People aren’t just Googling anymore. They’re asking ChatGPT, scrolling TikTok, or talking to Siri. Search is no longer about keywords and blue links—it’s about answers, recommendations, and conversations delivered by AI.
In a 2024 survey, 80% of consumers resolved 40% of their online searches without clicking any links, and 42% regularly used generative AI for shopping recommendations. This marks the rise of a decentralized, multi-surface discovery landscape, where visibility depends on AI, not just traditional search engine optimization (SEO).
From zero-click summaries in search engine results pages (SERPs) to personalized large language model (LLM) responses and algorithm-driven content feeds on TikTok and Instagram, discovery now happens across multiple channels. AI is reshaping discovery, and brands and marketers must adapt or disappear.
This article explains how search is changing, what’s at stake, and what businesses must do to stay visible, relevant, and competitive in an AI-first world.
The Crumbling Foundations of Search
The transition from traditional keyword-based search (Search 1.0) to AI-driven, conversational search (Search 2.0) marks a significant shift in how users seek and consume information online.
In the Search 1.0 model, you typically create content centered around specific keywords, optimize on-page elements, build backlinks, and aim to move up the search rankings. Users enter keywords, and search engines return a list of links ranked by relevance.
This linear and centralized approach focuses on where your site appears on the results page and offers only a single channel or path for discovering content.
However, with the rise of large language models (LLMs) such as ChatGPT, Perplexity, and Google’s Gemini, Search 2.0 has emerged, ushering in AI-powered discovery in which users no longer rely on a single source.
Instead, they navigate through various platforms, interfaces, and formats. A search journey might start on TikTok, move to YouTube or Reddit, and conclude with an AI chatbot.
Unlike traditional search engines, LLMs process content by identifying structures and patterns within text rather than relying solely on ranking signals. They prioritize clear headings, bullet points, and concise paragraphs to extract key information.
These models then generate summaries presented directly within the search interface, eliminating the need for users to click through to external sites. If your content is well-structured and factually sound, these models can provide relevant and accurate summaries, improving your brand visibility on LLMs.
The chart below from a Growth Memo study shows how referral traffic from AI chatbots to six B2B companies grew from about 250 visits per month early in 2024 to over 1,300 visits in November. This fivefold increase happened because more people are using AI chatbots, more links to sources are being shared, and OpenAI launched ChatGPT Search.
The Invisible Middle: The Hidden Challenge in AI-Driven Search
Despite the growth of AI-driven search, a new challenge has surfaced: the loss of visibility into user behavior. In earlier search models, marketers could track the full path from query to conversion, allowing for detailed analysis and optimization. Now, with users turning to AI tools, a critical stage between intent and action has become hidden within these closed systems.
This gap, known as the “Invisible Middle”, makes it difficult to see how users explore, compare, and decide. As a result, behavioral signals are lost, and attribution becomes weaker, leaving marketers uncertain about what influenced the user’s final action.
However, this should not stop you from leveraging AI tools. Instead, it should encourage you to adopt innovative strategies to grow visibility and influence beyond what current search metrics can measure.
The AI Disruptors Changing the Game
Five main forces are changing how people search and what it means to be seen online. Each creates new challenges that businesses need to understand and handle to succeed.
LLM Adoption
LLMs such as ChatGPT and Perplexity are transforming how users discover information.
In an AI search optimization study of over 30 websites, Previsible reported a 900% increase in referral traffic from LLMs in the events industry over 90 days, with the e-commerce and finance sectors seeing growth of around 400%.
Unlike traditional search engines that retrieve web pages, these models generate responses by synthesizing content from their training data. Your brand’s visibility on these platforms depends on the relevance and quality of the content you contribute to that data.
Personalization
With AI-driven personalization, two users can ask the same question and receive completely different recommendations. For example, Amazon’s generative AI shopping assistant Rufus delivers tailored product recommendations, feature comparisons, and purchase insights.
It analyzes user preferences, historical shopping behavior, search history, and trending consumer patterns to provide results that closely match each user’s individual needs.
Social Discovery
Social platforms now serve as powerful search tools for discovering information, trends, and businesses, especially for Gen Z and millennials. For instance, 62% of users aged 18–24 use TikTok mainly to find local businesses.
Its rise as a search engine stems from AI-driven recommendations and short, engaging videos tailored to user behavior and previous interactions. Unlike keyword-based search engines, TikTok delivers intuitive visual results, appealing to younger users who prefer fast, personalized content over long-form, text-heavy pages.
Zero-Click Search/AI Overviews
Zero-click search transforms how users access information by providing answers directly on the results page through AI-powered featured snippets, panels, summaries, and visual content. This reduces visits to external sites via traditional blue links.
Google’s AI Mode exemplifies this shift by delivering conversational responses and summaries on its platform. This has contributed to reduced visits to sites like Reddit and a nearly 5% decline in its stock due to fewer casual, logged-out users.
Multimodal Search
Multimodal search allows users to combine different input methods—text, voice, images, or video—in a single query. A user might capture a photo of a product and ask where to buy it or issue a voice command like “Show me outfits like this” while uploading an image.
Google Lens processes nearly 20 billion visual searches monthly, with shopping-related queries making up 20% of the total.
The High-Stakes Challenge for Brands
As AI-generated answers become more prevalent, brands must adapt by enhancing their online visibility and authority to ensure inclusion in AI-powered search results. However, most brands remain invisible in AI-generated search summaries.
A 2025 Ahrefs study analyzing 75,000 brands found that 26% had zero mentions in Google’s AI Overviews, despite ranking well in traditional search results.
This visibility gap stems from AI systems prioritizing content with strong brand signals, such as frequent online mentions and branded search volume, over traditional SEO factors like backlinks or domain authority.
Traditional SEO metrics like impressions, clicks, rankings, and traffic volume no longer reflect the true influence of your brand or the value of your content. In today’s AI-driven search environment, this poses a significant challenge for brands. You may see impressions rise while clicks fall, and your SEO dashboard likely can’t explain why.
That’s because AI is changing user behavior. Users engage with searches in a conversational manner to get instant answers. Your content might appear in AI overviews or snippets that provide direct answers, delivering value without requiring a click.
Semrush reported that in March 2025, Google AI Overviews surfaced in 13.14% of desktop searches across the U.S., nearly doubling from 6.49% in January. While 88.1% involved informational topics, commercial and navigational queries also increased.
Thus, to stay competitive in the future of SEO, you must assess how well your content meets user intent, not just how many users visit your site.
How Brands Can Stay Discoverable
As generative AI reshapes SEO, where success is no longer about driving clicks or traffic, here are some effective strategies to ensure your brand appears in AI conversations and your content serves users’ needs regardless of where they consume it:
1. Create AI-Friendly Content
AI algorithms evaluate content using various signals, from technical structure and semantic clarity to real-world engagement patterns. To align with how LLMs interpret information, use data schemas and microformats that clearly communicate the nature of the content.
Additionally, organizing information with lists, tables, and highlights helps LLMs quickly identify and prioritize key points. Equally important are logical paragraph structures and semantic coherence. Maintaining consistent terminology and related concepts enables AI systems to map ideas with greater precision.
Rather than relying on keyword-stuffing, focus on directly answering real user questions with clarity and depth. Adopting a conversational tone also makes content sound more natural and engaging. LLMs tend to favor human-centered writing that feels authentic while still being machine-readable.
In short, write for people, but structure content deliberately for AI comprehension.
2. Build Authority Beyond Your Site
Consistently build a strong brand presence across the web to boost your LLM search visibility. Get quoted in trusted publications, contribute guest articles, and invest in PR to earn high-quality backlinks. These efforts strengthen your SEO and Generative Engine Optimization (GEO)—the signals AI systems use to identify trusted sources.
Note that LLMs reward brands that the web is already talking about. A study found that only 9% of links in LLM-generated responses point to branded domains. Most links go to high-authority, non-branded sources like Wikipedia or major publishers.
3. Track and Measure AI Visibility
AI-powered discovery has changed what it means for your brand to be seen. Traditional SEO metrics like rankings and clicks still matter, but they no longer show the full picture. Now, tracking how often your brand is mentioned in AI-generated answers is essential. These mentions reflect brand awareness and influence.
If AI tools recommend your competitors more often, your brand may be losing attention early in the customer journey. Meanwhile, Share of Voice (SOV) tracks the percentage of relevant AI responses that include your brand versus competitors.
Sentiment analysis further gauges how a brand is portrayed: positively, neutrally, or as an afterthought. Tools like Peec.AI, Spyfu, Brandlight, and “Am I On AI?” can help track these insights..
To quantify AI-driven traffic, your team can configure Google Analytics 4 (GA4) with regular expression (regex) filters targeting domains like chat.openai.com or perplexity.ai. This setup also allows you to track sessions, engagement, and conversions from AI systems to assess the effectiveness of your AI visibility strategies and the success of your SEO for ChatGPT/Perplexity efforts.
4. Embrace Platform-Native Discovery
Adapt content to match how each platform delivers results to improve your visibility in AI-powered search. Incorporating affiliate marketing into platform-specific content can further amplify reach, as AI algorithms prioritize personalized and relevant product recommendations. Create short, engaging videos for TikTok and YouTube using trending sounds, captions, and strong calls to action (CTAs). Both users and AI algorithms prioritize these formats.
On Amazon, optimize product listings with keyword-rich titles, structured bullet points, and informative Q&As that answer common customer questions. For voice assistants like Siri and Alexa, and visual tools like Google Lens, use structured data (schema markup), alt text, and conversational language.
These elements help AI systems accurately and effectively interpret and surface your content in relevant responses.
Real-Word Example
A period care brand saw a 400% increase in monthly website traffic after optimizing content for AI platforms like ChatGPT. The brand’s strategy centered on producing detailed, context-rich blog posts that answered common questions about sustainable menstrual products.
This strategy aligned well with AI’s preference for authoritative and comprehensive content. As a result, ChatGPT frequently cited the brand’s content in response to user queries, significantly boosting visibility among Gen Z and millennial audiences.
This AI-driven exposure led to a 436% increase in sales conversions and a rapid sellout of six months’ inventory within three weeks. This case highlights the importance of tailoring content formats to match AI-driven search behavior, thereby maximizing both traffic and revenue growth.
Discovery Isn’t Dying. It’s Moving.
Discovery isn’t fading away—it’s transforming. As AI redefines how people find and explore information, brands need to evolve alongside it. You must go beyond traditional rankings by being present, creating structured content, earning consistent and credible citations, and building trust and authority across AI platforms.
The brands that will win in Search 2.0 won’t just be ranked; they will also be recognized. They’ll be remembered—and recommended.
