The Future of Search Value: Why LLMs Will Drive 75% of Revenue by 2028

Posted on July 17, 2025
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TL;DR Summary of How Large Language Model Search is Transforming SEO and Digital Marketing

Large Language Model (LLM) search is revolutionizing how users find information online by providing conversational, synthesized answers rather than traditional link-based results. This shift is driving a rapid increase in AI-driven search adoption, with LLM search traffic projected to surpass traditional organic search by 2028. Businesses must optimize content structure, target question-based and comparative prompts, and build a consistent, authoritative digital presence to succeed in this evolving landscape. LLM visitors tend to be more informed and ready to convert, making LLM search a high-value traffic source for marketers.

Optimixed’s Overview: Navigating the Future of Search with AI-Powered Large Language Models

Understanding the Rise of LLM Search and Its Impact on Digital Marketing

Large Language Models (LLMs) like ChatGPT, Google Gemini, and Claude are reshaping the search ecosystem by delivering direct, conversational answers that prioritize clarity, personalization, and source citations over traditional search engine results pages (SERPs) filled with blue links. This new mode of search is growing rapidly, with AI overview queries increasing significantly and generating less click-through traffic but higher quality user engagement.

Key Insights from Recent Studies

  • Shift in User Behavior: Over 13% of queries now trigger AI Overviews, predominantly informational, signaling a major change in how users seek and receive information.
  • Traffic Trends: AI search traffic is forecasted to increase from 4% in 2025 to 87% by 2029, overtaking traditional organic search.
  • Higher Conversion Potential: LLM-driven visitors are 4.4 times more likely to convert, as they come better informed and closer to purchase decisions.
  • Unlinked Brand Mentions: AI answers often cite brands without links, making direct traffic and brand visibility tracking more complex but emphasizing the importance of brand authority.

What Kind of Content and Sites Are Favored?

LLMs tend to prioritize:

  • User-Generated Content (UGC): Forums like Quora and Reddit are heavily cited due to their authentic, detailed insights.
  • Business and Service Sites: These represent 50% of links cited in AI answers, especially those offering clear, actionable information for local and commercial queries.
  • High Authority Domains: Established sites like LinkedIn, YouTube, and major news outlets also perform well in AI search results.

Strategies to Optimize for LLM Search

  • Structure Content for AI Readability: Use descriptive headings, bullet points, FAQs, and comparison tables to make content easily digestible by AI models.
  • Focus on Question and Comparative Prompts: Target specific user queries and comparison-based content using tools to identify relevant long-tail keywords and schema markup for better AI discoverability.
  • Build a Consistent Digital Footprint: Ensure uniform branding, showcase expertise and trustworthiness, publish regularly across channels, and engage in relevant communities to increase your chances of being cited by LLMs.

Preparing for an AI-Driven Search Future

As LLM search becomes the preferred method for information retrieval, digital marketers must adapt by monitoring brand visibility within AI platforms and adjusting SEO strategies accordingly. Utilizing advanced tools like Semrush Enterprise AIO and AI Toolkits can help track and enhance LLM presence. Embracing this shift early will secure competitive advantages in user engagement, brand authority, and conversion rates in an increasingly AI-dominated search landscape.