Artificial General Intelligence Archives

Digital visibility for 2026

The Search Behavior is Leaning Towards Answer Engines

Less than 6 months ago, we provided you with a 10-step to-do list to improve your digital visibility with the AI search tools (Generative Engine Optimization / Answer Engine Optimization). Since then, there have been some more changes in the search landscape. While your marketing team may optimize meta descriptions, builds backlinks and provide basic FAQs, over 400 million users weekly bypass traditional search results entirely, directing their queries to ChatGPT, Perplexity, Claud, and Google AI Overviews instead. This shift represents a critical gap in most modern SEO strategies.

Many people have been screaming about the demise of traditional search, but for non-branded search, the strategy for appearing in the results for conventional and AI search is similar enough not to matter. Generative Engine Optimization (GEO)/Answer Engine Optimization (AEO) does change the paradigm for branded search. GEO is now an essential extension of your visibility strategy across all emerging search paradigms relevant in 2026 and beyond. Unless your plan accounts for AI-driven answer engines, you’re missing substantial audience reach.

Understanding Answer Engine Optimization

Answer Engine Optimization is the process of organizing and formatting content so that AI-based platforms can extract, cite, and display your information as authoritative answers to user queries. While traditional SEO focuses on appearing in search engine results pages (SERPs), AEO targets visibility across a broader ecosystem: AI chatbots like ChatGPT, Claude, and Gemini; AI-powered search features such as Google AI Overviews and Bing Copilot; voice assistants including Alexa, Siri, and Google Assistant; and answer-based platforms like Perplexity AI.

This distinction matters significantly. Over half of all searches are now zero-click searches—users get answers from AI summaries without visiting websites. When your content appears in these AI responses, you gain brand visibility even when users don’t click through to your site.

How AEO and SEO Work Together

AEO and SEO aren’t competing strategies; they’re complementary approaches targeting the same goal—discoverability—through different user behaviors and search mechanisms.

Traditional SEO maximizes keyword rankings in SERPs, drives site traffic, builds backlink profiles and domain authority, and optimizes page experience metrics through technical performance. AEO, conversely, prioritizes citations and mentions in AI-generated responses, direct answer delivery for conversational queries, structured data that AI models can easily interpret, and authority indicators that AI systems recognize and trust.

Both methods are necessary for comprehensive digital marketing. Search behavior is fragmenting rapidly. Gartner projects that 25% of all organic traffic will be captured by AI chatbots and virtual assistants by 2026. Companies implementing integrated AEO and SEO strategies simultaneously capture visibility across traditional search results and AI-powered platforms, maintaining traffic growth as the search landscape evolves.

Why Integration Matters

Consider how your target audience actually searches today. Some still use Google’s keyword-based search. Others query ChatGPT conversationally. Many use voice search while multitasking. Increasingly, demographics rely on AI assistants within social media for recommendations.

Traditional SEO alone captures only a portion of this fragmented audience. AEO extends your reach to segments that have adopted AI tools as their primary research method—demographics that SERP optimization completely misses. The expansion of the addressable audience directly translates into business growth.

The Business Reality: Threats and Opportunities

The shift to AI-powered search presents both danger and opportunity. Stack Overflow experienced an 18% traffic reduction after ChatGPT’s introduction because users now get code answers without visiting the site. However, companies that adopted AEO strategies successfully resisted these traffic patterns, maintaining visibility and revenue.

Zero-click searches aren’t lost opportunities—they’re visibility opportunities requiring different optimization approaches. When your brand is cited as a source in AI-generated responses, you gain several advantages: brand exposure to users who might never have clicked traditional search results, authority positioning through credible citations in AI platforms, indirect traffic as users discover your content through AI and later visit your website, and voice search exposure through smart speakers and assistants mentioning your brand.

Reaching the Evolving Demographics

Different groups prefer different search methods. Forty-five percent of millennials use social media for searches. Voice commerce is projected to reach $80 billion annually. AEO strategies support voice-first users who prefer smart speaker answers, AI-native searchers comfortable with ChatGPT and Perplexity, mobile multitaskers who need quick answers while driving or working, and social media researchers using Meta AI or platform-specific assistants.

Answer engines allow you to reach broader audiences than competitors focused solely on traditional SEO.

Essential AEO Implementation Strategies

Implementation of AEO is not the same as abandoning your SEO startegy. The best approach mixes AEO optimization with sound fundamental SEO practices. Here are a sumary of the core strategies:

Structure Content for Direct Answer Delivery

AI models prioritize straightforward questions and concise answers, placing them at the top of content sections. Implement this by placing direct, complete 40-60 word answers as the first block of relevant sections, formatting H2 and H3 tags as actual user questions, creating dedicated question-and-answer sections for frequently asked queries, and writing conversationally to match how users naturally phrase their queries.

This formatting simultaneously enhances user experience (a core SEO ranking metric) and simplifies content extraction by AI models.

Implement Comprehensive Schema Markup

Structured data acts as an interpreter, helping AI tools comprehend your content’s meaning and connections. Priority schema types for AEO include FAQPage (for question-answer content), HowTo (for step-by-step tutorials), Article (for editorial content), LocalBusiness (for location-based information), and Organization (for company information).

Schema markup benefits both AEO and traditional SEO. Google displays rich results in regular searches, making your content more accessible to AI platforms that crawl for training data and provide real-time responses.

Build Topical Authority Across Platforms

AI systems prefer trusted voices indicated by consistent citations, reviews, and authoritative external links. Build this authority by creating and optimizing business profiles on Google Business Profile, Yelp, and industry directories; ensuring consistent Name, Address, and Phone Number information (NAP) across all listings; soliciting genuine customer reviews on reputable sites; and publishing original research or data that others reference and link to.

These off-site signals strengthen both traditional SEO link profiles and train AI models to recognize your brand as a reliable citation source.

Target Conversational Query Patterns

Answer engines process conversational queries differently from keyword-based searches. “What are some good restaurants in Los Angeles?” differs fundamentally from “best restaurants in Los Angeles.”

To maximize conversational visibility, research questions using tools like Answer the Public and Google’s People Also Ask feature, map questions to buyer journey phases (awareness, consideration, decision), write content answering specific how-to, what-is, and should-I questions, and use natural language rather than awkwardly inserting keywords.

This approach aligns with Google’s shift toward natural language processing and user intent, enhancing both AEO and conventional SEO performance.

Most importantly, implement the 10 tangible steps we already provided you in August.

1. 1. Ensure your site is crawlable by LLM bots.
  2. Maintain strong traditional SEO rankings.
  3. Target “query fanout” keywords generated by LLMs.
  4. Keep brand mentions consistent across platforms.
  5. Avoid heavy reliance on JavaScript for core content.
  6. Engage on UGC-heavy platforms like Reddit and Wikipedia.
  7. Write in machine-readable, quotable formats with schema and clear facts.
  8. Optimize AI-generated content for unique terms, pros/cons, expert quotes, and structured data.
  9. Stick to verifiable facts and introduce original data.
  10. Invest in digital PR to increase brand authority and citations.

Measuring AEO Success

Standard analytics tools focus on clicks and rankings but miss citations and mentions—the core AEO metrics. Effective measurement requires distinct methodologies incorporating both direct AEO measures and integrated SEO-AEO metrics.

Direct AEO Metrics

Track mentions in AI-generated answers across ChatGPT, Perplexity, and Google AI Overviews using citation tracking tools. Monitor how frequently your content appears in Google’s featured snippets. Test branded and non-branded queries in voice assistants to assess voice search visibility. Create custom GA4 channel groups to isolate answer engine referrals and analyze traffic sources.

Tracking AEO mentions is like monitoring stock market transactions—each citation serves as an indicator of your content’s visibility and engagement.

Integrated SEO-AEO Measurement

Monitor growth in zero-click impressions and watch for declining click-through rates with deep impressions, indicating AI Overviews or featured snippet appearances, and track performance on conversational queries alongside traditional keywords. Conduct a conversion path analysis to show how AI discovery drives conversions. Watch for branded direct traffic growth from users learning about your brand through AI channels. Analyze question-based query rankings across conversational and traditional searches.

Comprehensive tracking systems that capture both traditional SEO performance and AEO visibility provide complete insight into how optimization efforts drive business results.

The Competitive Landscape Ahead

The search environment will become increasingly fragmented as AI tools become more sophisticated and personalized. Future answer engines will deliver varied results based on context, previous user actions, and individual preferences, making cross-platform visibility even more critical.

Companies that delay AEO adoption risk losing competitiveness to early adopters already gaining traction in AI-based search. The opportunity cost increases continuously as platforms train their models. Notably, 25% of top-quality sites in ChatGPT’s training data have already opted out of future training, creating space for brands producing authoritative content.

Getting Started with AEO

Begin by conducting a content audit to identify pages that could be reorganized to improve AI extraction. Apply schema markup to high-value pages, starting with FAQs and how-to guides. Maximize business profile presence across all platforms AI tools visit. Develop content incorporating questions your audience actually uses in conversational queries. Track and refine based on which content begins appearing in AI-generated answers.

The implementation complexity can be substantial, but the payoff justifies the effort. Integrated solutions that simultaneously achieve maximum visibility across conventional search engines and AI answer platforms ensure you reach your whole addressable audience regardless of the search method.

The Bottom Line

The brands dominating search visibility in 2026 won’t be those choosing between SEO and AEO. There’ll be those who understand how these strategies blend across all modern search touchpoints. The fragmentation of search behavior means that relying on a single approach guarantees missed opportunities.

Your content strategy must now account for how information flows through multiple channels: traditional Google results, AI chatbots, voice assistants, and social platforms. The companies that master this multi-channel visibility—maintaining authority, relevance, and discoverability across all platforms—will capture the full spectrum of search-driven opportunities.

AEO isn’t a future consideration. With 400 million weekly users already bypassing traditional search, it’s a present necessity. The question isn’t whether to implement AEO, but how quickly you can integrate it into your existing SEO foundation to capture the full addressable market of 2025 searchers.

Relevant Resources:

- - Gartner – “The Future of Search: AI-Powered Answer Engines” (2024-2025) https://www.gartner.com/en/search-marketing Provides the foundational 25% traffic shift projection cited in the article; includes broader enterprise-level research on search fragmentation, AI adoption timelines, and competitive implications for brands.
  - Google Search Central – “Answer Engine Optimization Best Practices” https://developers.google.com/search Official Google documentation on AI Overviews, featured snippet optimization, and schema markup for AI platforms—directly supports the article’s schema implementation and content structure recommendations.
  - Schema.org – Structured Data Documentation https://schema.org Complete reference for FAQPage, HowTo, Article, LocalBusiness, and Organization schema types mentioned in the article; essential technical foundation for implementing AEO markup.
  - Perplexity Labs – “Understanding Answer Engine Results” https://www.perplexity.ai Provides insight into how conversational AI platforms extract and cite sources, directly relevant to understanding citation mechanics and how brands appear in AI-generated responses.
  - Search Engine Journal – “Answer Engine Optimization: The New SEO Frontier” https://www.searchenginejournal.com Industry analysis on AEO vs. traditional SEO, emerging best practices, and case studies of brands adapting to fragmented search—provides broader context for the article’s core thesis.
  - Semrush – “2025 State of Search Report: AI’s Impact on SEO” https://www.semrush.com/state-of-search Data on zero-click searches, AI platform usage statistics, and how top brands are optimizing for both traditional and AI search—validates the article’s claims about search behavior fragmentation.

Building Content Engines with AI Automation for 2026

Content creation is rapidly changing with artificial intelligence (AI). Research, drafting, editing, and formatting, once weeks-long tasks, are now much faster with AI tools. This article shows how AI acts as an essential partner in content development, streamlining workflows and redefining marketers’ and creators’ best practices.

Efficiency in content workflows drives this shift. Using AI at each stage reduces manual, repetitive work, freeing teams for strategic, creative tasks. AI boosts efficiency, strengthens brand consistency, and enables creative options beyond resource limits. Still, AI brings challenges, including algorithmic bias, less human oversight, and concerns about originality and authenticity. This article covers four phases where AI speeds content creation, turning it from slow to flexible and scalable, while noting these challenges.

From Idea to Architecture: Intelligent Research and Strategic Outlining

Effective content starts with strong planning. Once slow due to research and analysis, this is where AI first proves valuable.

Developing a Data-Driven Content Strategy

Set clear goals and know your audience. AI speeds this up using data. It audits content, reviews successes, and analyzes competitors for gaps and trends. Instead of manual checks, AI tracks search results, keywords, and interests. For example, if a blog loses traffic, AI suggests quick updates—new stats, examples, or structure. This keeps content fresh and useful.

AI populates your content calendar with ideas based on trends and audience preferences, streamlining the ideation process.

Generating Strategic, SEO-Optimized Outlines

Modern AI outlines use three analytical pillars to create comprehensive content frameworks. First, the AI analyzes search intent to determine what users want from a query. Are they seeking information, ready to buy, or comparing options? Understanding whether intent is informational, transactional, or commercial helps the AI structure the outline to align with user expectations and the stage. This ensures the content delivers what the reader needs at the right moment.

Second, the AI conducts a competitor gap analysis. It reviews top-ranking articles on Search Engine Results Pages. Instead of repeating existing content, the AI identifies subtopics, questions, and angles that others overlook or under exploit. This ensures your content doesn’t just match others—it surpasses them. Your content becomes more complete, valuable, and better at satisfying user queries that competitors miss. This competitive intelligence turns your content from just another article into a definitive resource.

Finally, AI uses semantic keyword analysis to group related concepts and phrases. Instead of focusing on one keyword, it maps the ecosystem of related terms and ideas readers expect. This ensures in-depth topic coverage and helps the article answer more user queries, including long-tail and related questions. These three elements, when combined, create outlines that are strategic, structured, and optimized for search engines and readers.

The result is a clear H2/H3 structure aligned with search intent. These outlines may include optimized CTAs and graphic sections. Writers get outlines with H2/H3s matching user queries and notes on where to add CTAs, graphics, or checklists. This prevents weak structure and ensures content works for SEO and conversions.

Structured outlines prepare marketers for effective AI-generated content. Prompt engineering is crucial for quality AI results. Simple prompts give plain output; strong prompts deliver better results. To maximize AI, use a clear formula:

A goal, audience, tone, and format make a great prompt.

A strong prompt is specific. Add topic, audience (e.g., beginner students), tone (e.g., witty or formal), and limits (e.g., length or excluded competitors). Giving context helps AI match your brand and goals.

Generating First Drafts and Overcoming Block

AI tools excel at first drafts, often the toughest stage . Research shows AI helps writers overcome blocks and saves time. Rather than begin with a blank page, AI quickly turns outlines into drafts. These tools brainstorm headlines, new angles, and alternative openings. AI creates raw material, but human writers refine it and add expertise. Jasper and ChatGPT are top tools for rapid drafts in formats from blogs to marketing copy.

Creating Specialized Copy and Visuals at Scale

AI does more than write. For marketers with many channels, AI can quickly and at scale create product descriptions, social posts, and newsletters.

AI-powered generators create graphics and presentations from text prompts, enabling non-designers to create professional visuals. Video tools like Synthesia let users build instructional videos with AI avatars and voices in 120+ languages. Scripts become videos in minutes, making design easy and assets authoritative.

Enhancing SEO and Performance

AI is vital for performance marketing. These tools use SEO data to fit requirements. They go past keywords, scoring content, finding related keywords, and crafting optimized meta details.

AI helps keep content updated. A sound plan keeps material relevant. AI identifies underperforming articles, analyzes rank and traffic, and suggests updates such as new examples, improved flow, or rewrites. Teams improve content without manual reviews.

Proofreading, Paraphrasing, and Brand Consistency

AI polishes content and fixes errors. Editing tools find grammar issues, suggest structure changes, and ensure consistency.

AI rewrites content fast. It checks context and adjusts tone while keeping the message strong. Big teams struggle to maintain a consistent voice. Training AI on your brand means all content matches your style. Upload style guides or samples so AI learns your preferences. This is crucial for compliance and growth.

Scaling with Automation and Content Atomization

Scaling content with AI means automating and breaking material into platform-specific pieces. This keeps creation smooth.

The Content Waterfall: Repurposing at Scale

Repurposing content for social channels was slow and generic. Now, AI automates this ‘Content Waterfall’ process.

AI can turn one article into 20+ content pieces for different platforms (Lindley et al., 2025). It changes tone, length, and format for each channel:

- - A series of short, punchy scripts for YouTube Shorts or TikTok.
  - An educational, numbered thread for LinkedIn.
  - Visually focused captions and graphic prompts for Instagram or Pinterest.

Teams cover more channels and keep consistent messages without more hires. Descript and Lumen5 turn text into videos and audio for many platforms.

Building Automated Content Pipelines

Big teams use AI and automation tools. Gumloop and Zapier connect Notion, Google Docs, ChatGPT, and Slack.

These systems use simple “if this, then that” flows. For example: IF a brief is added to Notion, THEN AI generates an outline, THEN the draft appears in Google Docs, THEN the writer is notified in Slack. This removes manual work and saves hours. To start, automate outline generation. This step helps teams build confidence with AI and prepares them for more complex workflows. This matters for teams with heavy content demands who want to focus on strategy and quality.

Conclusion

AI in content creation isn’t just a tech upgrade—it redefines what it means to be a creator. The AI content market is set to grow fast, making this normal, not a trend.

AI brings speed and efficiency to content development, yet it is important to recognize its limitations. While AI can generate drafts, outlines, and repurposed materials with impressive rapidity, it lacks the nuanced empathy, creativity, and contextual understanding that human contributors provide. AI-generated content often requires careful human oversight to ensure factual accuracy, as these tools can inadvertently reproduce errors or introduce misinformation. Furthermore, AI systems may reinforce biases in their training data, raising ethical concerns about fairness and inclusivity. Questions about originality and the authenticity of ideas also persist, since AI-generated outputs are based on pre-existing data and cannot replicate true human inventiveness. Therefore, while AI can handle repetitive and time-intensive tasks, human intervention remains essential for factual verification, offering unique insights, and upholding ethical standards. Through this collaboration, creators can produce content that not only achieves operational efficiency but also maintains originality, relevance, and a strong ethical foundation. Ultimately, future success will depend on using AI as a supportive tool while prioritizing distinctly human qualities in the creation process.

To translate the theoretical benefits of AI into tangible outcomes, marketers should conduct a systematic audit of their existing workflows. This should include mapping each stage of the content creation process and critically evaluating specific tasks where inefficiencies or bottlenecks occur. Based on these findings, marketers can then select a targeted area—such as content ideation, drafting, or distribution—where AI integration would yield measurable improvements. Piloting AI implementation in this identified area should be accompanied by clear key performance indicators to assess its impact on both efficiency and quality. By adopting a structured, evidence-based approach to AI integration, organizations can move beyond experimentation toward developing a robust, innovative content strategy that fully leverages the complementary strengths of human expertise and AI technologies.

Relevant Resources:

SEO Strategies for 2025 – Fall Edition

Strategies for better Search Rankings in the AI Era

Highlights

- - AI-Driven Search Takes Over
    Search engines now use advanced AI to interpret context and intent. Zero-click searches exceed 60%, AI summaries appear in ~20% of results, and answer engines like ChatGPT and Perplexity are diverting traffic from traditional search.
  - Answer Engine Optimization (AEO)
    SEO must adapt to answer-first platforms by structuring content for direct responses, implementing schema markup, and optimizing FAQs and conversational queries.
  - Community and Forum Content Surge
    Reddit and other forums gain visibility due to demand for authentic, experience-based answers, making participation in niche communities an effective visibility strategy.
  - Sales-Focused SEO
    Middle- and bottom-funnel content targeting commercial intent keywords is critical. Product integration, case studies, and branded content improve conversions and rankings.
  - Experience as a Ranking Factor
    Google prioritizes firsthand experience (E-E-A-T). Unique insights, original research, and case studies help content stand out amid AI-generated material.
  - Intent-First Optimization
    Search algorithms now value user intent and engagement quality over exact keyword matches. Content clusters, semantic relevance, and problem-solving approaches outperform keyword stuffing.
  - Zero-Click Strategies
    Featured snippets, knowledge panels, and brand-building content are essential to gain visibility even when users don’t click through to websites.
  - Technical SEO and Core Web Vitals
    Fast, stable, mobile-friendly sites remain foundational. Optimizing for Core Web Vitals, structured data, and schema markup is required for strong rankings.
  - Backlink Quality Over Quantity
    Relationship-driven, authoritative backlinks matter more than volume. AI tools help identify and secure high-value link opportunities.
  - Continuous Monitoring
    Frequent algorithm updates and AI-driven changes demand ongoing tracking of performance metrics beyond rankings, including brand awareness, cross-platform visibility, and conversion rates.

The SEO environment has radically changed. What was successful in 2023 is already outdated, and the evolution continues daily into 2025. We keep you up to date with what with real world solutions to Search Every Optimization we have implemented for our clients. Frankly, those who keep up with the change are doing very well, and some who are not are experiencing difficulties.

Unfortunately, many think that a redesign of the website will solve their problems which is almost never true. On the other hand, the ability to shift content strategy based on the changes in AI will separate successful businesses from those that are left behind at the bottom of search results. The emergence of AI-based search, the appearance of new types of content, and the development of user expectations are among the most significant trends in SEO shaping 2025 efforts.

Search engines are currently utilizing advanced AI-based systems that comprehend the context, intent, and quality of content at unprecedented levels. Zero-click searches now comprise more than 60 percent of searches, AI summaries occupy close to 20 percent of results, and answer engines such as ChatGPT and Perplexity are capturing a significant portion of the traditional search market share. YouTube, the second largest in the world, is also increasing its role in SEO strategies and provides exceptional opportunities in terms of organic search traffic and visibility.

The companies that are doing well in the new environment are not simply adjusting; they are redefining their whole content and search visibility strategy. Video content is also becoming a key component in improving visibility and interaction on both Google and YouTube, and has become a valuable tool in modern SEO.

The New Era of SEO

Search Everywhere Optimization is the new paradigm for search. With the increasing integration of artificial intelligence and machine learning into search engines, user search behavior has undergone a radical shift, and this is equally true of the search engine’s understanding of search queries. Modern digital marketers need to reassess their SEO practices to align with these innovations. It is a success in this new age because it emphasizes high-quality, user-centric content that fulfills search intent and utilizes the latest AI-driven tools. When focusing on these factors, companies can improve online presence, and organic traffic, by maintain a higher placement on search result ranking pages. The future of SEO is all about how the search engines work with information and how you need to adjust your strategy so that you match the evolving demands of the search users and the search engine.

Setting SEO Goals and Objectives

An effective SEO plan is based on practical, achievable objectives. The first step in developing effective strategies is to clarify what you would like to accomplish with your SEO activities, whether it be increasing organic traffic, achieving a higher ranking with search engines, or generating higher-qualified leads and conversions. Align your SEO goals with your overall business objectives to ensure that all optimization efforts work in your favor. Be specific and measurable: monitor key metrics such as search engine rankings, organic traffic, click-through rates, and conversion rates. Establishing data-driven goals provides you with a roadmap for your SEO strategy. It allows you to quantify the impact of your work, making it more likely to make adjustments and optimize it for further success.

1. AI-Powered Search Results Are Reshaping Visibility

The AI Overviews of Google are now shown on almost 20 percent of organic search traffic, as compared to only 7 percent in June 2024. In the information-heavy sectors such as technology and business, more than one-third of search results currently include AI-generated summaries. Answers generated by AI are altering the search results page (SERP) in response to user queries, delivering direct answers that affect user behavior and change the way users engage with search outcomes.

The change poses challenges and opportunities. As much as AI summaries can decrease direct clicks to websites, they also provide websites that are not in the top 10 results with a new citation opportunity.

Actionable Strategy:

- - Structure content in clear Q&A formats with concise 40-60-word answers
  - Use bullet points, numbered lists, and tables for easy parsing by AI.
  - Include authoritative statistics and data that AI systems can cite.
  - Focus on answering specific questions rather than broad topics.
  - Organize information to help search engines understand your content and generate accurate AI answers.

2. Answer Engine Optimization (AEO) Is The New SEO

Traditional search engines are evolving into answer engines. ChatGPT Search was introduced at the end of 2024 and is estimated to grow to 1 percent of the search market in 2025. Perplexity has increased to over 15 million users, and referral traffic has grown by 71 percent annually.

This represents a radical shift from connecting users to websites to connecting them with direct answers and citations.

As generative AI products generate more content, it is essential to evaluate the quality and reliability of this content to prioritize content ranking in answer engines.

Some essential steps include developing and maintaining FAQ sections for every significant content piece. You should also write in a way that your content addresses conversational queries. Next, you must pay close attention to implementing proper schema markup to help AI systems understand your content. And, finally, you must monitor performance across multiple answer tools, and not just Google.

3. Community and Forum Content Domination

Following the core refresh in August 2024, Reddit’s visibility improved to become the third most visible search result, next to Google, with a fourfold increase in Google traffic. Users are also actively incorporating Reddit into their searches to obtain more authentic and experience-based responses.

This tendency represents the desire of users to consume authentic, firsthand information, as opposed to AI-generated or strictly promotional texts.

Strategic Approach:

- - Identify relevant communities where your target audience actively participates.
  - Engage authentically in industry-specific forums.
  - Create content that answers fundamental questions being asked in these communities.
  - Develop relationships with community moderators and active participants within the community.

4. Sales-Focused SEO Content Strategy

The best SEO practices in the coming months will incorporate sales goals into content optimization, rather than focusing solely on the informational content in the top-of-funnel section. Winning strategies will be geared towards middle- and bottom-funnel keywords that drive conversions. Competitive analysis is crucial for identifying and optimizing target keywords, ensuring your content is ranked in high-traffic, commercially relevant search results.

Studies have shown that Google tends to give preference to websites with a higher percentage of branded content, implying that there is no cost associated with incorporating product promotion into SEO content.

The specific page should be audience- and goal-conversion focused, and on-page items should be customized to optimize visibility and interaction.

Content Integration Methods:

- - Weave product demonstrations and case studies into informational articles.
  - Target commercial intent keywords alongside informational ones
  - Ensure the target keyword is included in on-page elements, such as page titles, header tags, and meta descriptions. Although some elements, like meta descriptions, are not direct ranking factors, they can improve click-through rates and user engagement.
  - Create and optimize blog posts as part of a sales-focused SEO strategy to attract backlinks, drive organic traffic, and enhance online visibility.
  - Include video demos and interactive elements within educational content to enhance learning experiences.
  - Develop content that serves both search rankings and sales enablement.

5. Firsthand Experience as a Ranking Differentiator

The first E in the E-E-A-T guidelines at Google prioritizes experience. As the volume of AI-generated output increases, covering search results, unique insights, and firsthand experiences are now important ranking factors.

This was confirmed by the Google API leak, which exposed an artificial factor of OriginalContentScore. This factor is actually a ranking factor that proves search engines are actively scoring content based on novelty and authenticity.

Experience-Driven Content Creation:

- - Conduct original research and surveys within your industry.
  - Interview subject matter experts and include unique insights.
  - Share specific case studies and real-world applications.
  - Document proprietary processes and methodologies
  - Include personal anecdotes and lessons learned from actual implementation.

6. User-Centric Intent Optimization Over Keywords

The percentage of Google AI Overviews that include a perfect match to the key phrase is only 5.4%, which suggests that search engines no longer focus on a specific phrase, but instead on the user’s intention.

The Navboost platform at Google analyzes various types of clicks, including good clicks, longest-lasting clicks, and bad clicks. That is, the quality of engagement is considered more important than mere traffic data.

Intent-First Optimization:

- - Research the specific problems your audience faces at each stage of their journey. Effective keyword research is essential here—using keyword research tools like SEMrush or Ahrefs helps uncover search intent, relevant topics, and new SEO opportunities.
  - Create content clusters that address related questions and concerns, and optimize for semantic relevance by using natural language and addressing related concepts to improve visibility in AI-driven search engines.
  - Develop shorter, focused pieces that interlink rather than massive pillar pages.
  - Focus on solving specific user problems rather than targeting keyword volumes.
  - Analyze queries entered into the search bar to identify long-tail keyword opportunities and better understand user needs.

7. Zero-Click Search Strategy Development

As zero-click searches now account for 60% of all Google searches, effective SEO practices must consider the visibility that does not result in direct traffic to a website.

This change requires the creation of content strategies that will foster brand awareness and authority, even when users do not click through to your website. It should be noted that measuring traffic is not as important as engagement, conversions, and the quality of buyers and visitors, particularly as zero-clicks and AI-based SERPs become more prevalent.

Zero-Click Optimization Tactics:

- - Optimize for featured snippets with clear, concise answers.
  - Develop content specifically designed for knowledge panels.
  - Create brand-focused content that builds recognition in search results.
  - Track brand search volume and awareness metrics alongside traditional traffic metrics to gain a comprehensive understanding of your brand’s performance.
  - Use local SEO optimization for location-based zero-click queries.
  - Leverage zero-click features to increase organic traffic and brand visibility.

Examine the most popular results to understand what Google rewards without clicks, as it may be helpful to structure your content in accordance with what is highly ranked. It is essential to stay up-to-date with the changes in Google search that can impact zero-click visibility, ensuring your SEO strategy remains effective and enhanced.

Optimizing for Clarity and Context

Clarity and context are now more than ever before in the era of AI-driven search engines. To produce content that is notable on search engine results pages, emphasize the use of natural language that reflects the search and speech of users. It is essential not to emphasize stuffing keywords, but instead to focus on content that helps users, making it easy for search engines to understand the purpose and relevance of each web page. Divide your material and use clear header tags, interesting meta descriptions, and key internal links to help guide your visitors and search engines across your site. Beyond featured snippets optimization, which means the ability to give a brief and direct response to frequent search queries, can also increase your visibility and attract more organic traffic. It aims to produce content that not only ranks well but also provides real value to your target audience.

Building High-Quality Backlinks in 2025

Backlinks are still considered the cornerstone of any successful SEO strategy, yet the process of link building is evolving with the emergence of AI-powered search engines. In 2025, the quality of an earned backlink will not be a matter of volume, but rather the development of proper relationships with other websites and offering valuable, relevant content that will naturally lead to links. Consider becoming a guest blogger, creating detailed resources, and promoting user-generated content that others will find helpful to refer to. Utilize the power of modern AI tools to analyze your backlink profile, identify potential loopholes, and uncover new collaboration opportunities. A diverse and authoritative backlink profile can help increase the credibility of your website, improve your ranking with search engines, and drive organic traffic from a wide range of sources.

Technical Foundation: Core Web Vitals and Performance

Search engines continue to prioritize technical performance based on Core Web Vitals metrics. The next Interaction to Next Paint (INP) value will be added to Largest Contentful Paint (LCP) and Cumulative Layout Shift (CLS) as necessary ranking measures. Technical SEO is crucial for enhancing the site’s speed and overall performance, which directly impacts user experience and the webpage’s visibility on search engines.

Technical Optimization Priorities:

- - Compress images using WebP and AVIF formats.
  - Implement lazy loading for below-fold content.
  - Minimize third-party scripts and unnecessary JavaScript.
  - Ensure mobile-first design with touch-friendly navigation.
  - Reserve space for dynamic content to prevent layout shifts
  - Apply image optimization techniques, such as image compression, descriptive file naming, and adding alt text with targeted keywords, to enhance site speed and improve search rankings.

Using high-quality images with descriptive alt text and proper schema markup enhances the user experience, supports visual search optimization, and contributes to faster content loading. Technical improvements like these can have a significant impact on SERP rankings.

Structured Data and Schema Implementation

Structured data has become a choice and a requirement in contemporary SEO. Good schema markup enables rich results and allows AI to understand the context and relationships within content. The adoption and validation of structured data can be easily achieved, and by leveraging reliable SEO tools, the information will be accurate and have a significant impact on search results. Structured data also makes larger content marketing plans more productive, as it enhances the visibility and interaction of content across multiple media.

Priority Schema Types for 2025:

- - Article schema with author information and publication dates
  - Product schema with ratings, prices, and availability
  - FAQ schema for question-and-answer content
  - LocalBusiness schema for location-based businesses
  - HowTo schema for instructional content

Staying Updated on Algorithm Changes

SEO is a constantly evolving world with hundreds of changes made to the search engines every year. It is imperative to keep up with these changes to maintain and increase your organic traffic. It should be a habit to follow industry news, attend webinars, and conferences to stay up to date with recent events. Track the performance of your website using AI-powered tools and rapidly detect the impact of any algorithmic changes. Of particular interest are trends in the field of SEO, including the emergence of AI-based search engines, the growing importance of core web vitals, and the role of user-generated content in search engine rankings. Being proactive and flexible will keep your SEO strategy contributing to organic traffic and showing results, regardless of how the search landscape changes.

Measuring Success in the New SEO Landscape

Traditional metrics, such as organic traffic and keyword rankings, while still important, don’t tell the complete story of SEO success in 2025.

Expanded Metrics Framework:

- - Brand search volume and awareness tracking
  - Featured snippet and AI Overview appearances
  - Cross-platform visibility (YouTube, social media, answer engines)
  - Content engagement depth and time-on-page metrics
  - Conversion rate optimization from organic traffic
  - Share of voice in your industry’s search landscape

Website owners play a crucial role in tracking and interpreting these metrics to ensure ongoing improvements in SEO. High-quality content directly contributes to improved engagement and better performance across these key SEO metrics.

Building Your Fall 2025 SEO Strategy

The most effective SEO techniques in 2025 will combine these factors into a unified solution that is user-focused, featuring multi-search and AI-search optimization. Even though new AI-based approaches are being developed, the operational principles of classical SEO, i.e., creating original content and an adequate site structure, will remain a pillar and must be integrated with the new methods.

Begin with a content audit of your existing E-E-A-T signals to identify opportunities to incorporate first-hand experience and professional observations. Producing content that directly relates to the user’s needs and search intent is key to supporting your overall search engine goals. Build content around user purpose, not keyword lists, and perform technical Optimization that serves both humans and AI.

Keep in mind that SEO in 2025 is not just about ranking in Google; it is about creating omnichannel content authority that benefits users across all the platforms they seek information.

The companies that succeed in the new environment will be those that consider SEO as a component of a wider content and brand approach, one that is concerned with actual value creation, rather than search engine optimization.

Dream Warrior Group, a Los Angeles-based web design and digital marketing Company, provides solutions for your online marketing needs. Our expertise includes Search Engine Optimization (SEO), Social Media Posts and marketing, and Google PPC campaigns. Call us now at 818.610.3316 or click here.

How to Build up your Generative AI Optimization Engines – Part 2

Step 1: Be Crawlable

This may even sound simple, but this is a vital preliminary process. Your best bet for getting seen in large language models is to enable them to crawl your site. There are many LLM crawlers, such as OpenAI and Anthropic.

Specific crawlers are likely to act so predatorily that they can provoke scraping and DDoS mitigation actions. If you have automated blocks against aggressive bots, align with your IT team to make sure that you do not block the LLM crawlers that you do want to access.

When you deploy a CDN, such as Fastly or Cloudflare, your LLM crawlers should not be blocked by default.

Step 2: Continue Gaining Search Engine Optimization Rankings

The best strategy for GEO is relatively simple: target traditional SEO. Rank highly on Google (Gemini and AI Overviews), Bing (ChatGPT and Copilot), Brave (Claude), and Baidu (DeepSeek).

SEO remains crucial in Google Search and other search engines. However, the introduction of AI search with its advanced models is changing the game of generating and providing search results by eliminating the need to match keywords merely and instead offering highly context-sensitive and personalized search results.

Step 3: Target the Query Fanout

The current generation of LLMs does a little more than simple RAG. They generate multiple queries. This is called query fanout. LLMs analyze user queries and process entire sequences of text, allowing them to generate AI-generated responses that are tailored to user intent.

As an example, I also recently asked ChatGPT, “What is the newest Google patent that SEOs talk about?”, and it did two web searches on the queries “latest Google patent discussed by SEOs patent 2025 SEO forum” and “latest Google patent SEOs 2025 discussed” (which returned identical results as the former query).

Tips: Check typical query fanouts to your prompts and strive to acquire ranking on those keywords too.

The most common fanout patterns I encounter in ChatGPT involve using the word “forums” to inquire about a topic in the public and attaching “interview” to questions about people. Also often mentioned is the current year (2025).

Caution: fanout patterns can change across LLMs and may change over time as well. What we are seeing today may not be relevant in a year.

Step 4: Keep Consistency Across Your Brand Mentions

It is a rather basic but essential exercise for all people, whether in a business context or otherwise. Ensure your presence remains consistent across all platforms, including X, LinkedIn, your web page, Crunchbase, and GitHub. Always maintain the same profile description, regardless of where you are.

When listing your occupation on multiple social sites, such as “GEO consultant on small business,” do not alter it to “AEO expert” on Github or “LLMO Freelancer” in your press releases.

On ChatGPT and Google AI Overviews, people have claimed to see positive results within a couple of days by simply utilizing a consistent self-description throughout the web. The same can be said about PR coverage, too. The broader and better the PR coverage you get on your brand, the more you will get referred back to users by the large language models.

Step 5: Avoid JavaScript

With SEO, we preferred that our developers to use as little JavaScript as possible. With GEO/AEO, we insist on it!

The majority of LLM crawlers are unable to process JavaScript. You are out if your main content is buried in JavaScript.

Step 6: Embrace Social Media & UGC

LLMs appear to be heavily dependent on Reddit and Wikipedia. Both sites provide user-generated content on nearly any subject. And with various levels of community-based moderation, a lot of the junk and spam already gets weeded out. Platforms are now dealing with the issue of maintaining a balance between human contributions and the volume of AI-generated content and posts.

Donors can manipulate both platforms, but the general content trustworthiness of those systems is much more customary than it is on the internet. Besides, the two are constantly updated.

Reddit provides valuable insights to LLM labs on how individuals can engage in online discourse, the terminology used in various topics, and knowledge of specific specialty areas.

It is only logical to suppose that user-generated content that is moderated on websites such as Reddit, Wikipedia, Quora, and Stack Overflow will remain relevant in large language models.

I do not suggest spamming those sites, but whenever you have such an opportunity to influence how your brand and competitors are represented there, it might be worth considering.

Step 7: Create For Machine-Readability & Quotability

Write in a manner or style that large language models (LLMs) will understand readily and tend to cite. Although there is nobody who has it right yet, the following approaches appear to work:

Write indicating and factual words. Instead of typing something like “We are fairly confident that the shoe is good on our customers”, type something like this: 96 percent of buyers have self-reported being happy with this shoe.

Add schema. It has been argued many times. Very recently, Fabrice Canel (Principal Product Manager at Bing) stated that schema markup can assist LLMs to comprehend your content.

If you desire to be quoted in an already publicized AI Overview, then you are supposed to possess content that is approximately of the same length as the already available one. Having a high cosine can also assist, but you are not just supposed to copy the current AI Overview. And nerd-fans: yes, you can of course use dot product instead of cosine similarity, given normalization.

In case you use some technical terms that you wish to explain in your content, do so, ideally in a single sentence.

Include summaries of lengthy paragraphs of text, lists of reviews, tables, videos, and other forms of content formats that may be difficult to cite.

Step 8: Optimize your AI-generated content

To be cited for some topics in some LLMs, it helps to:

- - Add unique words.
  - Have pros/cons.
  - Gather user reviews.
  - Quote experts.
  - Include quantitative data and name your sources.
  - Use easy-to-understand language.
  - Write with positive sentiment.
  - Add product text with low perplexity (predictable and well-structured).
  - Include more lists (like this one!).
  - Provide valuable insights and actionable insights to support data-driven decisions, and ensure human oversight to maintain content quality and accuracy.

Nevertheless, such measures may backfire with other combinations of topics and LLMs.

Until well-established best practices become standard practice, in the short term, my advice is to think about what benefits users, and to experiment enthusiastically.

Step 9: Stick to the Facts

In more than 10 years, algorithms have been able to learn through text represented as triples such as (Subject, Predicate, Object) — in other words, (Lady Liberty, Location, New York). Text that has been disproven by known facts can be considered unreliable, and the information that agrees with the majority opinion and contains new information is the kind that will benefit both LLMs and knowledge graphs.

The facts presented can be validated using mathematical models, and the information provided to LLMs can be precise.

And stick to the ascertained facts. And include some original facts.

Step 10: Invest in Digital PR

All of this will be true of your site as well as literally any other site. How best to influence this? Digital PR!

The more coverage you get for your brand, the more likely LLMs are to repeat it to users.

I have even read situations where advertorials were used as sources!

Learn Who Your Competitors Are

As with other aspects of SEO, leveraging a good tool can reveal unexpected information. Review the list of competitors that are identified automatically on a regular basis. In case of any surprises, look into where they have been prompted and investigate the sources that was included. Are you placing well in those sources? if not, take action!

Is a competitor cited because of their profile, and you have no reviews? Ask your customers review your product.

Did a popular YouTuber interview the CEO of your competitor? You want to be featured on that show, or create your videos using the exact keywords.

Does your rival often find itself on the top 10 or some lists, whereas you can never break the top 5? It may be a good idea to provide the publisher of the list with a hard-to-resist affiliate offer. You may be the number one with the following content update.

Understand the Sources

Sources are consulted when LLMs carry out generation searching.

Investigate the leading sources that could provide a broad scope of pertinent prompts, but leave your site and rivals on the back street. Of these, you may hear some of the following:

- - A community like Reddit or X. Become part of the community and join the discussion. X is your best bet to influence results on Grok.
  - An influencer-driven website like YouTube or TikTok. Hire influencers to create videos. Make sure to instruct them to target the right keywords.
  - An affiliate publisher. Buy your way to the top with higher commissions.
  - A news and media publisher. Buy an advertorial and/or target them with your PR efforts. In some instances, you should contact their commercial content department.

Target Query Fanout

Once you have discovered the searches that query fanout is producing on your key prompts, create something with the express intent of targeting those search terms.

Whether that will be on your site, posted on Medium and LinkedIn, published in press releases, or even by paying to place an article–so long as it appears high in search engines, chances are good LLM-based answer engines will cite it.

Position Yourself for AI-Discoverability

Generative Engine Optimization is what is needed most nowadays- it is the vanguard of organic growth. At Peec AI, we are working on tools to help you track, influence, and succeed within this changing landscape.

We have seen clients doubling their LLM-fuelled traffic in 2 to 3 months with conversion rates as much as 20 times higher than conventional SEO traffic!

The question is not whether you are going to do any of the following: create artificial intelligence answers, monitor your brand mentions, or pursue source authority. The question is the urgency in doing so. The LLMs that consumers will use in the future are being trained now.

Conclusion

Generative Engine Optimization is quickly becoming a critical discipline as AI-driven search changes how users discover information. While many traditional SEO best practices still apply, GEO requires a deeper focus on machine readability, source authority, and positioning content where LLMs can find, trust, and quote it. Brands that adopt GEO now can capture early advantages in AI search visibility, potentially driving higher-quality traffic and stronger conversion rates. The future of search is being shaped today, and those who prepare for AI discoverability will be best positioned to lead in the next wave of organic growth.

How to Build up your Generative AI Optimization Engines – Part 1

Generative AI (generative engine) is any artificial intelligence (AI) that can generate content (text, images, audio, video, code, or a combination of many) as opposed to being merely a retriever or classifier of existing content and is deemed to be part of generative AI. Generative AI systems and models are composed of deep learning models, including neural networks, which make them a part of artificial intelligence. Optimization for Generative Engines is a subset of Serch Everywhere Optimization. This is a two part article, where I have separated the basics from the pratical work.

Highlights

- Generative AI & LLMs – Generative AI creates new content (text, images, video, audio, code) rather than simply retrieving information. Large Language Models (LLMs) like GPT-4 fall within this category, alongside models using GANs, RNNs, and hybrid neural networks.
- Generative Engine Optimization (GEO)/Answer Engine Optimization (AEO) – A new branch of SEO focused on making content discoverable and quotable by generative AI systems. It emphasizes understanding user intent, providing EEAT-rich content, and optimizing for AI-driven search environments.
- Two Core Strategies – Influence foundational models (often difficult for most creators) and optimize for Retrieval Augmented Generation (RAG), ensuring your content is chosen as a source and cited often.
- 10 Practical Steps for GEO/AEO –
  1. 1. Ensure your site is crawlable by LLM bots.
    2. Maintain strong traditional SEO rankings.
    3. Target “query fanout” keywords generated by LLMs.
    4. Keep brand mentions consistent across platforms.
    5. Avoid heavy reliance on JavaScript for core content.
    6. Engage on UGC-heavy platforms like Reddit and Wikipedia.
    7. Write in machine-readable, quotable formats with schema and clear facts.
    8. Optimize AI-generated content for unique terms, pros/cons, expert quotes, and structured data.
    9. Stick to verifiable facts and introduce original data.
    10. Invest in digital PR to increase brand authority and citations.
- Workflow & Tactics – Use GEO tools to identify competitors, analyze high-authority sources, target keywords from query fanouts, and leverage PR, influencer marketing, and affiliate opportunities to secure citations in AI responses.

Genrative AI Vs. Large Language Models

Generative AI allows the creation of content on a diverse variety of outputs, including generated text, image generation (such as realistic images), video generation, music generation, and voice cloning. The use of AI-generated media and content is becoming widespread, enabling the production of content at scale through generative artificial intelligence.

The Generative Engines that only have natural language processing characteristics fall under the large language models (LLMs). These are also a form of foundation models and are instances of advanced models that employ machine learning and neural networks. The generative AI models also employ generative adversarial networks (GANs), recurrent neural networks, and architectures that combine two neural networks. Data augmentation techniques utilize generative AI models to train machine learning models, relying on extensive data sets that contain synthetic and structured data. You can address complex problems in various fields by leveraging outputs from numerous generative AI models that demonstrate high levels of advanced capabilities.

In this article, we will discuss Generative Engine Optimization (GEO), a sub-form of Search Everywhere Optimization (SEO). The initial process of any successful GEO campaign is to generate content that Large Language models will want to link to or cite. To create that content, you need to understand your users’ intent! What is it that the user is interested in finding out, and what is his reason to come seeking answers? Unlike traditional search engines, you are not just optimizing content on sites; you are developing a comprehensive understanding of who, what, where, when, why, and how this content relates to your product or service. The users are not even on your site, and you have to guess the condition that leads them to perform the search.

GEO Strategy Components

Consider experiences that you wouldn’t typically expect to find directly within ChatGPT or similar systems:

- Engaging content like a 3D tour of the Louvre or a virtual reality concert. Generative AI can also automate the creation of web pages and digital assets, making it easier to deliver interactive and personalized experiences.
- Live data includes prices, flight delays, and available hotel rooms. While LLMs can integrate this data via APIs, I see the opportunity to capture some of this traffic for the time being.
- Topics that require EEAT (experience, expertise, authoritativeness, trustworthiness).

Users want a firsthand experience, but LLMs do not have one. Thus, the issue motivates LLMs to cite sources where the knowledge resides and can be accessed firsthand. Well, that is only one critical consideration; what then are the others?

We should differentiate between 2 strategies: the role of influencing the basis of the model and the role of grounding as an instructional tool. Whereas the former is mainly out of reach of most creators, the latter holds opportunities. To succeed, new SEO developments must incorporate improved AI tools to aid content creation and optimization, according to GEO.

Influencing Foundational and Large Language Models

The foundational models have a pre-determined set of data and are not able to learn anything outside their training sets once they are trained. These datasets can incorporate synthetic data, structured data, and data augmentation methods to enhance the performance and robustness of the models. On existing systems such as GPT-4, it is too late – such systems have already been trained.

However, this is relevant towards the future: a so-called refrigerator that is operating on o4-mini in 2025 and which, in theory, may have a preference towards Coke rather than Pepsi. This prejudice may affect purchasing decisions in the future.

Optimizing For Retrieval Augmented Generation (RAG)/Grounding

When large language models (LLMs) are unable to produce answers based solely on their training data, they employ the retrieval augmented generation (RAG) technique to incorporate new information and provide an answer. Such systems as AI Overviews or ChatGPT web search are based on this approach. RAG combines information retrieval and generative model outputs to provide contextually more precise and contextually appropriate answers, resulting in improved contextual knowledge of the system.

As SEO professionals, we want three things:

1. Our content gets selected as a source.
2. Our content is most frequently quoted within those sources.
3. Other selected sources support our desired outcome.

Concrete Steps To Succeed With GEO

Don’t panic – there is no rocket science involved in optimizing your content and referencing your brands when using large language models. To the contrary, a lot of the old SEO strategies will still work, and only a couple of new ones will need to be implemented into your routine. AI assistants and AI agents can also be used to automate and simplify your GEO operations, allowing you to streamline content optimization and management processes more easily.