AI Revolutionizes Search: Google Adapts, Rivals Emerge

AI Is Taking Over Your Search Engine. Here's What It's Doing and Why It Matters

Expertise Artificial intelligence, home energy, heating and cooling, home technology. For decades, the way we find information on the internet changed only in small ways. Doing a traditional Google search today doesn't feel all that different from when, in the 1990s, you would Ask Jeeves. Sure, a lot has changed under the hood, the results are likely far more relevant and the interface has some new features, but you're still typing in keywords and getting a list of websites that might hold the answer. That way of searching, it seems, is starting to go the way of AltaVista, may it rest in peace. In May, Google announced the rollout of its new AI Mode for search, which uses a generative AI model (based on the company's Gemini large language model) to give you conversational answers that feel a lot more like having a chat and less like combing through a set of links. Other companies, like Perplexity and OpenAI, have also deployed search tools based on gen AI. These tools, which merge the functionality of a chatbot and a traditional search engine, are quickly gaining steam. You can't even escape AI by doing just a regular Google search: AI Overviews have been popping up atop those results pages since last year, and about one in five searches are now showing this kind of summary, according to a Pew Research Center report. I'm surprised it's not even more than that. These newfangled search tools feel a lot like your typical chatbot, like ChatGPT, but they do things a little differently. Those differences share a lot of DNA with their search engine ancestors. Here's a look at how these new tools work and how you can use them effectively. The underlying technology of a search engine is kinda like an old library card catalog. The engine uses bots to crawl the vast expanses of the internet to find, analyze and index the endless number of web pages. Then, when you do a search to ask who played Dr. Angela Hicks on ER, because you're trying to remember what else you've seen her in, it will return pages for things like the cast of ER or the biography of the actor, CCH Pounder. From there, you can click through those pages, whether they're on Wikipedia or IMDB or somewhere else, and learn that you know CCH Pounder from her Emmy-winning guest appearance on an episode of The X-Files. "When customers have a certain question, they can type that question into Google and then Google runs their ranking algorithms to find what content is the best for a particular query," Eugene Levin, president of the marketing and SEO tool company Semrush, told me. Generally, with a traditional search, you have to click through to other websites to get the answer you're looking for. When I was trying to figure out where I recognized CCH Pounder from, I clicked on at least half a dozen different sites to track it down. That included using Google's video search -- which combs an index of videos across different hosting platforms -- to find clips of her appearance on The X-Files. These multiple searches don't necessarily have to happen. If I just want to know the cast of ER, I can type in "cast of ER" and click on the Wikipedia page at the top. You'll usually find Wikipedia or another relevant, trustworthy site at or near the top of a search result page. That's because a main way today's search algorithms work is by tracking which sites and pages get most links from elsewhere on the web. That model, which "changed the game for search" when Google launched it in the 1990s, was more reliable than indexing systems that relied on things like just how many times a keyword appeared on a page, said Sauvik Das, associate professor at Carnegie Mellon University's Human-Computer Interaction Institute. "There's lots of cookie recipes on the web, but how do you know which ones to show first?" Das said. "Well, if a bunch of other websites are linking to this website for the keywords of 'cookie recipe,' that's pretty difficult to game." AI-powered search engines work a little differently, but operate on the same basic infrastructure. In my quest to see where I recognized CCH Pounder from, I asked Google's AI Mode, literally, "Where do I recognize the actress who plays Dr. Angie Hicks on ER from?" In a conversation that felt far more like chatting with a bot than doing searches, I narrowed it down. The first result gave me a list of shows and movies I hadn't seen, so I asked for a broader list, which featured her guest appearances on other shows. Then I could ask for more details about her X-Files appearance, and that narrowed it down. While the way I interacted with Google was different, the search mechanisms were basically the same. AI Mode just used its Gemini model to develop and process dozens of different web searches to gather the information needed, Robby Stein, vice president of product for Google Search, told me. "A user could've just queried each of those queries themselves." Basically, AI Mode did the same thing I did, just a lot faster. The approach here is called "query fan-out." The AI model takes your request and breaks it down into a series of questions, then conducts searches to answer those components of the request. It then takes the information it gathers from all those searches and websites and puts it together in an answer for you. In a heartbeat. Those searches are using the same index that a traditional search would. "They work on the same foundation," Levin said. "What changes is how they pull information from this foundation." This fan-out process allows the AI search to pull in relevant information from sites that might not have appeared on the first page of traditional search results, or to pull a paragraph of good information from a page that has a lot more irrelevant information. Instead of you going down a rabbit hole to find one tiny piece of the answer you want, the AI goes down a wide range of rabbit holes in a few seconds. "They will anticipate, if you're looking for this, what is the next thing you might be interested in?" Levin said. Read more: AI Essentials: 29 Ways You Can Make Gen AI Work for You, According to Our Experts The number of searches the AI model will do depends on the tool you're using and on how complicated your question is. AI Mode that uses Google's Deep Search will spend more time and conduct more searches, Stein said. "Increasingly, if you ask a really hard question, it will use our most powerful models to reply," Stein said. The large language models that power these search engines also have their existing training data to pull from or use to guide their searches. While a lot of the information is coming from the up-to-date content it finds by searching the web, some may come from that training data, which could include reams of information ranging from websites like this one to whole libraries of books. That training data is so extensive that lawsuits over whether AI companies actually had the right to use that information are quickly multiplying. (Disclosure: Ziff Davis, CNET's parent company, in April filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.) Not relying on training data is one thing that sets an AI-powered search engine apart from a traditional chatbot, even though the underlying language model might be largely the same. While ChatGPT Search will scour the internet for relevant sites and answers, regular ChatGPT might rely on its own training data to answer your question. "The right answer might be in there," Das said. "It might also hallucinate a likely answer that isn't anywhere in the pre-training data." The AI search uses a concept called retrieval-augmented generation to incorporate what it finds on the internet into its answer. It collects information from a source you point it to (in this case, the search engine index) and tells it to look there instead of making something up if it can't find it in its training data. "You're telling the AI the answer is here, I just want you to find where," Das said. "You get the top 10 Google results, and you're telling the AI the answer is probably in here." While an AI chatbot like Gemini is more of an assistant there for long conversations, AI Mode is all about retrieving information, Google CEO Sundar Pichai said during a recent earnings call. "I think where the queries are information-oriented, but people really want to rely on the information, but have the full power of AI. I think AI Mode really shines in that," he said. These AI-powered search tools might be more reliable than just using a chatbot itself, because they're pulling from current, relevant information and giving you links, but you still have to think critically about it. Here are some tips from the experts: Consider how bad people are at telling when you're sarcastic on the internet. Then think about how bad a large language model might be at it. That's how Google's AI Overviews came up with the idea to put glue on pizza -- by pulling information from a humorous Reddit post and repeating it as if it were real culinary advice. "The AI doesn't know what is authentic and what is humorous," Das said. "It's going to treat all that information the same." Remember to use your own judgement and look for the sources of the information. They might not be as accurate as the LLM thinks, and you don't want to make important life decisions based on somebody's joke on an internet forum that a robot thought was real. Even though they're supposed to be pulling from search results, these tools can still make things up in the absence of good information. That's how AI Overviews started creating fake definitions for nonsensical sayings. The retrieval-augmented generation might reduce the risk of outright hallucinations but doesn't eliminate it, according to Das. Remember that an LLM doesn't have a sense of what the right answer to a question is. "It's just predicting what is the next English word that would come after this previous stream of other English words or other language words," Das said. "It doesn't really have a concept of truthiness in that sense." Traditional search engines are very hands-off. They will give you a list of websites that appear relevant to your search and let you decide whether you want to trust them. Because an AI search is consolidating and rewriting that information itself, it may not be obvious when it's using an untrustworthy source. "Those systems are not going to be entirely error-free, but I think the challenge is that over time you will lose an ability to catch them," Levin said. "They will be very convincing and you will not know how to really go and verify, or you will think you don't need to go and verify." But you can check every source. But that's exactly the kind of work you were probably hoping to avoid using this new system that's designed to save you time and effort. "The problem is if you're going to do this analysis for every query you perform in ChatGPT, what is the purpose of ChatGPT?" Levin said.

Google Neutralizes Its Rivals... For Now

Armed with new data showing AI actually boosts search volume, the tech giant has turned a perceived threat into a powerful new weapon. For over two decades, “Google it†has been the default way to find answers online. Now that dominance is being tested by a new wave of AI tools like OpenAI’s ChatGPT and upstarts such as Perplexity, which deliver conversational answers instead of a list of links. These disruptors are being cast as a mortal threat to Google Search, long the undisputed king of the internet. But on Wednesday, Google CEO Sundar Pichai delivered a powerful counter-narrative, armed with staggering new data that suggests the AI "threat" is actually making its core product stronger than ever. The story Google is telling is not one of defense, but of offense. Far from cannibalizing its search business, AI is encouraging people to search more, ask new kinds of questions, and engage more deeply with the platform. “We see AI powering an expansion in how people are searching for and accessing information, unlocking completely new kinds of questions you can ask Google,†Pichai said in remarks for the company’s Q2 earnings call. "Overall queries and commercial queries on Search continued to grow year over year. And our new AI experiences significantly contributed to this increase in usage." Pichai revealed that the company's new AI features are now driving “over 10% more queries globally†for the types of searches that show them, a clear sign that AI is expanding the pie, not just slicing it differently. At the heart of Google’s strategy is a two-pronged approach designed to serve both casual users and power users simultaneously. The first approach is AI Overviews, the AI-generated summaries that now appear at the top of many search results. This feature has been rolled out at a massive scale, now serving, Pichai claims, over 2 billion monthly users across more than 200 countries and territories. It’s the mainstream integration designed to make everyday search faster and more efficient for the masses. The second axis is AI Mode, an end-to-end conversational search experience for more complex and nuanced questions. While still rolling out, this power-user tool has already attracted, the CEO says, over 100 million monthly active users in the U.S. and India. This is Google’s direct answer to the advanced capabilities of its new competitorsâ€"ChatGPT and Perplexityâ€" offering a space for deeper exploration within Google ecosystem. According to Google, this evolution of search is resonating most strongly with the users who will define the next decade of the internet: young people. Pichai emphasized that the growth in new search behaviors, particularly multimodal searchâ€"using tools like Google Lens or Circle to Search to ask questions with imagesâ€"was “most pronounced among younger users.†By integrating AI in a way that feels intuitive and powerful to a generation that has grown up with visual communication, Google wants to make sure it stays relevant. The ultimate validation of this strategy lies in the numbers. In a direct rebuttal to fears that AI would kill its golden goose, Alphabet reported $54.19 billion in second-quarter search revenue, up 12% year-over-year. The AI-powered experience is proving to be not just engaging, but highly lucrative. Chief Business Officer Philipp Schindler noted during the earnings' call with analysts that advertisers using the company's new AI-powered tools are seeing tangible benefits, with AI Max campaigns delivering “14% more conversions†on average. This proves that a more complex, AI-driven search experience can be even more valuable for advertisers, he claimed. OpenAI’s ChatGPT and smaller players like Perplexity AI are winning early adopters who prefer direct, conversational responses over Google’s traditional list of blue links. These platforms summarize and synthesize information instantly, bypassing the need to click through multiple sites. This shift threatens Google’s core business model: search advertising. A shift from traditional search to AI-generated answers could reshape how people consume information online. Instead of clicking through multiple sources, users may rely on a single AI response, potentially concentrating power in fewer platforms and reducing traffic to independent publishers. For Google, the challenge is to evolve fast enough to keep its users while preserving the revenue streams that make up the bulk of its business. "We'll focus on the organic experience for the near term," Pichai told analysts. Google is not simply adding AI to its old search box to keep competitors at bay. It’s building an entirely new information engine, one designed to answer questions people never even thought to ask. The AI race has forced Google to evolve fast, and it could make Search more indispensable, and more profitable, than ever. Google wants to stay the gatekeeper of how we access information.

No more links, no more scrolling -- The browser is becoming an AI Agent

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Rumors that OpenAI is set to release a gen AI-powered web browser to rival Alphabet's Google Chrome have amped up excitement about the future of search and how AI will fundamentally change how we browse the web. In this seeming next phase of the internet, search engines won't just point to information; intelligent agents will find it for us and even act on it. "This isn't just about better answers; it's about redefining the interface between humans and the web," Ja-Naé Duane, a Brown University faculty member and MIT CISR research fellow, told VentureBeat. "By embedding a conversational, task-completing AI into the browser itself, OpenAI is signaling the end of search as we know it." What exactly is gen AI-powered search? Gen AI-powered search is fundamentally different from traditional search, as it not only fetches the most relevant links in response to a query, but summarizes and directly links to them. Users won't have to scroll URLs, websites or databases to get the information they need. For enterprises, this means that SEO may eventually become obsolete, so they must fundamentally rethink their online strategy. Presumably, OpenAI's goal is to keep users inside GPT-like interfaces as long as possible. A dedicated browser would allow the company to directly integrate products such as Operator, which handles repetitive browser tasks. The latter, ultimately, is the future of AI-powered search, experts say: Agents that fetch information for users and get to know their habits, interests and goals. "We're moving into an era where the browser doesn't just respond, it anticipates," said Duane. "The future of search is not about finding, it's about fulfilling." The current gen AI-powered search landscape Whenever OpenAI enters the gen AI-powered search space, it will face a slate of competition, including from Perplexity, Dia, Arc, Andi, Bagoodex, Komo You.com and others. Notably, Perplexity's Comet was launched earlier this month, but is currently only available to customers on the $200-per-month tier. The company says it will roll out the browser to additional users on an invite-only basis, and eventually make it free. Perplexity is "excellent for deep research," noted Wyatt Mayham of Northwest AI Consulting, but its current price tag gears it toward power users, not the mass market. Perplexity is "fast, task-oriented" and being increasingly adopted in knowledge work, noted Johnny Hughes, co-founder and CMO at marketing and advertising firm Avenue Z. "The issue? Source transparency and trust are still hit or miss," he said. You.com, Arc and others also have good user interface (UI) experimentation, but "lack scale, funding or core differentiators." Dia, meanwhile, as Mayham put it, is "rethinking the browser from scratch with modular AI features, but faces the uphill battle of adoption in a space dominated by incumbents." And, its intent-sensitive automation is also more constrained. Incumbents have also taken steps to compete. Chrome has introduced AI Mode and Bing offers Copilot search, while Firefox, DuckDuckGo and others have incorporated AI chatbots and sidebars, as well as integrated AI summaries into search results. Still, these are more conservative and remain closer to traditional assistive search, and are beholden to ad revenue models and legacy UX. OpenAI's potential advantage in search What could set ChatGPT apart from the others is its strong market share, deep industry partnerships -- and the fact that it has 500 million weekly active users. Experts say one advantage is its task-oriented nature. "Instead of giving you a list of links, their upcoming browser agent aims to complete actions (book a flight, order groceries, handle forms)," said Mayham of Northwest AI Consulting. "That's a different model than Google's ad-driven approach and has major implications for how discovery happens online." It is indeed a "big shift in mental models," agreed Hughes of Avenue Z. Google was built to index and rank, while OpenAI is engineered to understand, synthesize and serve intent-based outcomes. "They're not trying to 'crawl the web,' they're trying to comprehend it," he said, emphasizing that today's users are searching for direct answers, not just links. OpenAI's advantage over rivals is its massive developer ecosystem, built-in user behavior via ChatGPT and direct feedback loops from billions of prompts. Where Perplexity functions as a powerful agentic assistant, and Gemini augments search with context and extensions, "OpenAI is positioned to become the OS layer of the internet," said Hughes. But can OpenAI really topple Google? The browser wars have been ongoing for years, and Chrome remains the far-and-away dominant player. According to marketing intelligence firm Datos, the tech giant maintained a 90.15% share of the U.S. user base and 92.49% in Europe between Q1 2024 and Q1 2025. By contrast, ChatGPT accounted for just 0.29% of desktop events in the U.S. and 0.32% in Europe. "Short of a miracle, I have a hard time seeing any new browser having any kind of material impact on Google's browser dominance for quite some time, if at all," said Eli Goodman, Datos' CEO and co-founder. AI tools will show value in areas including summarization, research acceleration and "mitigating tab fatigue," he said. "But an existential threat to Google? Not yet." For AI browsers to truly disrupt the market, they'll need to prove that their end-to-end experience is not just faster or smarter, but consistently more useful than what users already know, he noted. ChatGPT is strong at answering well-formed questions using its internal knowledge and language reasoning, but it lacks access to real-time, long-tail and less-indexed web content, said Vladyslav Hamolia, AI product lead at Mac app builder MacPaw. "This is where a traditional browser-plus-search engine still plays a key role, surfacing newly published pages, live prices, event-specific updates or in-depth technical documentation," said Hamolia. "The browser is not just a UI layer; it's a gateway to navigating and filtering a vast, dynamic web that models alone cannot fully absorb." Google remains dominant in crawling depth (with two decades of crawling infrastructure), semantic understanding of web structure (sitemaps, structured data) and personalized relevance, he noted. Brian Jackson, principal research director at Info-Tech Research Group, pointed out that Chrome users also likely use Gmail, Google Calendar, Google Docs and other Google platforms. "OpenAI and Perplexity don't have that same gamut of services." However, if their AI agents can begin replacing more Google tools beyond search, they can win some market share. "We also have to consider what strategy OpenAI and Perplexity take with their browsers," said Jackson. "Right now, Perplexity makes Comet available only for its paying users, so at the moment, it's more of an added value to draw in subscribers rather than trying to win browser market share." Advantages and disadvantages of AI web browsers The advantages of AI search may not be truly seen for some time, said Info-Tech's Jackson. While Comet touts its ability to summarize and translate every page instantly, that's not so different from what can be accomplished with Chrome -- especially once you consider its extensive library of available extensions. "These AI browsers will literally be trying to interpret the goal of users," he said. "They will make suggestions, offer to automate routine tasks, find product comparisons or source multiple quotes for services. "Browsers could transition from being mere windows to web content to agentic assistants that help users achieve their digital goals." On the other hand, resistance to new technology is always a factor, he pointed out. Users who reject the AI summaries they see in core search will likely also reject the notion that AI should be at the forefront of browsing. "The early days of user experience will be important here, and if we see browsers recommending that users put glue on pizza or other silly things like that, it won't help with adoption," said Jackson. Another distinguishing factor with AI search is models' ability to persist memory across sessions and assist with task execution in-browser. "The risk, however, is user trust," said Kaveh Vahdat, founder and president at fractional CMO agency RiseOpp. "A browser that thinks and remembers raises legitimate privacy concerns unless boundaries are clearly defined." Moving from static search bars to dynamic AI interfaces that learn, adapt and integrate with internal systems also introduces new exposure points, especially when proprietary data is surfaced by models operating across public and private content, he noted. Enterprises must be prepared to revisit access controls and ensure AI agents align with governance and compliance standards. "These tools are converging in functionality but diverging in user control," said Vahdat. "The key differentiator may not be capability, but how well each platform balances autonomy with transparency." What enterprises should do now Whether sooner or later, how should enterprises prepare for a new search environment where SEO is no longer relevant? Think of your site as a reference point for AI systems, advised Mayham of Northwest AI Consulting. Content should be clear, factual and structured so AI tools can easily surface information. Also, prepare for conversational commerce by ensuring product data and checkout flows are API-friendly and that AI agents can complete transactions without friction. Additionally, invest in brand authority; if AI cites sources, it'll use a brand name, not just keywords. "Brand trust is critical," said Mayham, and is achieved by being featured on other authoritative websites or reviewed well on review platforms. "Enterprises should stop thinking in blue links and start building content that answers, reasons and resonates," agreed Avenue Z's Hughes. This means: * Structuring content with AI comprehension in mind (schema, embeddings, FAQs) * Prioritizing expert-driven, evergreen content that large language models (LLMs) trust * Diversifying beyond Google (social search, TikTok SEO, YouTube, voice) * Training internal teams on prompt engineering and AI integration Ultimately, it is critical to make the customer experience interoperable with agentic AI, emphasized Brown University's Duane. "Soon, users won't be browsing; they'll be delegating," she said. "You need to prepare your systems not just to be found, but to be understood by AI."

The Google Search era internet is dying. Here comes AI

A version of this article originally appeared in Quartz's members-only Weekend Brief newsletter. Quartz members get access to exclusive newsletters and more. Sign up here. Everyone knows traditional search is dying. No one quite knows what comes next. ChatGPT hit 500 million monthly active users in May 2025 -- the same month Google launched AI Mode, essentially admitting that large language models are the future of search. According to the Pew Research Center, about 1 in 5 searches now include AI Overviews, with the feature appearing in 60% of question-based searches and 36% of full-sentence searches. Meanwhile, according to Adobe, traffic to retail sites from AI tools has surged 1,200% since last summer. But the rise of AI search comes with a brutal cost for traditional websites. According to the same Pew research, searches with AI Overviews result in dramatically fewer clicks to other websites. When Google shows an AI summary, users click through to other sites just 8% of the time, compared to 15% for searches without AI answers, which represents a nearly 50% drop. Even worse, only 1% of AI Overviews generate clicks to the sources they cite. For marketers, this represents nothing short of an existential crisis. Unlike Google's algorithm, which has been reverse-engineered and optimized for over two decades, AI search remains largely opaque. What's emerging from the chaos is a discipline marketers are calling GEO (Generative Engine Optimization) or AIO (Artificial Intelligence Optimization), essentially SEO for the AI era. But unlike traditional search optimization, which followed somewhat predictable patterns, AI optimization feels more like reading tea leaves. The fundamental shift is philosophical. Where Google's algorithm hunted for relevance and authority, AI models prioritize utility and resolution. Instead of optimizing for broad terms like "running shoes," some experts now recommend brands to rank for detailed queries like "best running shoes for flat feet under $150 with good arch support." "LLMs are not optimizing for attention; they are optimizing for resolution," according to a Harvard Business Review report who studied how brands appear in AI recommendations. "Identifying the 'job to be done' thus becomes the number one priority for brand leaders." This has created an awkward period where traditional marketing expertise suddenly feels obsolete. The keywords and backlinks that once guaranteed visibility mean little to large language models that prioritize different signals entirely. In the absence of clear guidelines, marketers are trying everything. Some are posting obsessively on Reddit, hoping to influence the training data that OpenAI licenses from the platform. Others are creating highly structured content like FAQ sections, detailed product specifications, and comparison charts that AI models can easily parse and cite. The panic has spawned a new industry. At least a dozen startups are now developing tools to help brands navigate AI search, according to The Wall Street Journal. Athena, launched by former Google search team member Andrew Yan, raised $2.2 million and now has more than 100 customers. "Companies have been spending the last 10 or 20 years optimizing their website for the '10 blue links' version of Google," Yan told the Journal. "That version of Google is changing very fast, and it is changing forever." Startups like Profound, which raised $3.5 million to help brands optimize for AI search, generate thousands of variations on search prompts and track how often their clients appear in AI responses. It's a brute-force approach to cracking an algorithmic black box. "Every brand on the planet has one new, very big, very important customer that's called ChatGPT," James Cadwallader, Profound's CEO told The Information. This philosophy represents a fundamental challenge to the optimization mindset that has dominated digital marketing for decades. If AI search engines can't be gamed, what happens to the hundreds of billions of dollars in digital advertising that has grown up around manipulating algorithms? Brands that fail to appear in AI search results don't just lose traffic -- they become invisible. Unlike Google, where even poorly optimized sites appear somewhere in results, AI models either feature brands prominently or ignore them entirely. There is no "page two" of ChatGPT. For marketers accustomed to having some control over their digital destiny, this binary outcome feels terrifying. Either you're part of the conversation or you're not, and the rules for inclusion keep changing. Of course, this cutting-edge technology might end up borrowing some old tricks. Generative AI is expensive to run, and advertising is how the internet has always paid its bills. OpenAI is now considering incorporating ads into ChatGPT, according to reports, while Perplexity has already begun experimenting with sponsored searches. If AI search platforms start selling ad space, marketers may find themselves back in familiar territory, buying their way to visibility just like they do on Google today. Some things never change, after all.

The AI Boom Is Expanding Google's Dominance

Google became popular by offering a tool that was better than others at collecting links, ranking them, and making them searchable. It has made many billions of dollars by sending browsers this way and that, providing value to searchers and advertisers and website operators and taking tolls along the way. It built an advertising business around Search, and an empire around that business. Then came generative AI. Google, an early innovator in the space, stumbled into action after ChatGPT went viral, rolling out its own chatbots and image and video generators and installing AI-powered features across its product line. It was initially cautious with Search, its most valuable and contested property, but has since pushed ahead: first, with AI Overviews, which answer a wide range of queries with generated answers instead of a list of links, and then with a preview of "AI Mode" in Search, which replaces the standard search experience with a chatbot attached to a web crawler. Google's official story -- and prevailing press narrative -- has been one of a company meeting a new challenge, embracing a new technology, and fending off fresh competition. But the story of a stunned and beleaguered Google understates just how powerful their position was, and the extent to which they've been able to leverage it, already, in the age of generative AI. Here's another way to tell it: Google built and maintained the world's most extensive index of the web, a ranked and sorted database of as much online human activity and output as it could find. Then, under the auspices of a pivot to AI, it started treating that information as its own, first by incorporating it into its models and then by using those models to generate content for users instead of sending them to an outside source. This is a meaningful change in Google's relationship to "the world's information," to borrow its favored term, less clearly about making it "universally accessible and useful" than about incorporating it directly into a proprietary product. It's also a somewhat better background for understanding why the company is doing so incredibly well, per CNBC: Alphabet reported second-quarter results on Wednesday that beat on revenue and earnings, but the company said it would raise its capital investments by $10 billion in 2025. Shares of the company were up as much as 3% in after-hours trading. The company's overall revenue grew 14% year over year, higher than the 10.9% Wall Street expected. Some of the biggest contributors to Google's blockbuster quarter had little to do with AI -- YouTube advertising in particular is growing extremely fast -- but it's clear that Google, in the early stages of its remodeling of Search, has found a pretty good way to squeeze more value out of the web: by incorporating it into a chatbot, and installing that chatbot on top of Search. Companies like OpenAI could still represent a long term threat to Google -- as could the United States government -- but for now, things are going very well. As any website or online business with an analytics dashboard could have told you for the better part of a year, this has had some consequences outside of Google. The company has pushed back against reports that Search has been sending fewer people to outside sources; last month, Alphabet CEO Sundar Pichai told The Verge that, actually, if you take into account all forms of online content, we're in an "expansionary moment," and also that the number of websites available to them -- a strange metric that might be affected by the widespread availability of automatic website and content generation tools -- has "gone up by 45 percent in the last two years alone." Elsewhere, numbers are telling a clearer story. In a June interview with Axios, Matthew Prince, CEO of internet infrastructure company Cloudflare, shared some internal data. "Ten years ago," he said, "for every two pages [Google] scraped, they sent you one visitor." Ten years later, he said, "for every six pages that Google scrapes, they send you one visitor." In the six months before June, he said, the ratio had shifted dramatically: "The traffic ratio now is for every 18 pages that Google takes from you, you get one visitor." This week, Pew added its own data to the mix: Users who encountered an AI summary clicked on a traditional search result link in 8% of all visits. Those who did not encounter an AI summary clicked on a search result nearly twice as often (15% of visits). Google users who encountered an AI summary also rarely clicked on a link in the summary itself. This occurred in just 1% of all visits to pages with such a summary. Given that AI summaries are both a feature and a preview of the general direction of Search -- you can think of them, as well as AI Mode, as tests for a more complete redesign to the core product, that 1 percent figure really sticks out. Google really is burying the web. After this week's earnings report, Google chief business officer Phillip Schindler explained why the company was doubling down. "[AI Overviews] continue to drive higher satisfaction. They continue to drive higher search users. They're scaling up very nicely," he said, giving the company a "really strong base on which we can then innovate and drive actually more innovative and new and next-generation ad formats." As AI features claw back traffic, they're driving search growth, in other words, which Google is pretty sure it can monetize more than it already does. This dynamic gets a lot of attention in part because "the web" encompasses a great deal of conversation about what the company is doing, not just in the commercial media but on forums like Reddit; in hindsight, it may end up being a marginal story in the development of a much more expansive and weirder online world. But it will also be an instructive one. In the same earnings call, Pichai was more candid than usual about what an AI-forward Google might mean for its partners, or for the many parts of the economy with some adjacency to Google: Just like the early days of the web, there are aspects about it that will expand access, grow the use cases, etc. And I think those elements are there. But I do think it's important. It's not just a technology claim, but we have to solve the business models for the varying players involved. This was in response to a question that mentioned so-called "agentic" AI, meaning tools that are intended to carry out tasks on behalf of users. In Google's vision of the future, the company's chatbots won't just mediate searches, but interact with a much wider range of businesses, whether it's e-commerce, travel, or through tasks done for work. It's a broader version of a familiar relationship: Google collects a bunch of partners, sends its users around to interact with them, and collects its fares along the way. A similar arrangement helped expand and commercialize a web that was relatively small when Google first got started, perhaps a do-it-all chatbot assistant will create similar opportunities online and off. If it does, though, Google -- and other companies now pursuing similar models -- will accrue incredible leverage and power. At some point, like last time, they might just decide to use it.

Predictive AI Search Is Here -- Is Your Brand Ready for It?

In the past, search was all about keywords -- you typed in what you needed, whether it was a product, service or piece of information. But now, search is evolving into something smarter, something that can anticipate what you're looking for before you even start typing. This shift toward predictive search capabilities is not just a technological leap; it's a seismic change in how businesses connect with intent, personalize experiences and drive conversions. For digital marketers, product teams and CX leaders, understanding the mechanics and applications of predictive AI in search is no longer optional; it is part and parcel of success. Related: Want to Rank in AI Search? Focus on These Sources Search used to be reactive, which means that a person has a need and they type it out into a search engine in order to find an answer. Based on that practice, brands optimised for what people were searching for, utilising keywords, trends, SEO tactics and other methods in order to be ranked by search engines and be found by people. But it responded instead of anticipated. These methods required users and consumers to make the first move. In 2025, predictive AI is flipping the script. Instead of waiting for consumers to express intent, platforms are now learning to recognise patterns, analyze behaviors and predict probable actions. That means consumers are seeing content, products or answers they were about to search for, sometimes even before realising they needed it. This shift is part of a broader movement toward proactive digital experiences, powered by big data, machine learning and hyper-personalisation. That isn't to say that search is dead, but it is becoming increasingly invisible, ambient and eerily prescient. At the heart of predictive search is an algorithmic cocktail: machine learning, natural language processing, deep behavioral analytics and vast datasets pulled from across channels -- web activity, location data, app usage, purchase history and even social media sentiment. AI models today can map micro-behaviors like scroll speed, dwell time or mouse hover to determine intent. How long you spend on a website or watching a TikTok video will all play into the content that will be shown to you across the board. Whether you are logging onto a shopping platform or a social media platform, your behaviors will carry forward and offer you similar things that you might be interested in. For example, if a user browses organic skincare on Instagram, likes a product review and then opens a wellness app later in the day, an AI-driven search platform could predict that they're likely to seek "best clean moisturisers for sensitive skin" later that evening -- and serve that result proactively, even before the user searches. The tech giants are locked in a quiet arms race to own the predictive future. Google's Search Generative Experience -- now fully mainstream in 2025 -- uses AI to blend traditional search with contextual understanding, generating summaries and proactive suggestions based on intent, not just input. Microsoft's integration of Copilot into Bing and Microsoft 365 has also led to smarter enterprise search. Employees no longer have to look up files or protocols; they're suggested in the workflow before the query forms. Both platforms are investing heavily in LLMs (Large Language Models) fine-tuned for intent prediction, not just language generation. The goal: remove friction and surface what users need before they ask for it. Related: How to Control the Search Results For Your Name For brands, this is a goldmine of opportunity -- but only if they're prepared. Predictive AI doesn't just change how users search; it changes how businesses must structure, tag and deploy their digital content. Here's how brands are responding: 1. Creating content for "pre-intent" moments. Instead of focusing solely on transactional keywords ("buy running shoes"), forward-thinking marketers are now creating content for precursor behaviors. That means that consuming information like "How to avoid knee pain when jogging" or "Signs your shoes need replacing" will alert AI algorithms to show you the best shoes that protect your knees. It's about mapping the customer journey upstream, anticipating the questions that come before the conversion, and positioning your brand as the default source before the user is even aware of their need. 2. Structured data and AI-friendly taxonomy. To appear in predictive search, content must be easy for machines to read and index. Brands are investing in structured data, semantic markup and content taxonomies designed for AI interpretation. This helps AI systems link product attributes, FAQs and guides to broader intent signals. So the next time you search for "how to pet-proof a rental apartment", you'll likely get ads with products tagged with things like "pet-proof", "small-space friendly" or other pet-related products and furniture that are non-destructive and ideal for rental spaces. 3. Integrating first-party data with predictive engines. Brands with strong CRM and loyalty ecosystems are integrating first-party data with predictive platforms. This includes purchase cycles, user preferences and engagement history. When done ethically and securely, this allows companies to anticipate individual needs with astonishing precision. A beauty brand, for instance, might know that a customer repurchases foundation every six weeks. In week five, a push notification appears: "Running low? Your shade is in stock -- and 10% off today." Related: The Most Successful Founders Take Retreats -- Here's Why You Should, Too One of the biggest debates in 2025 is where the line lies between convenience and intrusion. Predictive AI walks a fine line between helpfulness and creepiness. Consumers are growing more aware of how their data is used -- and more selective about who gets access to it. This has led to a renewed focus on consent-based tracking, zero-party data and transparency. Companies that overstep with overly personal or mistimed suggestions risk backlash and lost trust. The key is relevance without overreach. Predictive search must feel like intuition and not like surveillance. For one consumer, getting a "rain expected this weekend - here are your most-viewed waterproof boots at 15% off" might signal convenience, but for another, it might feel like tech is encroaching on their privacy... but AI models will be able to glean consumer behaviors and dole out the appropriate approach for each consumer. For the latter consumer, AI models might subtly provide ads that are targeted at their subconscious needs or desires rather than their current situation. For example, drawing information from their stress indicators or mood predictors, AI models may provide weekend getaway ideas with the current deals and promos. This not only offers what the stressed user might need, but it also doesn't feel too hard-sell, which can be a turn off for some. As predictive AI reshapes search, here's how marketers can future-proof their strategy: We're entering an era where search is no longer a conscious act but a seamless service. Predictive AI in 2025 is transforming how intent is understood, how brands are discovered and how decisions are made. It rewards those who can think ahead about their customers, their data and their digital footprint. For businesses willing to embrace this shift, the payoff is enormous: smoother journeys, higher engagement and deeper loyalty. Because in the end, the smartest brands won't wait for their customers to ask -- they'll already be there with the answer.

Google's AI Mode will 'fundamentally redefine' digital ad industry | Digital | Campaign India

Adland reacts to Google's latest update after AI Overviews lead to a 79% drop in click-through rates to websites. Google rolled out its "most powerful" AI search yesterday (29 July) with AI Mode in the UK. Appearing as a tab on Google Search, it has more advanced reasoning, and using Gemini 2.5, people can type, speak or take a photo to begin a query, and it has the ability to "go deeper" with follow-up questions and links to web pages. Jon Mew, the chief executive of IAB UK, the industry body for digital advertising IAB UK, said: "Google's decision to introduce AI Mode within its UK search offering is a profound shift that will fundamentally redefine the shape of the digital ad industry going forwards." After already being rolled out in the US and India, it is now available in the UK. Google confirmed as part of this roll-out there will not be ads in AI Mode in the UK. Mew added: "No-one is under any illusion that AI innovation is moving at pace and it's inevitable that models will change along with that. The challenge for the rest of the industry is to keep pace, particularly publishers who are understandably concerned about how the changing search landscape will impact their traffic levels." Nearly half (47%) of all digital adspend in the UK is invested in search advertising. IAB UK's AI Compass forecasts that approximately 33% of total search advertising spend will be redirected towards AI-powered search interfaces, or "answer engines", by 2028, which will impact how consumers engage with content and change the opportunities for advertisers. AI Mode follows the launch of AI Overviews last year, disrupting the SEO landscape and causing concern for publishers whose content appears in AI answers, negating the need for users to click through, as well as pushing organic search results further down the page. Chris Shelbourn, head of technical SEO at IDHL, a digital marketing agency in the UK and US, said: "This isn't the end of SEO, it's an evolution. Based on our early insights from the US rollout of AI Mode (and previously, AI Overviews), we've seen a drop in clicks for some clients but also a significant rise in impressions and, in many cases, stronger conversion rates from the traffic that does land. In other words, the quality of traffic is improving even if volume fluctuates." AI Mode is designed to answer more complex search queries in a more "intuitive" way with multi-part questions and follow-ups. Google said that it is intended for exploratory questions and for more complicated tasks like comparing products, planning a trip or how-tos. The tech giant claimed that early users of AI Mode are asking questions two or three times the length of traditional search queries. For example: "Things to do in Edinburgh this weekend with friends. We're big foodies who like music but also chill vibes and exploring off the beaten track." Or: "How do migrating birds know where to go?" Claire Elsworth, strategy director at performance marketing agency Impression, said Google is "fundamentally changing how we expect information to be surfaced from a search behaviour", adding that AI Mode will get traction "not because it's shiny and new, but because it's been dropped straight into the path of least resistance". Elsworth explained that "yes, traffic might go down", but content can still perform. Marketers need to look at new signals, adding: "This is a different kind of visibility." She explained: "The experience is built to feel more human, more like chatting to a very knowledgeable friend. For marketers, that means we're not just trying to 'rank' any more, we're trying to be part of an infinite number of individual conversations. Planning and optimising for that is a very different ballgame to what we've been playing for the last couple of decades. "The content that gets picked up will be the most useful, the most clearly explained, the most structurally sound, and the most relevant on a case-by-case basis. Brand strength and talkability will matter for credibility signals, but structured content will matter for the long tail of intent." In Google's blog post announcing AI Mode, it said it will continue to evolve the search experience and that with AI Overviews, it claims users are visiting a greater diversity of websites for help with more complex questions. "When people click from search result pages with AI Overviews, these clicks are higher quality for websites -- meaning users are more likely to spend more time on the sites they visit," it said. Shelbourn added: "For ecommerce and lead gen brands, that's often meant bottom-line gains, not losses. As Google continues to surface more answers directly in search, brands that invest in useful multi-format content, develop trusted brands and provide great user experience will be best positioned to benefit." Google's AI Overview is "yet another wake-up call" for advertisers Despite Elsworth's perspective that AI Overview leads to "higher quality" clicks, the tool has led to a 79% drop in click-through rates to websites. Research from Authoritas has found that a site previously ranked first in a search result could lose 79% of its traffic from a question if results were delivered beneath an AI overview. News publications have already felt the effects. Carly Steven, Mail Online's director of SEO and editorial ecommerce, said in May that there was a "pretty profound change in clickthrough". When an AI Overview appeared for a query, Steven said that the Mail's average clickthrough rate was 56.1% lower on desktop and 48.2% lower on a mobile device. Simon Gayle, partner and head of digital transformation at Bicycle London, said that for advertisers it was "yet another wake-up call". She added: "Newsbrands have always delivered a high-attention environment rooted - in theory at least - in trust and context, something generative summaries can't replicate. "If we sleepwalk into a world where original journalism is replaced by AI regurgitation, we lose the oxygen that feeds brand trust, cultural relevance, and informed, engaged audiences." Media agencies such as Bountiful Cow and media owners Sky Media have been campaigning for more media spend on newsbrands, which have already suffered from a lack of investment. Presenting at Media 360 earlier this year, Sky Media's director of planning Sarah Jones said: "As the media industry, you're sentencing news to death, because, without any adspend, news as we know it will not prevail into the future." Charlotte Powers, chief digital officer at Bountiful Cow, called AI Overviews a "major disruption". She added: "For news brands, fewer clicks mean fewer opportunities to build direct relationships with readers, threatening subscription and ad revenue models." On how this might force advertisers to adapt, she said they would have to invest "more heavily within Google's ecosystem to compensate for the shortfall delivered through paid search". More drastically, she added, publishers and advertisers will have to diversify into other channels such as newsletters to maintain audiences. SEO and pay-per-click strategies will also need to be rethought, with measurement "shifting away" from click-based metrics. However, Ben Foster, chief digital officer at The Kite Factory, said Google did have to evolve as younger generations change how they search for information. He also thought that SEO strategies would have to change and already were, with "marketers reallocating efforts towards optimisation for large language models like ChatGPT". "You would expect AI results that still nod to external links, especially where there's monetisation potential, but in a format that integrates paid placements seamlessly into the experience."

1% click-through rate: How Google AI Overviews is killing publishers

New research from Pew shows just how dramatically AI-generated summaries are changing search behaviour, and the impact isn't good news for publishers. Users are less likely to click on search result links when an AI-generated summary is presented, according to new data from Pew Research Centre. According to the report, which surveyed 900 US adults in March 2025, users click on links within the AI summary itself only 1% of the time and the click-through rate on search result links declines heavily when AI-generated summary is present. Without an AI summary, the click-through rate is 15%; whereas with one, it drops down to 8%. Browsing sessions are also more likely to end after seeing an AI summary (26%) compared to without (16%). AI summaries are becoming more common with 58% of participants stating they've encountered at least one. Three-fifths (60%) of searches beginning with 'who', 'when', or 'why', generated a summary and so did prompts that used questions, full sentences, or longer phrases. Just over half (53%) of searches with 10 or more words produced AI summaries, while only 8% of one or two-word searches did. By March 2025, 18% of all Google searches had generated an AI summary. Wikipedia, YouTube, and Reddit accounted for 15-17% of the links across both AI summaries and regular results, while news websites appeared equally in both formats (5%). Pushback from publishers In July, Google officially launched AI-generated summaries in the discover feed within its smartphone search app (iOS and Android) for users in the US. Instead of headlines, users now see AI-generated summaries accompanied by small publisher logos linking to source sites. A disclaimer reads: "Generated with AI, which can make mistakes." There has been no official launch date for Asia Pacific set yet. Publishers fear a further decline in traffic due to zero-click searches, when users get their answer from the summary. Entertainment news publishers like Giant Freakin Robot have been significantly impacted by AI overviews. In November last year, the independent publisher had to announce it is shutting down, nearly six months after Google launched AI Overviews, due to a drastic drop in search traffic. At the start of this month, a group of independent publishers filed a formal antitrust complaint against Google with the European Commission, targeting its AI Overviews feature. The complaint included a request for interim measures to prevent what publishers described as "irreparable harm". The UK Competition and Markets Authority (CMA) has also received the complaint. Co-signers include The Independent Publishers Alliance, Foxglove Legal (a UK non-profit advocating tech fairness), and Movement for an Open Web. Benjamin Lanfry, chief supply and operations officer at Ogury, told Performance Marketing World: "The open web is pushing back. From antitrust complaints against AI Overviews to technical defenses like Cloudflare's new crawler controls, publishers are drawing a clear line: unchecked AI scraping and value extraction won't go unchallenged. "And it's not just publishers -- privacy regulators are stepping in too. France's CNIL [Commission nationale de l'informatique et des libertés], for instance, just clarified that legitimate interest is not a blank check for training AI on personal data. "Together, these signals point to a growing consensus: this isn't about resisting innovation - it's about demanding sustainability, transparency, and a future where both independent content and individual rights are protected. The stakes now go beyond traffic and revenue - they touch on the very infrastructure of digital trust." However, Google defended itself by arguing that it sends billions of clicks to websites daily and creates "new opportunities" for discovery via AI experiences. The company claims traffic data is often misrepresented and affected by many factors, like seasonal trends or algorithm updates. A Google spokesperson said: "New AI experiences in search enable people to ask even more questions, which creates new opportunities for content and businesses to be discovered. "The reality is that sites can gain and lose traffic for a variety of reasons, including seasonal demand, interests of users, and regular algorithmic updates to search." What's next? As tensions between AI firms and publishers continue to rise, Google is reportedly working on a solution, talking with about 20 national news outlets to license content for its AI tools. This would be part of a pilot project aimed at developing AI-related partnerships with media companies. The move resembles strategies by OpenAI (which has deals with Condé Nast, Vox, The Atlantic, and News Corp) and Perplexity (the second most active in licensing deals). Amazon also recently signed a licensing deal with Condé Nast and Hearst to allow its AI shopping assistant, Rufus, to scrape content from its publications. Google already has a partnership with the Associated Press for real-time news updates via its Gemini model and a $60m licensing deal with Reddit.