AI search engines like ChatGPT and Google AI are revolutionizing how we find information online. Instead of listing links, they provide conversational, synthesized answers, challenging traditional SEO practices.

Generative Engine Optimization (GEO) is becoming important for visibility in AI-generated responses. Predictions suggest traditional search volume may decrease by 25% by 2026, making adaptation to these changes necessary.

We’ll explore the shift toward GEO, sharing key insights on balancing traditional Search Engine Optimization (SEO) with new strategies to optimize content for both human readers and AI comprehension.

TL;DR

• AI search engines deliver synthesized answers, transforming traditional SEO into Generative Engine Optimization (GEO) for better visibility
• Predictions suggest traditional search volume may decrease by 25% by 2026 as AI platforms become more popular
• GEO emphasizes structuring content for AI processing, ensuring it is both accessible and contextually rich
• Future content strategies should cater to both human readers and AI systems for optimal reach and engagement

Defining Generative Engine Optimization (GEO)

GEO has become a transformative force in how we think about search visibility, especially in content marketing.

While traditional SEO focuses on climbing those search engine rankings, GEO is all about structuring your content so search engines can process, understand, and cite it effectively. Frankly, the stakes could not be higher.

As more users trust and rely on AI-generated search results, GEO is becoming as vital as traditional SEO for staying visible online. Just look at the numbers—a recent study by Gartner reveals that organic search traffic could decline by up to 25% by 2026 as users shift towards AI-powered search engines for direct, conversational answers instead of clicking through multiple search results.

When organizations adapt to this transition, they must understand that AI search engines operate with different parameters and expectations. Traditional keyword optimization remains relevant but takes on new dimensions when AI systems analyze content for context, authority, and practical value.

We recently caught up with Isiah Cruz, Data Scientist and Founder of environmental AI startup Ama Earth Group, who put it perfectly:

“GEO is the next frontier of search optimization. Consumers are moving en masse to AI-first search engines (ChatGPT has 300 million weekly active users and growing). Naturally, the search criteria is different as well.

Instead of searching ‘gardeners near me,’ one might type ‘native plant-focused gardeners near me with prices under $100’ since AI has the ability to process and make use of this level of context.

As such, businesses that maximize their position and ranking on AI search engines will see outsized results in the form of client leads, website visits, etc. These are the early days of this movement so there are opportunities to leapfrog competitors spending substantially in the SEO space.”

Echoing Isiah, this leap forward in AI capabilities is not happening by accident—continuous improvements in machine learning techniques and resources have enabled these systems to understand context, synthesize information, and generate relevant responses.

For businesses, this evolution means it is time to adapt their content strategies to ensure visibility in this new search paradigm. But what makes GEO distinct from traditional SEO lies in its emphasis on comprehensive, well-structured information that AI systems can parse effectively.

Brands that win in GEO focus on creating content that answers specific questions, provides clear context, and maintains semantic relationships between different pieces of information.

Key differences between GEO and SEO

As AI-driven search engines reshape content discovery, GEO and SEO are evolving in parallel—but with distinct methodologies and objectives.

1. Content creation process

Traditional SEO relies on manual content creation, where writers and marketers strategically place keywords, structure content for readability, and build quality backlinks to improve rankings. In contrast, GEO leverages AI to generate content at scale, analyzing search intent and synthesizing information with minimal human input.

Lauren Funaro, Content Marketing Manager at Freed.ai, puts it simply:

“GEO refers to using generative AI to analyze SERP results and build content at scale. In a purely GEO approach, there’s little to no human involvement in the content creation process. Traditional SEO, on the other hand, is a manual process—writers create content for search engines using keywords and optimization best practices.”

2. Optimization approach

SEO professionals focus on manual adjustments, refining content through keyword research, meta descriptions, and link-building strategies. GEO, however, optimizes content dynamically, as AI models process vast amounts of data to predict search intent and generate responses accordingly.

However, both SEO and GEO face the same overarching issue: content written for algorithms rather than people. Google is actively combating this with a “people-first” approach, prioritizing expertise, topical authority, and unique insights over keyword-stuffed, AI-generated content.

3. Trust and authenticity challenges

A major differentiator between GEO and SEO is consumer perception. Audiences remain skeptical about AI-generated content, with studies showing that 69% of consumers prefer human-written product descriptions over AI-generated ones. This skepticism demonstrates the increasing importance of authenticity, human insights, and expert credibility in both GEO and SEO strategies.

4. Evolution and adaptation

Search engines evolve constantly, requiring both SEO and GEO practitioners to adapt. While SEO best practices have historically revolved around algorithmic updates and ranking factors, GEO’s success hinges on AI’s ability to accurately interpret search intent, relevance, and trust signals.

As AI-generated search becomes dominant, a hybrid approach will emerge:

• Traditional SEO will need to integrate expert insights and unique perspectives to maintain credibility
• GEO will serve as a foundation for content, but human writers will refine and enhance AI-generated drafts to ensure depth, nuance, and originality

Lauren adds that “both GEO and SEO will need to evolve. Traditional SEO must incorporate expert insights and unique viewpoints, while GEO should be a starting point rather than the final product. If AI tools work in tandem with real writers and experts, we’ll see a lasting motion that fuses GEO with strong authorship.”

Why GEO is a non-negotiable in today’s digital landscape

AI-driven search represents a fundamental change in how people look for information online.

Platforms like ChatGPT and Google AI Overviews are quickly becoming the go-to sources for everything from basic information to product research and purchase decisions.

As machine learning advances, these AI platforms now deliver (scarily) accurate and nuanced responses, adapting to user preferences and behavioral patterns in real time. Not only that, but their ability to understand context and provide relevant information continues to improve with each and every interaction.

However, Google’s long-standing dominance is facing real competition from AI search platforms like Bing’s AI integration, ChatGPT, and Perplexity. We are past the initial hype phase—these technologies are maturing, and public trust is growing steadier by the day.

Recent usage statistics demonstrate a clear shift in search behavior, where ChatGPT alone is dominating with a whopping 123.5 million daily users turning to AI for their daily information needs.

This then begs the question: Will AI-powered search engines ultimately end transactional search?

Data & Analytics leader, Dan Meers, states that “this transformation goes much deeper than just switching platforms. Users are starting their search journeys differently now, looking for more personalized, contextual, and immediate answers through AI platforms.”

This shift means brands need to adapt their digital strategies—traditional SEO alone simply won’t cut it anymore.

What makes AI search particularly powerful is its capacity to synthesize information from multiple sources, providing comprehensive answers rather than just links to potentially relevant pages. For businesses, this creates both opportunities and challenges in content distribution and visibility.

Want to stay ahead? Try Dan Meers’ approach:

• First, create and optimize content around hyper-relevant customer topics
• Next, distribute it across multiple platforms, from your company blog to LinkedIn and Reddit, to broaden ingestion by commercial GenAI engines
• Finally, add structured data to make more connections inside the GenAI model to increase prioritization in search results

This broader distribution ensures commercial Generative AI engines can both find and digest your content.

Want to multiply your efforts? Adding structured data helps create stronger connections within the GenAI model, making it more likely to prioritize your content in AI-generated results. Structured data acts as a clear signal to AI systems, helping them understand and categorize your content more effectively.

In practice, successful AI optimization requires a balanced approach between creating valuable content and ensuring technical implementation aligns with AI platform requirements. Organizations that master this balance often see better visibility across both traditional search and AI-powered platforms.

Best practices for optimizing content for Generative AI search

Now we understand the cause and effect of GEO, you might be wondering: What really makes GEO work?

Afnan Rehan, Consultant and SEO Lead at Wordbrew, states that “intent is everything“.

Ultimately, AI search engines aim to give users exactly what they need—whether it’s a quick answer, an in-depth guide, or a solution to a problem. Companies that align their content with different search intents, rather than just chasing keywords, are best positioned to stay relevant and maintain traffic for AI-first searches.

Not just that, but a clear structure is absolutely essential. She continues: “It’s important to structure content in a way that both people and AI can easily understand. Using clear headings, bullet points, and well-organized sections makes it more likely that AI will pull key insights from your content and feature them in search results.”

This structural clarity helps AI accurately extract and synthesize information from your pages. When content is properly organized, you enable AI systems to parse and comprehend your content more effectively. Take time to consider how information flows from one section to another, creating logical connections that both machines and humans can follow naturally.

In GEO, credibility also matters more than ever. AI overviews tend to favor content backed by solid data and authoritative sources, so including well-cited stats and references can help improve visibility. Need to find expert insights quickly? Try Wordbrew to tap your internal and external SMEs for quotes in a fraction of the time.

When AI engines encounter well-cited statistics and references from respected sources, they are more likely to feature that content in their responses. This focus on credibility shows just how sophisticated AI search algorithms have become.

Just remember that proper sourcing practices extend beyond simple citations. Linking to primary research, industry studies, and expert insights or analysis strengthens your content’s authority while providing AI systems with verification paths for fact-checking.

Overall, intent alignment is clearly shown to be central to AI search success. These systems are designed to give users exactly what they need—whether quick answers, in-depth guides, or simple solutions to a problem.

Brands that structure their content to match different search intents, rather than just targeting keywords, are positioning themselves much more effectively for AI-first searches.

Integrating GEO and SEO for maximum visibility

Creating content that works for both human readers and AI systems is like walking a tightrope—but it is definitely doable.

The secret? Develop material that keeps humans engaged while including the structural elements that help AI understand it. This means using clear, straightforward language and well-organized sections without sacrificing your content’s natural flow or readability.

Each piece should maintain a natural conversational tone while incorporating relevant semantic markers and structured elements that make the content machine-readable.

Over the past year, we’ve seen successful digital strategies shift focus from simple keyword placement to semantic relevance—an approach that works better for both traditional search algorithms and AI systems, since it emphasizes contextual understanding and natural language patterns.

Typically, your content should include traditional search terms while addressing the broader context and related concepts that AI systems use to generate comprehensive responses. In practice, this means considering how different systems process and interpret your content.

For example, search engines look for specific signals of expertise and authority (as we mentioned earlier: components like expert quotes, citations, and beyond), while AI systems analyze patterns and relationships between concepts. Understanding these differences allows you to create content that serves both purposes effectively.

Outside this, don’t forget about the technical foundation that supports both SEO and GEO efforts. This includes:

• Optimizing for load speed
• Ensuring mobile friendliness
• Implementing structured data markup

These technical elements help traditional search engines index your content effectively while giving AI systems clear signals about content structure and relationships.

When you successfully combine GEO and SEO principles, you create an exceptional user experience. Your content ranks well in traditional search results and appears prominently in AI-generated responses, reaching users through their preferred search method while maintaining consistent quality and messaging.

To achieve this balance, regular testing and refinement will need to become essential parts of your content strategy. Why? Because what works in traditional search results might need adjustment for AI systems, and vice versa.

Tracking performance across search ecosystems

Tracking performance in today’s search environment requires a more comprehensive approach than ever before. You need to keep tabs on both traditional search rankings and AI-driven citations to really understand the true impact of your content.

Modern search ecosystems present unique challenges for performance measurement. Each platform uses distinct algorithms and ranking factors, making unified tracking increasingly complex. To build a clearer picture of their content’s reach and effectiveness across different search environments, organizations must carefully analyze multiple data sources.

The good news? Advanced analytics tools now offer insights into AI-driven traffic patterns, helping you stay ahead of developments in GEO-specific tracking capabilities. These tools show you valuable data about how your content performs across search platforms, and how users interact with AI-generated responses that feature your content.

Here are some key tools to help you track and optimize your GEO efforts:

• SEMRush – Tracks traditional keyword rankings and provides insights into AI-powered search trends.
• Google Search Console – Helps monitor organic search performance, structured data errors, and AI-driven results from Google’s AI Overviews.
• Perplexity AI Citation Tracker – Identifies when and how your content is cited within AI-generated responses.
• ChatGPT Insights – Analyzes how OpenAI’s models generate responses and reference third-party sources.
• Wordbrew – Extracts internal expertise and structures content in a way that AI engines can easily interpret and prioritize.
• Schema Markup Testing Tool – Ensures your structured data is correctly implemented for better indexing by AI systems.

Understanding how AI-driven platforms prioritize and surface your content is crucial for refining your optimization tactics. Unlike traditional search rankings, AI engines pull and synthesize data differently, making it essential to track how your content is referenced and cited.

Instead of focusing solely on keyword rankings and organic metrics, successful tracking strategies now need to look at referral traffic from AI engines, citation patterns, and response structures.

Implementing tracking systems requires careful planning—each AI search ecosystem may have unique parameters, necessitating tailored tracking configurations to ensure accuracy. Establishing a robust measurement framework early on helps capture reliable, actionable insights about your content’s performance.

Plus, localized search behaviors add another layer of complexity. Factors like regional search trends, language nuances, and platform adoption rates influence content visibility.

To stay ahead, businesses must account for these variations and continuously refine their GEO strategies based on AI search behavior and user interactions.

Embracing the future of search with GEO

The future of GEO is bright as AI technology continues to evolve, moving us beyond basic Q interactions to more advanced capabilities that anticipate user needs and provide precise, contextual responses.

The integration of voice and visual search will revolutionize user interaction with content, making it important to optimize for multiple formats to maintain visibility and reach users through their preferred methods.

Success will favor those who adapt their content to an ecosystem where text, images, audio, and video harmonize, all while focusing on delivering valuable content that effectively serves both humans and AI.

Thanks to the following experts for participating in this piece:

• Isiah Cruz
• Lauren Funaro
• Dan Meers
• Afnan Rehan