AI and SEO Readiness: How to Rank in the Age of AI Search

Oh, congratulations! Just when you thought you had this whole SEO thing figured out, along comes AI to flip the table on your carefully arranged digital marketing strategy. 

While AI search is boldly shoving traditional results 1200+ pixels down the page with its fancy summary boxes appearing in over 91% of queries, savvy business owners (like you) can absolutely crack the code and become AI search darlings. 

Think of this not as the SEO apocalypse, but as your chance to leap ahead of competitors who are still optimizing for yesterday’s search engine!

In order to help you rank higher we’ve created a step-by-step audit checklist you can follow to ensure your website is ready to rank within AI search results.

Want us to do the hard work for you? Click here to have Enleaf create a free AI readiness audit for your site.

TL;DR – Elevator Pitch Summary

• 🔍 If your website isn’t optimized for AI-driven results, it could get buried under AI-generated answers—meaning less visibility, less traffic, and fewer customers!
• 🤖 Make sure AI can actually find and understand your site: Ensure your site is crawlable and AI-friendly
• 🧠 Use structured data and smart content tweaks so AI knows exactly what you’re about.
• ⚡ Improve readability, speed your site up, and link your content together logically.
• 🚴 Stay ahead of AI search trends (like you’re doing right now😉) so you’re not playing catch-up 

AI Tools Are Trending, but Google’s Search Volume is Still Booming

Contrary to widespread assumptions that AI tools like ChatGPT have significantly eroded Google’s search market share, recent data from SparkToro and Datos (a Semrush company) reveals the opposite is true. In fact, Google Search experienced a remarkable growth of over 20% in 2024, driven in part by the successful integration of AI-generated summaries directly into its search results. While it’s true that AI summaries have notably reduced click-through rates to organic and paid listings, overall search volume on Google remains robust.

When directly compared to AI tools, the scale difference is clear: Google averaged over 14 billion searches per day in 2024, approximately 373 times more than ChatGPT’s estimated 37.5 million daily search-like interactions. Even when factoring in all prominent AI search competitors (such as Perplexity, Claude, Copilot, and Gemini), AI-driven search activity accounted for less than 2% of total search volume.

These findings highlight an important reality for businesses and SEO professionals—despite the hype, traditional Google search continues to dominate user attention. While experimenting with AI visibility can provide value for PR and innovation, marketers should avoid shifting significant resources based purely on media buzz, instead focusing efforts where substantial user activity occurs.

AI readiness is actually just SEO, in a new light.

Many of the same considerations that businesses apply to technical SEO and content optimization are also critical to making a website “AI-ready.” In fact, optimizing your website for search engines and LLMs like ChatGPT, Google Gemini, and Grok often overlap because these models pull information from well-optimized, authoritative, and easily accessible websites.

To maximize a website’s visibility and chances of being featured in Large Language Models (LLMs) like ChatGPT, Google Gemini, and Grok, it’s essential to prioritize certain aspects like technical SEO, content quality and relevance, and EEAT.

Now on to the AI SEO readiness guide…

Step 1: Crawl & Indexability Analysis

Crawl & Indexability Analysis is essential for understanding how search engine bots navigate and index a website. Crawlability refers to the ability of bots to access and traverse the site, while indexability determines which pages are likely to appear in search engine results. Screaming Frog, a widely used SEO tool, simulates this process by crawling the site and providing detailed data for analysis. Given its industry-leading status, trusted by thousands of SEOs and agencies worldwide, it’s a reliable choice for technical SEO audits, available on Windows, Mac, and Linux, with a free download option or paid licence for advanced features.

Step-by-Step Process

The following table outlines the detailed steps, including configuration options and analysis methods, based on official documentation and tutorials:

Step	Description	Details and Tools
Install and Launch	Download and install Screaming Frog SEO Spider, then launch the application.	Free download from the Screaming Frog website, paid version for advanced features.
Set Up the Crawl	Enter the website URL, select “Spider” mode, and configure settings.	Configure depth, thread count, user agent, and robots.txt settings under Configuration (User Guide).
Run the Crawl	Click “Start” to begin, monitor progress, and ensure completion.	Can pause, resume, or save crawl as needed, real-time data populates in tabs.
Analyze Crawlability	Check for pages not crawled, focusing on response codes in the “Internal” tab.	Filter by “Response Code” for non-200 statuses (e.g., 404, 500) to identify issues.
Analyze Indexability	Check status codes, meta directives, and robots.txt blocking across tabs.	– Status: “Internal” tab, 200 OK for indexable. – Directives: “Directives” tab for noindex tags. – Robots.txt: “Issues” tab for “Internal URL Blocked by Robots.txt” warnings.
Crawl Depth Analysis	Sort by “Depth” in “Internal” tab to assess page distance from homepage.	Identify high-depth important pages for potential restructuring.
Export and Further Analysis	Export data to CSV for detailed filtering and pattern recognition.	Useful for large sites, consider paid version to remove 500 URL limit.

Detailed Configuration and Tutorials

Configuration is critical for accurate analysis. The Spider Advanced Tab offers options like “Ignore non-indexable URLs for Issues” and “Respect noindex” for indexability analysis, while “Respect canonical” helps with canonicalization (Configuration). Tutorials provide specific guidance, such as “How To Crawl JavaScript Websites” for handling dynamic content, and “How To Audit Canonicals” for checking canonical tags, both essential for indexability (JavaScript Crawl, Canonical Audit).

For robots.txt impact, the “Robots.txt Testing In The SEO Spider” tutorial explains how to assess its effect on crawlability, crucial for ensuring no important pages are blocked (Robots.txt Tester). The “How To Debug Missing Pages In A Crawl” tutorial helps identify non-indexable pages, enhancing the analysis (Debug Missing Pages).

Advanced Features and Limitations

Advanced features, available in the paid version, include integration with Google Analytics, Search Console, and PageSpeed Insights APIs for performance data, enhancing indexability analysis. The free version, limited to 500 URLs, is suitable for small to medium sites, but for larger sites, the paid version is recommended to avoid truncation. Activation requires a licence key, with support available via email at [email protected], typically responding within 24 hours during business hours.

Practical Tips and Considerations

For a precise list of indexable pages, export the “Internal” tab data, filter for Response Code = 200, cross-reference with the “Directives” tab to exclude noindex pages, and check the “Issues” tab for robots.txt blocking. This manual process can be cumbersome, but it’s effective for detailed analysis. Regularly performing these analyses helps track changes, and using the “Visualizations” tab can provide graphical insights into site architecture, aiding in identifying structural issues (Visualizations).

External guides, such as “Crawl Depth: How To Audit Crawl Depth With Screaming Frog” from GoFish Digital, suggest filtering by HTML and exporting for spreadsheet analysis, reinforcing the export strategy (Crawl Depth Guide). Another resource, “How to Do SEO Analysis With Screaming Frog” from Dopinger, highlights using the “Directives” tab for technical issues, aligning with our approach.

Installing and Using Bing Webmaster Tools for Higher Rankings

Step-by-Step Installation and Setup

The process begins with creating or signing into a Microsoft account, essential for accessing Bing Webmaster Tools. Here’s how to proceed:

1. Sign Up for a Microsoft Account: Visit account.live.com to create an account if you don’t have one, or sign in if you do. This step is straightforward and ensures you can access Microsoft services, including Bing Webmaster Tools.
2. Access Bing Webmaster Tools: Navigate to www.bing.com/webmaster and sign in with your Microsoft account. This page, as of 2025, provides access to the dashboard and site management features.
3. Add Your Website: Click “Add a site” and enter your website’s URL. This step initiates the process of connecting your site to Bing’s indexing system.
4. Verify Your Website Ownership: Bing offers several verification methods to ensure you own the site:
   • HTML File Verification: Download a provided HTML file (e.g., “BingSiteAuth.xml”) and upload it to your website’s root directory. This method is common for those with FTP access.
   • Meta Tag Verification: Add a specific meta tag provided by Bing to your homepage’s HTML, typically in the <head> section.
   • Domain Verification: Add a TXT record to your domain’s DNS settings, suitable for those managing domain configurations. Follow the instructions for your chosen method to complete verification, a critical step for accessing full tool functionality.
5. Explore the Dashboard: Once verified, the dashboard offers an overview of your site’s performance, including indexed pages, search queries, and crawl stats. This is your starting point for monitoring and optimization.

Using Bing Webmaster Tools for Optimization

With your site set up, the following steps leverage Bing Webmaster Tools to improve rankings in SERPs and potentially AI search results:

6. Check Crawl Errors: Navigate to the “Crawl” section to identify any errors Bingbot encounters, such as 404 errors or server issues. Fixing these ensures Bing can access and index your content effectively. For example, resolving broken links can prevent pages from being excluded from search results.
7. Review Index Coverage: In the “Index” section, review which pages are indexed and which are not. Ensure all important pages, like product pages or blog posts, are indexed, and address any exclusions (e.g., due to robots.txt restrictions). This step is crucial for visibility in both standard and AI search, as indexed content is more likely to be considered for summaries.
8. Analyze Search Queries: The “Search Queries” section provides data on which keywords drive traffic to your site, including impressions, clicks, and click-through rates (CTR). This insight helps identify high-performing keywords to target and underperforming ones to optimize. For instance, if “best hiking boots” has high impressions but low CTR, consider improving the title or meta description for better engagement.
9. Optimize Your Content: Use the search query data to refine your content. Focus on targeting relevant keywords in titles, headers, and body text, ensuring they align with user intent. For example, if users search for “how to choose hiking boots,” create detailed guides with clear, actionable advice. This optimization not only boosts SERP rankings but also increases the likelihood of being featured in AI-generated responses, as these often pull from authoritative, relevant content.
10. Submit Sitemaps: Submit your sitemap (e.g., XML sitemap) through Bing Webmaster Tools to help Bingbot understand your site’s structure. This facilitates faster indexing of new or updated pages, ensuring they appear in search results promptly. For example, after publishing a new blog post, submitting the sitemap can accelerate its visibility.
11. Monitor Performance: Regularly check performance metrics like clicks, impressions, and CTR in the performance reports. Track changes over time to assess the impact of your optimizations. For instance, if impressions increase but clicks don’t, it may indicate a need for better meta descriptions or page content.
12. Use Advanced Features: Bing Webmaster Tools offers additional features to enhance optimization:
    • Backlink Analysis: Review backlinks pointing to your site, as quality backlinks can improve authority and rankings. For example, the Site Explorer function, as noted in recent guides, shows backlinks at the subfolder or page level, helping identify valuable links.
    • Mobile Usability: Ensure your site is mobile-friendly, as Bing prioritizes mobile usability for search rankings.

Structured Data: Implement structured data (e.g., schema markup) to enhance how your content appears in search results, potentially increasing visibility in AI summaries.

Step 2: Entity-Based & Semantic SEO Check

Entity-Based SEO focuses on optimizing content around specific entities—such as people, places, or things—rather than just keyword data, ensuring these entities are properly mentioned and linked. Semantic SEO, on the other hand, emphasizes the meaning behind content, aiming for search engines to understand relationships and context through structured data and clear content organization. 

Background on Screaming Frog and OpenAI Integration

Since version 20.0, released in May 2024, Screaming Frog supports direct integration with OpenAI, allowing SEOs to use ChatGPT for content analysis during crawls. This integration, detailed in resources like How the Screaming Frog SEO Tool Uses OpenAI for Optimization, enables automated recommendations for keyword usage, content structure, and readability, which are crucial for entity-based and semantic SEO.

Step-by-Step Guide for Implementation

The following steps outline how to set up and execute an Entity-Based & Semantic SEO Check with Screaming Frog, assuming the latest version (post-May 2024) for OpenAI compatibility.

1. Download and Install Screaming Frog SEO Spider:
   • Visit Screaming Frog Official Website to download the tool for Windows, macOS, or Linux. Follow the installation instructions provided.
2. Obtain an OpenAI API Key:
   • Create an account on OpenAI Platform if you don’t have one, and generate an API key from the account settings. Note that API usage incurs costs based on the number of requests, so monitor usage to manage expenses.
3. Set Up OpenAI Integration in Screaming Frog:
   • Launch Screaming Frog and navigate to Settings > OpenAI. Enter your API key in the designated field to enable AI-powered analysis. Ensure you have version 20.0 or later, as earlier versions may not support this feature, as noted in SEO Update: Screaming Frog Launches Direct OpenAI Integration.
4. Configure the Crawl Settings:
   • Enter the website URL in the “Start URLs” field within Screaming Frog.
   • Set crawl parameters such as depth and number of threads based on your site’s size. For large sites, ensure sufficient hardware (e.g., 16GB RAM, SSD) as recommended in SEO Spider General.
   • Enable JavaScript rendering by going to Configuration > Spider > Rendering and selecting “JavaScript” to capture dynamic content, essential for accurate entity and semantic analysis.
5. Develop Custom JavaScript for AI Analysis:
   • Navigate to Configuration > Custom JavaScript in Screaming Frog. Write a function to extract page content and interact with ChatGPT. For example:

function analyzePage() {
    var content = document.body.innerHTML;
    var prompt = "Analyze this web page content for entity-based and semantic SEO. Identify main entities and check if they are properly defined or linked. Also, provide feedback on the semantic structure, including header tags, meta description, and title tag.";
    var response = await openaiChat(content, prompt);
    return response;
}

• The openaiChat function is hypothetical here; refer to How to Crawl with ChatGPT for exact implementation, which likely involves sending the content to the OpenAI API and capturing the response. This step allows for tailored analysis, such as identifying entities like “New York” or checking if headers like <h1> align with semantic intent.

6. Execute the Crawl and Collect Data:
   • Click “Start” to begin the crawl. Screaming Frog will process each page, executing the custom JavaScript function to get AI-driven insights. Monitor the progress to ensure no errors, especially related to API rate limits.
7. Analyze the Results:
   • After the crawl completes, go to the “Data” tab. Look for columns or reports generated from the ChatGPT responses, which should include feedback on entity mentions (e.g., are “Apple Inc.” linked to its Wikipedia page?) and semantic structure (e.g., is the meta description coherent with the content?).
   • Use the export feature to save data in CSV format for further analysis, as described in Screaming Frog Guide For The SEO Spider.
8. Implement Improvements Based on Analysis:
   • Review the AI feedback to identify areas for enhancement. For entity-based SEO, ensure key entities are mentioned in titles, headers, and linked appropriately. For semantic SEO, optimize header hierarchy (e.g., ensure <h1> is unique per page) and refine meta descriptions to reflect content intent.
   • Consider using additional tools like Schema.org validators to complement Screaming Frog’s findings, especially for structured data, as noted in SEO Spider Tutorials.

Practical Considerations and Challenges

• Cost Management: The OpenAI API usage can incur significant costs, especially for large websites. Monitor your API calls via OpenAI Platform to avoid unexpected charges.
• Technical Expertise: Writing custom JavaScript requires some programming knowledge. For users less familiar, consider consulting Explore Screaming Frog and its AI API for tutorials or seeking professional SEO services.
• Version Compatibility: Ensure Screaming Frog is updated to version 20.0 or later, as earlier versions lack OpenAI integration, per Using the Screaming Frog SEO Spider and OpenAI Embeddings.

Comparative Analysis: Traditional vs. AI-Enhanced SEO Checks

To illustrate the benefits, consider the following table comparing traditional Screaming Frog features with AI-enhanced analysis for entity-based and semantic SEO:

Aspect	Traditional Screaming Frog	AI-Enhanced with OpenAI
Entity Identification	Manual review of content for entity mentions	Automated identification via ChatGPT, e.g., “New York” as a key entity
Semantic Structure Check	Analysis of headers, meta tags via reports	AI feedback on coherence, readability, and intent alignment
Schema.org Markup	Custom extraction for structured data, manual validation	AI can suggest missing markup based on content analysis
Scalability	Limited by manual analysis for large sites	Scales well with API, though cost increases with volume
Time Efficiency	Time-consuming for detailed semantic checks	Faster with automated AI insights during crawl

This table highlights how AI integration enhances scalability and depth, though at an additional cost, aligning with findings from How to Use AI in Screaming Frog.

Step 3: Structured Data & Schema Optimization

Structured data and schema optimization enhances how search engines understand and display website content, potentially improving visibility in search results. Using Screaming Frog you can audit and optimize this data efficiently. Below, we outline a clear process for beginners, including unexpected details like exporting error reports for deeper analysis.

Configuration for Structured Data

Configuration is critical for effective structured data optimization. Navigate to “Config” > “Spider” > “Advanced” to enable specific options:

• JSON-LD: Preferred by Google for its ease of implementation and compatibility.
• Microdata: Embedded within HTML for older schema implementations.
• RDFa: Another format for embedding structured data, less common but supported.
• Schema.org Validation: Ensures data adheres to Schema.org standards, a collaborative vocabulary by Google, Microsoft, Yahoo, and Yandex.
• Google Rich Result Feature Validation: Checks for compatibility with Google’s rich result features, enhancing search appearance.

These settings allow Screaming Frog to crawl and extract structured data in real-time, validating against both Schema.org and Google specifications.

Crawling and Analysis

Once configured, start the crawl, which may take time depending on the website’s size. Upon completion, the “Structured Data” tab provides a detailed breakdown:

• Pages with structured data present.
• Pages missing structured data, indicating potential optimization opportunities.
• Pages with validation errors or warnings, highlighting issues like incorrect schema types, missing properties, or syntax errors.

An unexpected feature is the ability to export validation errors and warnings via “Reports” > “Structured Data” > “Validation Errors & Warnings,” enabling bulk analysis and reporting, as detailed in the same Seer Interactive guide. This export can be particularly useful for large websites, facilitating collaboration with developers or SEO teams.

Addressing Identified Issues

Fixing structured data issues requires referring to external resources. The Schema.org website (Schema.org) offers detailed documentation on schema types and properties, while Google’s structured data guidelines provide best practices, especially for rich results. Common issues include:

• Incorrect schema types, such as using “Product” instead of “LocalBusiness” for a store.
• Missing required properties, like “price” for a product schema.
• Syntax errors in JSON-LD, such as malformed JSON.

Given Google’s preference, implementing or converting to JSON-LD is recommended for better compatibility and ease of maintenance. For example, a page with an error in microdata rating implementation might be rewritten in JSON-LD for clarity and validation success.

Verification and Maintenance

After updates, re-crawl the website with the same configuration to verify fixes, checking the “Structured Data” tab for resolved errors. Regular crawls are essential to catch new issues from website updates or added pages, ensuring ongoing optimization. Staying informed about updates to Schema.org and Google’s guidelines is crucial, as search engine requirements evolve, potentially affecting rich result eligibility.

Additional Considerations

While the guide focuses on Screaming Frog, integrating with Google Search Console can enhance analysis. This tool can highlight errors in the “Enhancements” section, complementing Screaming Frog’s findings. For advanced users, custom extractions in Screaming Frog allow extracting specific structured data elements, useful for targeted optimization.

Table: Structured Data Configuration Options in Screaming Frog

Option	Description	Relevance to Optimization
JSON-LD	Preferred format for structured data, easy to implement	High, Google’s recommended format
Microdata	Embedded in HTML, older but supported	Medium, for legacy implementations
RDFa	Another embedding format, less common	Low, niche use cases
Schema.org Validation	Validates against Schema.org standards	High, ensures compliance
Google Rich Result Feature Validation	Checks for rich result compatibility	High, enhances search visibility

This table, derived from various guides, underscores the importance of enabling all options for comprehensive analysis, ensuring no optimization opportunity is missed.

Step 4: AI Content Optimization & Readability Analysis

Step-by-Step Guide for AI Content Optimization and Readability Analysis

1. Understand the Target Audience and Search Intent
   • Begin by identifying your target audience and their search behaviors. Research suggests understanding user intent is critical, as AI search engines aim to provide direct, contextually relevant answers. For instance, if targeting health queries, focus on authoritative, clear responses to common questions.
   • Use tools like Google Keyword Planner (Google Ads) or SEMrush (SEMrush) to analyze search trends, focusing on long-tail keywords that align with user intent. This ensures content addresses specific queries, enhancing relevance for AI processing.
2. Conduct Keyword Research
   • Keyword research remains essential, but for AI search, the emphasis shifts to semantic keywords and natural language phrases. Tools like SEMrush (SEMrush) can help identify terms that trigger AI responses, such as question-based queries (e.g., “how to optimize for AI search”).
   • Integrate keywords naturally to avoid over-optimization, as AI models can detect and penalize keyword stuffing, prioritizing content quality over density.
3. Create High-Quality, Informative Content
   • Develop content that directly answers user queries, structured with clear headings, subheadings, and bullet points for easy navigation. Research from Search Engine Land (Search Engine Land) emphasizes providing concise answers, especially for featured snippets, which can boost click-through rates (CTR) by 42%.
   • Use a questions and answers format to align with AI’s tendency to extract direct responses. Include summaries and key takeaways, and cite sources to enhance credibility, leveraging E-E-A-T principles (Experience, Expertise, Authoritativeness, Trustworthiness).
   • For example, for a health blog, structure content with FAQs using FAQPage schema, ensuring AI can parse and present answers in overviews.
4. Optimize for Readability
   • Readability analysis assesses how easily content is understood, using metrics like Flesch-Kincaid Grade Level and Gunning Fog Index (Readability Formulas). Tools like Hemingway Editor (Hemingway Editor) provide instant scores, highlighting complex sentences.
   • Aim for a readability level matching your audience, typically an 8th-grade level for general audiences in the U.S. Improve readability by using simple language, short sentences (under 20 words), and avoiding jargon. For instance, replace “utilize” with “use” to reduce complexity.
   • This step is crucial as AI algorithms may correlate readability with user engagement, influencing rankings. Research suggests readable content reduces bounce rates, enhancing visibility in AI search results.
5. Use Structured Data and Schema Markup
   • Implement structured data using schema.org markup to help AI search engines understand content context. For example, use Article, FAQPage, or HowTo schemas to highlight key information (structured data SEO).
   • This enhances the likelihood of appearing in AI Overviews, which often include around 5 links, offering visibility opportunities. Ensure proper HTML tags (H1-H6) and metadata, improving AI parsing efficiency.
6. Ensure Technical Optimization
   • Technical SEO is vital, with fast loading times (under 1 second preferred) and mobile optimization ensuring accessibility. Use tools like SEMrush for audits, compressing images, enabling caching, and using CDNs to enhance speed (SEMrush).
   • Allow AI crawlers in robots.txt, distinguishing between training (e.g., GPTBot) and search crawlers (e.g., OAI-SearchBot). Block training crawlers if protecting content, but ensure search crawlers can access, as they represent 28% of Googlebot’s volume (Search Engine Land).
7. Create an llms.txt File (Advanced)
   • An unexpected detail is the llms.txt file, a proposed standard to aid LLMs in processing website content (llms.txt Proposal). This markdown file provides a summary and links to detailed information, bypassing complex HTML for AI efficiency.
   • For example, developer sites can use llms.txt to offer API documentation, improving AI agent interactions. This is particularly relevant for sites with large content, addressing context window limitations in LLMs.
8. Build Authority and Trust
   • Focus on E-E-A-T principles, crucial for AI search, as they signal content reliability. Provide author credentials, consistent publishing schedules, and high-quality backlinks to establish authority.
   • Social proof, like user reviews or expert quotes, enhances trustworthiness, aligning with AI’s preference for authoritative sources in overviews.
9. Test and Iterate
   • Monitor performance using Google Search Console (Google Search Console) and analytics tools like SEMrush (SEMrush), tracking snippet appearances, user engagement (bounce rate, time on page), and voice search traffic.
   • Iterate based on data, conducting regular content audits and A/B testing to refine strategies. For instance, test different heading structures to optimize for AI snippet inclusion.

Step 7: AI Predictive SEO & Search Trend Analysis

Step-by-Step Guide to AI Predictive SEO and Search Trend Analysis

1. Selecting AI-Powered SEO Trend Analysis Tools

The first step is choosing the right tool, as several platforms leverage AI for SEO trend prediction. Research suggests tools like SE Ranking, which mentions “AI Powered algorithms” for forecasting, and SEOMonitor, noted for “smarter forecasting” and AI innovations, are effective. Other potential tools, such as SEMrush, may also use AI, though explicit mentions for trend prediction vary.

When selecting, consider:

• Accuracy of predictions, based on historical data analysis.
• Ease of use, with intuitive interfaces for non-technical users.
• Integration capabilities with existing SEO analytics, such as Google Search Console and Google Analytics.
• Cost-effectiveness, ensuring alignment with budget constraints.

For example, SE Ranking offers an Organic Traffic Forecast template, while SEOMonitor provides advanced search rankings tracking, both crucial for predicting trends.

2. Setting Up the Tool and Inputting Data

Once a tool is chosen, set it up by subscribing or installing it, then input your website’s historical data. This includes traffic metrics, keyword rankings, and click-through rates (CTR), sourced from platforms like Google Search Console. Ensure data is clean and up-to-date to avoid skewed predictions. For instance, SE Ranking’s template allows inputting data from up to 16 months prior, using linear regression for projections.

Connect the tool to your analytics platforms to streamline data flow, ensuring real-time updates. This step is vital for accurate trend analysis, as incomplete data can lead to unreliable forecasts, as noted in discussions on Propeller’s insights on search engine optimization forecasting.

3. Analyzing Historical Data to Identify Trends

Analyze the historical data using the tool’s reporting features to visualize patterns. Look for:

• Seasonal variations, such as increased searches during holidays.
• Long-term growth trends, indicating sustained interest in topics.
• Anomalies, potentially linked to algorithm updates or external events.

This analysis helps understand past performance, such as how keyword rankings correlated with traffic spikes, informing future strategies. For example, Hawksem’s blog on SEO forecasting highlights using first-party data for trend identification, complementing AI tools.

4. Predicting Future Search Trends with AI

Leverage the tool’s AI capabilities to forecast future trends, focusing on emerging keywords and topics. AI models, such as those in SEOMonitor, use machine learning to predict shifts based on historical patterns, factoring in seasonality and market changes. Supplement this with external tools like Google Trends, which provides broader search volume insights, enhancing predictions.

Identify keywords with rising interest, such as those showing increased search volume over 12-24 months. This step ensures alignment with user intent, crucial for both search engine rankings and AI search results.

5. Optimizing SEO Strategy Based on Predictions

Based on predictions, optimize your search engine optimization efforts by:

• Prioritizing keywords with high growth potential, adjusting content to target these terms.
• Planning content creation around emerging trends, ensuring relevance to predicted user queries.
• Modifying website structure, such as improving page speed and mobile-friendliness, to align with predicted user behavior.

For instance, if AI predicts a rise in voice search queries, focus on long-tail, conversational keywords. This step ensures competitiveness in traditional SERPs and prepares content for AI models.

6. Monitoring and Adapting to Changes

Continuously monitor SEO performance against predictions, using the tool’s dashboards to track metrics like traffic and rankings. Adjust strategies as new data emerges, such as responding to unexpected trend shifts. Stay updated with SEO news, such as algorithm updates from Google’s blog on AI in Search, to anticipate changes affecting rankings.

This iterative process ensures adaptability, crucial in the fast-evolving 2025 search landscape.

7. Creating High-Quality, Comprehensive Content for AI and Traditional Search

Create content that is comprehensive, accurate, and well-structured, optimized for both traditional SEO and AI models. As of 2025, AI search results, such as Google’s AI Overviews, prioritize content that is:

• Thorough, covering all aspects of a topic, as seen in MIT Technology Review’s insights on generative AI search.
• Accurate and up-to-date, free from bias, to be cited in AI-generated answers.
• Well-structured, using clear headings, bullet points, and natural language for easy parsing by AI.

Include relevant data, statistics, and citations, such as linking to authoritative sources, to enhance credibility. For example, use internal links to related content and external links to reputable sites, ensuring AI models can reference your content in responses.

8. Building Authority and Trust

Build authority by consistently producing high-quality content that provides value (even if it’s ai generated content), earning trust from both users and search engine algorithms. Earn backlinks from reputable websites, such as industry leaders, to increase domain authority, a key factor for AI models in determining trustworthiness. Engage with your audience through comments and social media to foster community trust.

This step ensures your content is considered a reliable source, enhancing visibility in AI search results, such as those from ChatGPT Search, ranked as the top AI search engine for 2025 in Search Engine Journal’s list.

9. Staying Updated with AI Advancements in Search

Keep informed about AI advancements in search, such as Google’s expansion of AI Overviews to over a billion users by 2025, as reported in Google’s blog on generative AI in search. Participate in SEO communities, such as forums or webinars, to share knowledge and learn from peers. Experiment with new AI-powered tools to adapt strategies.

This ongoing education ensures alignment with the latest search trends, maintaining competitiveness in both search engine results pages and AI-driven results.

🚀 Final Verdict: AI Readiness is Your Competitive Edge

❌ Traditional SEO alone won’t cut it anymore. AI search is changing the game, and this audit exposes exactly what matters now.

✅ The companies winning in AI search results aren’t just optimizing—they’re implementing a structured approach: technical crawlability, entity relationships, and schema optimization.

💡 The solution? A systematic AI readiness plan. Each step builds on the last, creating a strategy that prepares your business for AI-driven search.

🔄 AI readiness isn’t a one-time fix—it’s an ongoing process. Stay ahead by regularly measuring your AI Readiness Score and adapting before your competitors do.

🏆 The businesses that adapt fastest will dominate AI search results. Will yours be one of them?

Click here to have Enleaf create a free AI readiness audit for your site to ensure your business is staying in front of potential customers.