Gemini, Claude, Copilot, and Perplexity. This shift changes the way people discover products, services, and information. Recent reports show that marketers now place more attention on AI visibility than simple search rankings. Industry experts expect this trend to shape the future of online discovery as AI assistants answer millions of questions every day. no longer depend only on keyword matching. Modern AI systems follow a retrieval process that starts with user intent. The system searches trusted sources, collects relevant documents, compares each source for quality, and selects only a small set of passages. The language model then creates a natural answer with support from those selected sources. This retrieve, rerank, and generate pipeline leaves little room for weak or poorly structured content. Content that never reaches the first retrieval stage cannot appear in the final response, no matter how detailed it looks. This major change explains why AI visibility now depends on retrieval quality instead of search ranking alone. The move toward continues at a fast pace. Google AI Overviews now reach more than 2.5 billion monthly users, while ChatGPT serves around one billion weekly users. AI assistants now answer a large share of online questions before visitors open traditional search results. This pattern creates more zero-click searches and fewer direct website visits. Several studies also report that AI referral traffic has grown sharply, even as click-through rates from traditional search continue to decline. These numbers highlight a clear shift from page rankings toward AI citations and brand mentions. Academic research offers valuable insight into successful . The original GEO study found that content with statistics, quotations, citations, and reliable references achieved visibility gains of up to 40 percent within controlled experiments. A larger review of 45 GEO studies, published in July 2026, reached another important conclusion. The review found that content structure, topical relevance, and strong context placement deliver more reliable results than generic optimization tricks. The researchers also noted that AI platforms often produce different answers for the same question, which makes continuous evaluation an essential part of every GEO strategy. High-quality content now plays a larger role than keyword repetition. AI systems understand topics, relationships, and entities instead of isolated phrases. Clear headings, direct answers, well-organized sections, trusted statistics, and accurate citations help retrieval systems understand each page with greater confidence. Independent publications and respected news outlets also strengthen authority. Many AI systems trust third-party validation more than promotional claims from company websites. Strong entity descriptions, structured information, and fresh updates increase the chance of selection during retrieval and citation stages. Traditional , impressions, and click-through rates. GEO introduces a different set of performance indicators. Companies now monitor AI citation frequency, brand mentions inside AI responses, share of voice across multiple AI platforms, AI referral traffic, and answer inclusion rates. Several software platforms already provide dashboards that measure AI visibility instead of keyword rankings. Industry reviews highlight tools from , Semrush, Ahrefs, Surfer, Mentions, and as leading options for brands that want detailed insight into AI search performance. Also Read - How to Rank Higher on Google My Business (Local SEO Tips) Generative Engine Optimization has moved far beyond a marketing trend. It now represents a major change in online discovery. Search no longer ends with a ranked list of blue links. AI assistants now collect information, evaluate trust, select the strongest evidence, and present complete answers in seconds. Every stage of this retrieval process shapes brand visibility. Organizations that publish original research, maintain accurate entity information, present clear facts, and earn recognition from trusted third-party sources stand in a stronger position for future AI search. Recent industry analysis also suggests that the next phase of digital competition will focus less on page rankings and far more on citation, authority, and retrieval success inside AI-generated answers.

AI Search Is Rewriting How New Zealand Firms Win Attention Before The Click

New Zealand businesses are discovering that visibility no longer starts on a homepage. It starts in the answers people read before they ever click. AI search tools, answer engines, and citation-heavy summaries are reshaping how buyers evaluate local services, exporters, and professional firms. That shift matters because traditional SEO playbooks assumed a ranked blue link was the prize. In practice, the prize is now being named, quoted, and trusted inside the answer itself. If your firm never appears in those generated summaries, you can still have a solid website and still lose the shortlist. What changed in the buyer journey - Buyers ask fuller questions, not just two-word keywords. - AI tools compress ten tabs of research into one briefing. - Citations and brand mentions often matter more than raw rankings. - Local proof -- case studies, credentials, and clear service pages -- gets reused as source material. For New Zealand companies selling into Australia, the US, or Asia, this creates both risk and opportunity. A thin brochure site is easy for AI systems to ignore. A well-structured site with original expertise is easy to quote. Practical moves that still work First, publish pages that answer complete questions: pricing models, delivery timelines, compliance constraints, and who the service is for. Second, keep claims specific. Vague marketing language rarely survives summarisation. Third, maintain a consistent entity footprint -- the same company name, locations, and service categories across your site, directories, and profiles. Finally, treat earned media and expert commentary as distribution, not vanity. When a credible outlet repeats your framing, answer engines have another high-quality source to cite. That is why thoughtful placements on established New Zealand news platforms still compound. AI search will not replace websites. It will decide which websites get introduced before the click. Firms that write clearly for humans -- and structure content so machines can reuse it accurately -- will keep showing up in the rooms where deals begin. For operators building that visibility system, start with one service line, one buyer question, and one proof-backed article. Measure whether your brand is named in AI answers over the next quarter, then expand from what works. More detail on that approach is at https://publishing.torkmedia.com/.

AI Search Is Changing How New Zealand Businesses Get Found Online

AUCKLAND - For years, businesses have focused on improving their position in traditional search engine results. The goal was straightforward: rank highly enough that potential customers would click through to a website. As artificial intelligence becomes a more common way for people to find information, however, businesses are discovering that visibility inside AI assistants follows a different set of rules. Instead of presenting users with pages of links, AI assistants often generate a direct answer that includes only a handful of businesses or recommendations. In many cases, users receive the information they need without ever viewing a traditional search results page. This shift is changing how businesses think about online visibility. Rather than competing simply to rank well, companies are increasingly competing to be included in AI-generated responses in the first place. According to Auckland-based digital marketing agency Net Branding Limited, this emerging area of online marketing requires businesses to rethink how they present information online. The agency began researching AI-driven search well before the industry had settled on common terminology. Director Cathy Mellett became certified as an AI specialist in 2024, reflecting the company's early interest in understanding how artificial intelligence would influence customer discovery. "We recognised that AI assistants were beginning to answer questions differently from traditional search engines," Mellett said. "That raised an important question: what makes one business appear in those answers while another doesn't?" Smaller Businesses Can Compete One of the assumptions many businesses make is that larger websites automatically dominate every form of online discovery. Net Branding's research suggests that isn't always the case. The agency recently worked with a New Zealand online directory that was competing against much larger international review platforms. Rather than attempting to match the scale of those websites, the project focused on strengthening the directory's dining section by making it a clear, reliable source of local information. Within six weeks, AI assistants began referencing the directory in responses to local dining-related questions. In some cases, it appeared ahead of established global platforms such as TripAdvisor. The improvements extended beyond AI visibility. Search click-through rates increased from 1.0 percent to 2.3 percent compared with the previous year, while referral traffic from AI assistants rose by 246 percent, with ChatGPT accounting for the majority of those visits. "The assumption was that a small site could not compete with a platform of that size," Mellett said. "But an assistant is trying to answer a question, not simply rank domains. Clear, specific information can outweigh scale." What AI Assistants Look For Unlike traditional search rankings, AI assistants evaluate information differently. While the exact methods used by AI platforms are not publicly disclosed, practical experience suggests that several factors consistently improve the likelihood of being referenced. Accurate business information across directories and websites remains important. Clear descriptions of products and services help AI systems understand what a business offers. Independent references from reputable sources also contribute to credibility, while pages that answer genuine customer questions in straightforward language appear to perform better than content written primarily to target keywords. These principles align with a broader shift toward providing useful, trustworthy information rather than simply optimising for search algorithms. AI Visibility Complements SEO Despite growing interest in AI search, Mellett stresses that businesses should not abandon traditional search engine optimisation. For most organisations, conventional search continues to generate the largest share of website traffic. Instead, AI visibility should be viewed as an additional opportunity to reach potential customers. One difference is that an AI referral often arrives with a degree of implied trust. If an assistant recommends a business directly within its answer, users may perceive that recommendation differently than selecting from a list of search results. That makes inclusion within AI-generated responses increasingly valuable, even if the overall volume of traffic remains smaller than traditional search. There Are No Guaranteed Rankings One challenge for businesses is that AI assistants do not publish ranking factors in the same way search engines once did. Responses can also vary between users, platforms, and even repeated searches. As a result, businesses should be cautious about anyone promising guaranteed placement inside AI-generated answers. "Anyone promising guaranteed placement is selling something that does not exist," Mellett said. "You can improve your chances with accurate, well-structured and supported information." Testing Your Own Visibility For business owners wondering whether they appear in AI-generated responses, Mellett recommends a straightforward exercise. Ask AI assistants the same questions your customers would ask when looking for products or services. Then review which businesses are mentioned, how they are described, and whether your own organisation appears in the response. This process can reveal opportunities to improve online information while highlighting competitors that AI assistants currently consider authoritative. As AI continues reshaping how people discover businesses, understanding these new patterns is becoming increasingly important for organisations of every size. Businesses interested in learning more about AI visibility and digital marketing strategies can find additional information at https://netbranding.co.nz/. While traditional search remains an essential part of online marketing, the rise of AI assistants signals that visibility is no longer measured solely by rankings. Increasingly, success depends on whether a business provides the kind of accurate, useful, and trustworthy information that artificial intelligence can confidently recommend.