The Rise of AI-Powered Search in 2025: How Answer Engines Are Changing SEO and Consumer Behavior

By P. Blake Renda, Co-CEO, Dragon Horse Agency

Val Laube, Director of Artificial Intelligence, Dragon Horse Agency

‍Naples, Florida-based Dragon Horse Agency is a pioneer in business marketing, being the first to introduce the concept of integrated business strategy within a comprehensive marketing platform known as DragonONE, and the first to deploy artificial intelligence, “AI,” with DragonIQ in 2016. The company employs experienced strategists, creative architects, and AI pilots and is headquartered in North Naples, Florida, with an additional satellite office in Santa Monica, California. Dragon Horse Agency takes great pride in its industry-leading innovative strategies delivering cutting-edge business and marketing solutions as “a fiduciary to brands ™.”

From Keywords to Conversations: The Shift to AI Answer Engines

For decades, search engine users typed short keywords and sifted through pages of results. Now, a massive shift is underway. AI-powered “answer engines” and conversational search interfaces are revolutionizing the way we find information online. Instead of providing ten blue links, these AI-driven tools deliver direct answers or engage in back-and-forth dialogue. Consumers no longer want to scroll through endless results – they expect AI to give a definitive answer, personalized and immediate.Examples of this shift are everywhere. Google’s Search Generative Experience (SGE) now displays AI-generated answer summaries (often called AI Overviews) at the top of many search results. In fact, as of early 2025, about 13% of Google searches show an AI Overview at the top of the page, up from just 6.5% a few months prior. These summaries synthesize content from across the web into concise answers, providing links to the sources. Meanwhile, standalone AI search tools like ChatGPT, Bing Chat, and Perplexity allow users to ask questions in natural language and receive conversational answers with cited sources. Rather than entering terse keywords, users can pose detailed questions or follow-ups as if chatting with an expert. This evolution from keyword-based search to conversational search means the search experience is becoming more like an intuitive dialogue, rather than a database query.Crucially, conversational AI can understand context and nuance. Traditional search engines matched keywords to web pages, but AI search uses natural language processing (NLP) to interpret the intent behind complex queries. For example, a user might ask, “What’s the best project management software for a remote design team, and why?” An AI answer engine can parse this complex question, break it down into subparts, and deliver a tailored answer (e.g., recommending top tools with reasons), rather than requiring the user to manually combine information from multiple sites. Follow-up questions are also supported – you can ask a question, get an answer, then ask a clarifying question in context, and the AI remembers the conversation. This creates a more natural and interactive search experience that feels less like querying a database and more like engaging in a dialogue with a knowledgeable assistant.The rise of voice assistants and voice search has further accelerated this trend toward conversational interfaces. Digital assistants like Siri, Alexa, and Google Assistant have trained users to ask questions out loud in complete sentences. By 2024, there will be more digital voice assistants in use globally than people, and by 2025, an estimated 75% of households will own at least one smart speaker. Voice search allows people to speak queries naturally and often receive spoken answers. It’s not identical to full conversational search – many voice queries still return a single spoken answer or action – but it shares the same spirit: natural language in, immediate answer out. As voice-capable devices proliferate, consumers are increasingly comfortable with conversational query-and-response interactions rather than old-school typing. Whether via voice or text chat, the expectation is clear: ask a question in plain language and get a helpful answer straightaway.All of this represents a fundamental change in search behavior. Google’s data shows that people are now coming to search with longer, more complex questions than before, and multi-turn interactions are on the rise. In short, search has evolved from a task of finding information into a process of getting answers. For businesses and marketers, this shift from keyword-based search to AI-powered answer engines has profound implications. In the following sections, we’ll explore how these AI search tools are altering consumer behavior and what it means for SEO and brand visibility.

How AI Search Is Changing Consumer Behavior

AI-powered search isn’t just a shiny new interface – it’s actively changing how consumers search and what they do with the results. One significant change is reduced reliance on traditional search engine results pages (SERPs). When a detailed answer is served up directly by an AI, users have less need to scroll through a list of websites. We’re seeing the rise of the “zero-click” search, where the answer is obtained without ever clicking a result. This was already a trend with featured snippets on Google, but AI takes it further by aggregating information from multiple sources into a single, coherent response.Evidence of shifting behavior is emerging in usage data. Following the release of ChatGPT, Google’s global search traffic declined by nearly 8% from 2023 to 2024. In other words, some queries that used to be directed to Google are now being asked of AI assistants. Alternative search platforms with AI capabilities saw traffic increases in that period, suggesting that users are experimenting with new AI search tools. This doesn’t mean Google is obsolete – far from it, with Google Search still holding approximately 89.7% of the global search market share – but it indicates a significant shift in where people seek answers. Google’s introduction of AI summaries (SGE) was a response to this shift, aiming to keep users satisfied by giving direct answers on Google’s platform.Surveys confirm that many consumers have quickly embraced AI-based search in their daily lives. In a 2025 Adobe survey of U.S. internet users, a striking 77% of respondents reported using ChatGPT as a search engine. Nearly one in four (24%) now go to ChatGPT first when looking for information, before trying a traditional search engine. Younger generations lead this trend – for Gen Z, the figure was 28% who turn to ChatGPT before Google. This is a remarkable change in habit that has occurred in just a couple of years. The same survey found that three in ten people (30%) trust ChatGPT’s answers more than those from other search engines. Consumers cited benefits like the ability of AI to “summarize complex topics quickly” and require “fewer clicks” than a Google search. In essence, users appreciate that conversational AI can do the legwork of digesting information, saving them time.Consumers are also discovering content and brands in new ways via AI. Instead of finding a brand’s website through a search listing, a user might encounter that brand as part of an AI-generated answer or recommendation. According to an Adobe survey, 36% of people reported that ChatGPT has helped them discover a new product or brand they were previously unaware of. This was especially true for younger users (47% of Gen Z in the survey). In practical terms, someone might ask ChatGPT for “the best noise-canceling headphones under $200” and receive an answer that describes a few models. This answer might introduce a consumer to a brand’s product without the consumer ever visiting a search results page or the brand’s website. It’s a new kind of AI word-of-mouth exposure.Another behavioral change is that search is becoming more conversational and iterative. With AI chat interfaces, users often refine their queries by asking follow-up questions in the same session (instead of performing a brand new search from scratch). For example, one might start by asking, “How do I improve my credit score?” and, after an initial answer, follow up with, “What are some good credit monitoring services to use?” – the AI remembers the context. This means consumers are engaging longer with the search interface itself, treating it as an advisor. Google has noted that when people use its AI Overview feature, they often end up asking more questions in that session than they would in a traditional search, essentially because the AI invites deeper exploration. For marketers, this means user journeys might stay within an AI platform longer before clicking out to a website (if they click at all). The classic funnel of “search -> click link -> browse site” is getting disrupted; now it may be “ask AI multiple questions -> possibly get one recommended link or answer without a click.”Voice search usage also ties into this behavioral shift. Speaking a query (to Siri/Alexa/etc) is inherently a one-answer interaction – the assistant typically gives you a single response, or acts, rather than reading a list of results. As more consumers use voice queries (and with billions of voice-enabled devices in circulation), they become accustomed to a single-answer paradigm. Even when they transition to text-based AI search, they carry that expectation that the first answer might be all they need. By 2025, an estimated 153 million Americans will use voice assistants (often for search), and 75% of households will have a smart speaker. This widespread adoption of voice interfaces reinforces the preference for direct answers and conversational engagement.In summary, AI-powered search is making consumer search behavior more focused on finding answers, rather than exploring multiple sources. Users are placing trust in AI to curate and even interpret information on their behalf. They’re also expecting more personalization – if the first answer isn’t exactly correct, they ask the AI to clarify or tailor the response, rather than clicking around. For businesses, this is a double-edged sword: the opportunity is that your brand can become part of an AI-delivered answer (which is a powerful endorsement if you’re the chosen source), but the challenge is that you might not even get a chance to win over the customer if you’re not visible to the AI in the first place. It’s a new battlefield for attention, happening on the AI’s output screen rather than the traditional SERP.

AI Search by the Numbers: Growth and Impact

Striking data and third-party insights back the rapid rise of AI search. To put the trend in perspective, here are some key statistics illustrating the growth and impact of AI-powered search:

• Explosive User Adoption: ChatGPT, the poster child of AI answer engines, reached a massive user base in record time. By early 2025, ChatGPT surpassed 400 million weekly active users – a staggering adoption curve for a tool that only launched publicly at the end of 2022. A Pew Research study in late 2023 found that 34% of US adults had already used ChatGPT, and that number has only grown since. This indicates that a substantial portion of the population is experimenting with AI to meet their information needs.
• Generative AI as a Search Starting-Point: Research by marketing firms indicates that 10% (or more) of internet users now turn to generative AI first for specific searches. In other words, for perhaps one in ten queries, users are bypassing traditional search engines entirely in favor of tools like ChatGPT, Bing’s AI chat, or similar. This is a remarkable shift considering these tools were niche or non-existent just a couple of years ago. Among younger, digitally savvy users, the percentage is likely even higher.
• Google’s Response and Integration: Google remains the dominant search engine, but it has rapidly integrated AI to keep pace with changing user preferences. As noted, around 13-16% of Google searches now trigger an AI-generated overview at the top of the results, and this portion has been climbing each month. These AI summaries typically cite around five sources on average, condensing what might have been a dozen search results into a single composite answer. Notably, one study found that approximately 48% of the sources mentioned in Google’s AI overviews were not ranking on page 1 organically, suggesting that AI results can elevate websites that might otherwise be buried in the rankings, thereby changing the visibility game. Google reports that the introduction of AI results has been well-received; users who engage with the AI summaries tend to be more satisfied and even increase their search usage for complex queries.
• Impact on Search Volume and Market Share: As mentioned, Google’s web traffic saw a ~7.9% decline in the year after ChatGPT’s debut – a possible sign of users spending some of their search time with AI alternatives. Microsoft’s Bing (which integrated GPT-4 into its search in early 2023) has seen an uptick of interest, though it still holds a small market share (~4%). Niche AI search startups, such as Perplexity, and privacy-focused engines with AI features (e.g., Brave Search with its AI summarizer) also gained users following the generative AI wave. Still, Google commands the lion’s share of search, nearly 90% globally, meaning Google’s own AI advancements (SGE, “AI Mode”, etc.) could mainstream AI search for hundreds of millions of users simply by changing the default Google experience.
• Mobile, Voice, and Multimodal Searches: Over 1.5 billion people use Google Lens each month to search what they see – a form of multimodal AI search where a user can take a photo (or use the camera) and ask questions about the image. Google is pushing boundaries with features like “Search Live,” which lets users hold up their phone camera, talk to an AI about what’s on screen, and receive answers in real-time. This indicates a future where search queries aren’t just text or voice, but images and even real-time video feeds. The lines between “searching” and “seeing” are blurring, powered by AI’s ability to analyze visuals.
• Marketing and SEO Industry Response: Recognizing the AI search trend, marketers are pivoting their strategies. In Adobe’s 2025 survey, two-thirds of marketers and business owners said they plan to increase their focus on “AI visibility” – essentially, ensuring their brand shows up in AI-driven search results. Over 75% of surveyed marketers called it essential for their brand to appear in ChatGPT’s answers in 2025. This has given rise to a new discipline of Answer Engine Optimization (AEO) (more on that below). The SEO community has been quick to research how generative AI selects and presents information. Agencies and SEO platforms are now tracking metrics such as “share of voice in AI answers” (i.e., the frequency at which AI mentions a company) in addition to traditional SERP rankings.

Overall, the data paints a clear picture: AI-driven search is not a minor sideshow – it has become a core part of how people find information, and it’s reshaping the digital landscape. Usage is growing rapidly, and user satisfaction with AI answers is high. Both tech giants and startups are investing heavily to win this new search paradigm. For businesses, these numbers serve as a wake-up call to adapt their search strategies for an AI-centric world.

Optimizing for AI-Driven Search: AEO and E-E-A-T Strategies

With search evolving, businesses must adjust their SEO strategies to remain visible and relevant. The goal is no longer just to rank on page one of Google, but to be featured in the answer that an AI-powered engine provides. This new approach is often referred to as Answer Engine Optimization (AEO) – the practice of optimizing your content so that AI search tools can readily find, understand, and include it in their answers. In essence, instead of optimizing purely for a search engine algorithm, you’re optimizing for the answer algorithms of large language models and AI summary systems.What is AEO, exactly? It’s an evolution of SEO that recognizes how AI systems work. Traditional SEO is about improving your ranking in search engine results. AEO is about increasing your brand’s visibility in AI-generated responses, many of which have no explicit rankings or even clickable links. For example, if someone asks an AI, “What’s the best project management software for small businesses?”, an AEO-optimized company would have content that the AI deems worthy of mentioning in its one-paragraph answer. As one guide put it, brands must evolve from search engine optimization to answer engine optimization to remain visible when AI engines synthesize the web’s information into a single authoritative answer. That means providing the kind of content that AI loves to quote and users find trustworthy.Here are some key strategies for optimizing your content for AI-driven search (AEO), along with how they relate to the familiar SEO best practices:

• Provide Direct, Concise Answers: Ensure your site features content that directly answers common questions in your domain. This could be in the form of FAQ pages, how-to guides, or Q&A-style articles. AI systems often scan for a straight answer to the user’s query. If, for example, you sell insurance and your blog answers “What does home insurance typically cover?” in a concise paragraph, an AI may quote or summarize that. Structuring content in a question-and-answer format helps both traditional search snippets and AI parsers. The content should be well-structured (using headings and bullet points) so AI can easily digest it.
• Focus on E-E-A-T – Quality and Trust are Paramount: E-E-A-T stands for Experience, Expertise, Authority, and Trustworthiness. This concept, stemming from Google’s search quality guidelines, is arguably even more critical in the age of AI search. AI models draw from vast training data and will prefer content that seems authoritative and accurate (and Google’s AI results certainly consider source quality). To demonstrate E-E-A-T:
  • Highlight the experience behind your content – for instance, include authors’ credentials or first-hand insights (“Our CEO shares 10 years of experience in cybersecurity”).
  • Show expertise by covering topics in depth, citing credible sources, and keeping information up to date.
  • Build authority through backlinks, mentions, and by publishing on reputable platforms. If your brand is frequently mentioned in industry discussions, AI is more likely to recognize it as a trusted source.
  • Foster trust with honest, factual content. Avoid hyperbole or unfounded claims. AI systems, and indeed Google’s algorithms, are designed to prioritize accuracy and reliability. In practical terms, that might mean double-checking facts in your content and providing references. (Some AI, like Bing Chat and Perplexity, directly cite sources – you want to be the source that gets mentioned, and that won’t happen if your content is dubious.)

Remember that content quality, depth, and expertise are shared pillars of both traditional SEO and AEO. By focusing on E-E-A-T, you not only improve your chances with AI but also future-proof your SEO as algorithms continue prioritizing quality.

• Use Structured Data and Schema Markup: Just as you would mark up your content for rich results in Google (using FAQ schema, HowTo schema, etc.), it’s wise to use structured data to help AI understand your content context. AI answer engines often rely on structured data to pull quick facts (for example, voice assistants using schema to answer a spoken query about store hours). Implementing schemas like FAQPage, HowTo, Product, etc., can make your content more digestible to AI. Additionally, structured data provides context that can enhance trust (e.g., identifying an author as a consistent entity across the web). Google’s AI results are still drawing from the indexed web, so traditional SEO steps, such as schema, proper metadata, and a clean site structure, indirectly aid AEO.
• Optimize for Conversational Queries: Consider the phrasing people use when speaking or asking full questions, and naturally incorporate those into your content. These are often long-tail, conversational keywords. For instance, a traditional keyword might be “best running shoes 2025”; a conversational query might be, “What are the best running shoes for marathons in 2025?” You should include both types in your content. Tools like Google’s People Also Ask or community forums can reveal natural language questions consumers are asking. Including question-and-answer sections in your content with exactly those phrasings can position you as a match for the AI’s needs. Essentially, you want to anticipate the questions and answer them in your copy.
• Format Content for Snippets and Voice: AI answers often resemble an expanded featured snippet. Continue to optimize for featured snippets by using clear and succinct paragraphs that directly answer a question immediately after it is posed. Use lists or tables for step-by-step or data-driven answers, and ensure the answer can be understood out of context. For voice search, keep sentences brief and to the point, since they might be read aloud. Google’s voice answers often come from content that reads in a conversational, natural tone, rather than being overly formal or stuffed with keywords. Including a summary section or a “In a nutshell, …” line for key topics might help an AI grab the summary. According to SEO experts, content written in a conversational, snippet-friendly style is more likely to be extracted by AI engines.
• Leverage Multi-Modal Content (Images, Video) and Alt Text: AI models don’t just read text; they can also analyze images and even video transcripts. Ensure your images have descriptive alt text (valid for both accessibility and AI context). Consider creating short video explainers for key topics – YouTube videos might get referenced by AI or appear in AI-driven carousels. Google’s generative search is increasingly blending images and text in answers for issues like shopping. By providing high-quality visuals (with proper metadata), you increase your content’s chances of being featured in those rich AI results. For example, if you have a product, using Google’s 3D image schema (so that it can appear in interactive results) could be beneficial – Google noted that interactive 3D results get 50% more engagement than static ones.
• Monitor and Adapt: Start tracking how and when your brand appears in AI contexts. This might include manually querying ChatGPT/Bing for industry questions to see if you’re mentioned, or using emerging tools that attempt to measure “LLM visibility.” If you find AI is citing competitors and you are not, analyze why – do they have more thorough content on specific subtopics? Do others more frequently reference them? This is new territory, but it’s wise to monitor your share of voice in AI answers much like you’d track search rankings. Also, keep an eye on Google’s Search Console (which now may report on AI overview traffic or similar, as those features roll out) to see if your content is being used in SGE.

Importantly, AEO isn’t a total departure from SEO – it builds on the same fundamentals. A site that is technically sound, fast, and mobile-friendly still has an advantage (since AI can’t see your content if it’s not crawlable). Backlinks and brand mentions still matter because they build authority. Good user experience still counts (if an AI result provides a link and users click through to a poor site, that doesn’t help you). Think of AEO as the next chapter of SEO – you still need to do everything you did for SEO, plus actively shape your content and strategy for the AI answer landscape.One new concept to be aware of is “prompt optimization” or prompt engineering for search. This refers to structuring your content (or even providing metadata hints) so that it aligns with how AI models might be prompted. For instance, some companies are experimenting with special files (like LLM.txt) that give instructions to AI crawlers on how to use their content. While this is cutting-edge and not standardized, the general idea is to consider the questions people will ask, not just the keywords they will type. Suppose you align your content with the actual natural language questions (and even incorporate those questions verbatim on your pages). In that case, you increase the likelihood that an AI will pick it up to answer a similar question.In summary, to optimize for AI-driven search engines, you should offer high-quality, trustworthy content that answers questions directly and succinctly, use structured formats and schema to make that content machine-friendly, and ensure your brand’s authority signals (E-E-A-T) are strong across the web. By doing so, you position your business to be the trusted answer when consumers ask their digital assistants or AI tools about your field.

The Future of Search: Voice, Multimodal, and Hyper-Personalized Experiences

What will search look like in the next few years as AI capabilities continue to advance? All signs point toward an even more integrated, intelligent, and personalized search experience. Here are a few key projections and emerging trends for the future of AI-driven search and SEO:

• Voice Search Becomes Ubiquitous and Conversational: Voice queries are expected to increase in volume as more users become comfortable interacting with their devices. We’re nearing a world where virtually every smartphone and household device is voice-enabled. By the end of 2025, experts project that over 8 billion voice assistants will be in use globally, roughly equivalent to one per person on the planet. As voice AI improves at understanding natural language and intent, voice search will transition from simple commands (“Call Mom” or “What’s the weather?”) to more complex questions and transactions. This means SEO will increasingly overlap with voice UX design – content may need to be optimized to sound good when read aloud and to satisfy spoken follow-up questions. Also, expect more voice-driven commerce (voice ordering of products, etc.), which will require brands to have a presence in voice assistant ecosystems. For SEO, securing those voice answer slots (e.g., being the answer the assistant provides) will be a highly coveted prize.
• Multimodal Search – Beyond Text to Image, Audio, and Video: AI is enabling search to break free from the text box. Visual search is a prime area of growth: consumers can point their phone camera at an object or scene and ask questions about it. Google Lens already processes billions of such searches, and new AI-powered features allow real-time visual Q&A. For example, you might scan a recipe card and ask Google to clarify a cooking instruction, or take a photo of a plant and ask how to care for it. In the future, we’ll see multimodal queries where users combine text, voice, and image inputs (e.g., saying “Find something similar to this dress” while showing a picture). Search engines will increasingly incorporate AR (augmented reality) for “search what you see” functionality. Businesses will need to optimize not just web pages, but images (with good metadata), videos (with transcripts and SEO), and even 3D models of products. Being discoverable in these new modalities will be part of SEO. Google’s introduction of features like “Circle to Search” – where users can circle something on their screen (an image or text) to search for it – is an example of making search more visual and seamless. The bottom line: search will happen everywhere, in various forms – scanning product labels, listening to a song, and asking “who is the artist?”, etc. – and AI will be the engine making sense of all those inputs.
• Real-Time Personalization and Contextual Results: AI’s ability to personalize on the fly means search results will become highly tailored to each individual’s context. We’re already seeing early signs of this trend. Google announced that its new AI search “Mode” will soon offer personalized suggestions based on your past searches and even data from other apps (like Gmail, with user permission). This could mean your search for “best restaurants” yields different answers than someone else’s search, because the AI knows your preferences (e.g., you’re a vegetarian and love jazz music, so it shows a vegetarian bistro with live music that you’ve never been to but matches your tastes). Soon, we can expect search AI to incorporate location, past behavior, calendar events, purchase history, and more – all in real-time – to serve uniquely relevant results. For instance, if you have a flight tomorrow, asking “What should I pack?” might prompt the AI to check your destination’s weather and your airline’s baggage rules automatically in forming its answer. For marketers, this hyper-personalization means the average ranking position may matter less than ensuring your content is aligned with specific audience segments or contexts. It will be about being the correct answer for the right person at the right moment. Techniques like using dynamic content (content that adapts to user segments) and leveraging customer data for search (in advertising, for example) will grow. Privacy considerations will be crucial here – users might need to opt in for these personalized AI features, and trust in how data is used will be paramount.
• Proactive and Agentive Search: Instead of waiting for us to ask, future search AIs might become proactive assistants. Imagine an AI that knows you have a meeting across town and proactively suggests the best time to leave based on traffic, or an AI that, upon detecting you’ve been researching “how to get a mortgage,” offers to pull your credit score and pre-fill some applications (with permission). Google teased “agentic capabilities” in its AI mode – essentially letting the AI not only answer questions but help complete tasks. For example, Google’s demo showed an AI that could find concert tickets across multiple sites and even navigate through purchasing steps for you. This is search blending into action – the AI doesn’t just tell you where to bu