How to track my rankings on Google, ChatGPT and Perplexity over time? Guide

In my understanding how to track my rankings on ChatGPT over time? is now essential for advanced SEOs. New tools like Rankability and Morningscore offer ChatGPT, Perplexity-specific rank tracking, measuring your brand’s appearance rate, average response position, and competitor share of voice across a library of prompts. This adds a crucial new layer to the standard keyword rankings tracked in Google. Integrating this metric directly into your regular reporting gives a full view across both search and generative answer engines.​

Pro Tip: Monitor your Visibility Rate (“% of tracked prompts where you're cited”), Share of Voice, and response context (recommendation, comparison, neutral), as these are now brand-defining KPIs for AI search.

In this blog, I’ll break down how AI is reshaping SEO, the strategies you can implement now, and the trends you need to prepare for to stay ahead in 2025.

How AI Is Changing SEO (With Real-World Impact)

SEO has always been about connecting the right content to the right user, but with billions of pages and constantly changing algorithms, manual optimization can’t keep up.

AI SEO uses artificial intelligence to optimize websites for search engines. It automates keyword research, content optimization, and technical audits. AI tools analyze search patterns, predict ranking opportunities, and identify content gaps. Machine learning improves accuracy by clustering keywords and monitoring SERP trends in real time. 

Businesses use AI SEO to increase traffic, improve efficiency, and scale optimization processes. This approach combines automation, predictive insights, and data-driven strategies to stay ahead of evolving algorithms and achieve faster search visibility.

And the shift is happening fast. McKinsey reports that 72% of companies adopted some form of AI in at least one business area in 2024, up from just 50% in 2022.

By shifting from slow, reactive methods to AI-powered SEO, marketers can scale efforts without adding headcount and respond to ranking changes faster than ever. In short, AI transforms SEO into a proactive growth engine that helps businesses stay ahead of competitors.

Businesses leveraging AI SEO optimization techniques in 2026 see more granular tracking of rank movements across Google, Bing, and AI engines. AI-driven platforms now cluster keywords by intent, batch-analyze SERP volatility, and proactively track inclusion in ChatGPT and Perplexity responses - making it easier to adapt content strategy before competitors react. For more in-depth examples, review our latest case study on AI SEO implementation.

AI vs Traditional SEO: What’s Different?

Traditional SEO is mostly reactive. You perform keyword research, optimize pages, and wait to see if rankings improve. This approach is slow and requires constant manual effort.

AI SEO, on the other hand, is proactive and continuous. It can:

• Analyze massive datasets instantly to uncover hidden keyword opportunities and search trends
• Identify gaps in your content by comparing it to top-performing competitors in real time
• Recommend precise optimizations instead of relying on trial-and-error adjustments

Where traditional SEO relies on guesswork and delayed results, AI SEO reduces uncertainty. It gives you actionable insights before rankings shift, allowing you to adjust content or site structure quickly. This evolution makes SEO less about manual execution and more about strategic decision-making.

This has become critical as AI-driven results are replacing traditional search behavior. 

An example is how traffic to major news publishers fell from 2.3 billion in March 2024 to 1.7 billion in May 2025, largely attributed to Google AI Overviews eliminating the need to click through, according to the New York Post.

A major evolution, the ai predictive seo algorithm change detector is an emerging capability in 2026. Platforms like MarketMuse, Surfer SEO, and Blocks.ai flag sudden ranking swings, identify likely causes (from Google updates or AI core logic changes), and offer plain-language next-step recommendations. This is essential for future-proofing your rankings from unexpected algorithm shifts

Machine Learning in SEO: How It Actually Works

Machine learning powers many of the tools that make AI SEO effective. It processes large volumes of data to identify patterns and predict outcomes that would be impossible to spot manually.

In SEO, machine learning helps by:

• Understanding search intent using natural language processing (NLP)
• Clustering related keywords to build content around topics instead of isolated terms
• Detecting ranking signals from user behavior like clicks and dwell time

For example, an AI tool can review your content, recognize which topics are missing compared to competitors, and suggest semantically related keywords to include. Over time, these models improve as they learn from more data, meaning the recommendations you receive become increasingly accurate and actionable.

Gartner’s 2025 Hype Cycle confirms that Gen AI and content intelligence systems are in the “Slope of Enlightenment” stage, maturing rapidly for real-world search use cases.

The key takeaway: machine learning doesn’t just automate SEO; it enhances decision-making by surfacing insights that guide content, optimization, and strategy.

ChatGPT SEO tools offer actionable recommendations and trend detection—both keyword and intent clusters—by analyzing thousands of ranking pages and tracking what AI-powered engines pull as authoritative sources. In 2026, a new best practice is to periodically prompt ChatGPT with your brand’s key phrases then benchmark response positions and contextual mentions as part of a full SEO audit.

Key advantage: AI search optimization tools now process real-time SERP data, recommend technical/semantic fixes, and actively sync citations appearing in LLM-generated content, closing the feedback loop between recommendations and results.

Why AI SEO Is More Scalable Than Ever

Scaling SEO has always been challenging. Manually optimizing hundreds of pages, running site audits, and updating metadata can overwhelm even large teams. AI solves this by handling repetitive, high-volume tasks efficiently.

AI makes SEO scalable in three main ways:

1. Automated Site Analysis – AI can crawl and flag technical issues, internal linking opportunities, or underperforming content without human intervention.
2. Content Optimization at Scale – Tools can generate topic clusters, suggest improvements for multiple pages, and maintain semantic relevance across your site.
3. Real-Time Adaptability – When search trends shift, AI surfaces changes quickly, so you can update pages without starting from scratch.

Instead of hiring large teams to handle manual tasks, businesses can rely on AI to extend their SEO capacity. This allows human experts to focus on strategy, creative content, and building authority, tasks where human judgment still matters most.

McKinsey found that companies using generative AI in marketing functions reduced content creation time by up to 60%, freeing teams to focus on higher-order thinking and planning.

Top AI SEO Strategies You Can Apply Today

AI in SEO isn’t just theoretical; it’s a set of tools and workflows you can implement immediately to work faster, reduce manual effort, and make smarter decisions. 

In this section, I’ll share the key strategies that have the most direct impact on performance. These are approaches you can integrate into your workflow without needing to overhaul your entire SEO process.

1. AI Keyword Research: Smarter, Faster, More Accurate

Keyword research is the foundation of every SEO strategy, and AI makes it significantly more efficient. Traditional research often involves scanning multiple tools, filtering long lists manually, and guessing which keywords matter most.

AI tools simplify this by:

1. Generating topic clusters – Instead of isolated keywords, AI groups terms by search intent and semantic relevance, helping you plan entire content pillars at once.
2. Identifying long-tail opportunities – AI detects low-competition queries with high intent that manual research might miss.
3. Analyzing competitor coverage – It highlights gaps in your current keyword targeting based on what top-ranking pages are already doing.

Practical takeaway: Start by using an AI-driven research tool like Semrush AI, Frase, or Clearscope. Export a list of clustered keywords for your niche and focus your content planning on clusters rather than chasing individual terms.

2. AI Content Optimization: Scale with Relevance

Creating content that ranks is more than just about keyword density. It’s about relevance and completeness. AI helps by reviewing your existing or draft content and comparing it to what currently performs in search.

Here’s how AI adds value:

• Semantic optimization – It ensures your content covers related concepts and answers search intent thoroughly.
• Real-time content scoring – Tools provide live feedback on readability, keyword usage, and topical depth.
• Content gap detection – AI surfaces missing subtopics or FAQs that would improve comprehensiveness.

Practical takeaway: Use an AI optimizer like Surfer SEO or MarketMuse to run your draft through a content analysis or follow a more holistic AI-powered content strategy that includes structured outlines, snippet-ready formats, and semantic scoring. This helps fine-tune drafts before publishing and rank in both SERPs and AI Overviews from day one.

At Revv Growth, we did something similar for Atlan. Their blogs were already ranking in the top 10 but not capturing featured snippets and AI responses. We refined the structure, inserted snippet-ready modules like FAQs and paragraph responses, and aligned content to semantic patterns preferred by AI. 

Within four weeks, Atlan secured multiple featured snippets for high-intent keywords like “data governance committee” and “modern data stack.” Many such pages now consistently show up in Google AI Overviews, ChatGPT, and Perplexity summaries, driving measurable traffic increases and outperforming pages with higher SERP ranks. 

Read the full case study → How Atlan’s Blog Strategy Made It to Google’s AI Overview and ChatGPT

3. SEO Automation: Save Time, Reduce Manual Work

Many SEO tasks are repetitive: updating internal links, checking for broken URLs, and generating metadata for large sites. AI can automate these low-value tasks so you can focus on strategy.

Effective automation use cases include:

• Internal linking – AI can suggest and insert relevant links across hundreds of pages automatically.
• Metadata generation – It can draft meta titles and descriptions that align with keyword clusters.
• Site health monitoring – Automated crawlers can continuously scan your site for technical issues without waiting for quarterly audits.

Practical takeaway: Integrate an AI SEO assistant that can run these repetitive processes in the background. Even automating a single task like metadata creation can save hours on large websites.

4. Predictive SEO: Stay Ahead of Ranking Changes

AI doesn’t just analyze the present; it can help anticipate future search behavior. Predictive SEO uses trend analysis and algorithmic pattern recognition to give you a competitive edge.

Key applications include:

• Detecting emerging topics before competitors start publishing
• Forecasting traffic potential based on current keyword and SERP behavior
• Planning seasonal or trend-based content proactively rather than reactively

Practical takeaway: Use tools with predictive features to monitor search trends in your industry. Create content for topics with rising search interest before they peak, giving you a first-mover advantage.

As an experienced AI SEO agency, our AI SEO system is designed not just to rank on Google, but to get surfaced inside AI Overviews, where brand visibility is now quietly compounding.

Using our AIO-focused architecture, Revv Growth went from $0 to $28.3K in organic traffic value in just 6 months, powered almost entirely by AI Overview wins.

We identified keywords triggering AIO summaries, structured content for extractability, and implemented internal links + schema to feed into LLM relevance layers. The result? Content that shows up where users are actually reading. You can connect with our team to make this work for your brand too.

Simply,

AI SEO optimization techniques 2026 include:

• Batch generation of structured content for programmatic SEO
• Automated internal linking with relevance scoring
• Live anomaly detection (CTR drops, crawl errors, inclusion/exclusion from AIO/SGE)
• SERP volatility alerts triggered by AI predictive SEO algorithm change detectors​
• Integration of ChatGPT prompt-based ranking snapshots into dashboards

Brands winning in 2026 don’t just automate tasks—they create AI-ready content structures that maximize extractability and relevance for both humans and machines.

How to Get Started with AI SEO Today

AI SEO can feel overwhelming if you’re new to it, but the key is to start small, focus on one workflow at a time, and build gradually. You don’t need to overhaul your entire SEO process in one go. 

Here’s a simple three-step plan to make AI part of your workflow without hitting “analysis paralysis.”

Step 1: Choose the Right AI SEO Tools for Your Workflow

The first step is deciding which part of SEO you want to enhance with AI. AI SEO tools typically focus on one of three areas:

1. Keyword research and topic clustering – Tools like Semrush AI or Frase help you identify opportunities and build content plans faster.
2. Content optimization – Platforms like Surfer SEO or MarketMuse ensure your pages meet search intent and stay competitive.
3. Automation and technical monitoring – Tools that handle repetitive tasks like metadata creation, internal linking, and audit alerts.

Practical tip: Don’t sign up for multiple tools at once. Pick one tool aligned with your immediate SEO goal, like improving content relevance or streamlining audits, and test it for a month. This approach keeps adoption manageable and measurable.

If you're building this in-house, it can take months to refine. But working with an experienced AI marketing agency that already has the SEO and AI content strategies, workflow, tools, and editorial systems in place can save you serious ramp-up time.

Step 2: Identify Quick-Win Use Cases

Once you have your first tool, focus on one or two quick wins to see real results fast. Quick wins are tasks that are:

• Time-consuming manually but easy to automate with AI
• Directly linked to performance improvements like better rankings or click-throughs

Examples of quick wins include:

• Generating metadata for multiple pages
• Clustering your existing keywords into topic groups
• Creating content briefs for upcoming articles

Practical tip: Start with the one task that consumes the most hours in your current workflow. This not only saves time immediately but also builds confidence in the AI process.

Step 3: Monitor, Measure, Refine, and Improve

AI is not a set-and-forget solution. To get long-term results, you need to track performance and fine-tune your process.

Here’s how to do it effectively:

1. Monitor performance regularly – Track organic traffic, impressions, and keyword positions for the pages optimized with AI.
2. Review AI recommendations critically – Use human judgment to ensure suggestions align with your brand voice and strategy.
3. Iterate based on results – Double down on tasks that bring visible improvements and refine areas that show little impact.

Practical tip: Treat AI as a decision-support system, not a replacement. The more feedback and adjustments you make, the better your results over time.

At Revv Growth, we run a full-stack AI SEO engine built around intent-driven research, SERP + AIO analysis, prompt-generated drafts, Clearscope/Frase scoring, schema markup, internal linking, and human editorial polish. It’s the same workflow we used to ship over 40 long-form blogs in just three months for Everstage, with multiple pieces now showing up on Google AI Overview, ChatGPT and Perplexity results.

Simply,

Want ChatGPT SEO tools actionable recommendations AI search trends 202?

• Use specialized trackers to monitor your content’s appearance and average position in ChatGPT and Perplexity prompts.
• Combine these reports with Google/Search Console logs for a unified view.​
• Adopt new AI search optimization tools (Rankability, Morningscore) for prompt-based ranking analytics.
• Tap into AI predictive SEO algorithm change detector dashboards to be alerted to ranking/visibility threats before they materialize.

What’s Next: AI SEO Trends to Watch in 2025

AI in SEO is moving beyond simple automation and optimization. It’s shaping how search engines display results, interpret intent, and reward content. If you want to future-proof your strategy, keep an eye on these emerging trends that are already changing how users discover information online.

1. Google SGE, AI Overviews & Generative Search

Google’s Search Generative Experience (SGE) and AI-powered overviews are changing how users interact with search results. Instead of clicking through multiple pages, users can now see AI-generated summaries directly in the SERP.

This shift means:

• Top positions matter even more – Being in the sources Google pulls for its AI overviews is crucial.
• Content depth and clarity are essential – Google prioritizes pages that provide complete, high-quality answers to user queries.
• Structured content has an advantage – Clear headings, concise answers, and semantically relevant content increase the chance of being referenced.

Practical takeaway: Focus on comprehensive, well-structured content that answers queries fully. Treat every page as if it might be used for an AI summary.

2. AI and Search Intent Forecasting

Search intent is no longer static. AI models are improving at predicting what users will search for next based on behavior trends, seasonal shifts, and emerging topics.

For SEOs, this creates opportunities to:

• Identify upcoming content gaps before competitors
• Plan content calendars proactively around rising queries
• Stay resilient against SERP volatility by publishing early on trending topics

Practical takeaway: Use AI tools that highlight emerging keyword clusters and intent shifts. Prioritize content that aligns with future demand, not just current traffic patterns.

Simply,

The AI SEO optimization techniques 2025 category now includes entity-first structuring, FAQ schema specifically tuned for LLMs, and continuous prompt monitoring to “train” ChatGPT to reference your brand. Winning sites dynamically analyze which prompts, topics, and competitor sites trend inside AI Overviews each month and pivot content accordingly.

Conclusion: AI Won’t Replace SEOs, But…

AI is transforming SEO from a manual, reactive process into a smarter, scalable, and predictive discipline. But it is not here to replace human SEOs. It is here to enhance what we do best. By letting AI handle repetitive tasks like keyword clustering, content optimization, and automation, we can focus on strategy, creativity, and building authority.

The key is to start small, stay consistent, and keep learning as AI evolves. Those who embrace these tools early will adapt faster and maintain a competitive edge in the changing search landscape.

If you're serious about ranking in Google and showing up in AI Overviews, Revv Growth is already doing it for both our clients and ourselves. We’ve helped scale traffic value by over $28,000, earned featured snippets, and built a repeatable AI SEO engine that gets results across Google, ChatGPT, and Perplexity.

Want the same for your brand? Book a free strategy call and let’s build your AI SEO roadmap together.

FAQs about AI SEO