As AI chatbots and AI Overviews (AIOs) continue to reshape the SEO landscape, we’ve been paying close attention to how these changes are impacting search visibility and site performance at Schema App.
Recently, Search Engine Journal published a piece titled “The State of AI Chatbots and SEO”, highlighting that:
While AI chatbot traffic currently represents a tiny percentage of overall traffic, the data shows early evidence for the value of citations and mentions. AI chatbot adoption is skyrocketing, referral traffic to websites is growing, and traffic quality is high.”
This aligns with what we’re observing on our own site. While organic Google traffic has been on a gradual decline compared to last year, we’ve seen a steady increase in referral traffic from ChatGPT and Perplexity—along with higher average engagement times from these sources compared to organic and direct. In other words, the quantity may be small, but the quality of these visits is strong.
That said, Google currently still owns roughly 90% of total search traffic. The shift toward AI-assisted search isn’t happening overnight. For us, this affirms a dual focus: continuing to optimize for traditional organic SEO while actively testing and learning how to adapt our strategy for these emerging AI experiences.
Let’s break down what we’re seeing.
How Are We Showing Up in AI Overviews (AIOs)?
Schema App’s AI Overview visibility from Dec 19 – March 18, 2025.
While attribution and reporting are still limited, we’re seeing some interesting trends in content performance for what’s currently ranking for an AIO. From December 2024 through mid-March 2025, we’ve tracked an increase in the number of keywords where our content appears in AI Overviews. For example, in January, we were showing up for a couple dozen keywords. By February, that number had more than tripled.
Although SEMrush’s AIO reporting is limited to actively tracked keywords (and likely underreports total appearances as a result), it helps us focus on queries that truly matter to our audience. Many of these queries are question-based, particularly “how to” searches.
Is Zero-Click Search Impacting Our Organic Performance?
Interestingly, this timeframe also coincided with a dip in click performance for some of our “how to” articles. When we examined Google Search Console data, several of our top pages with declining clicks were also those ranking in AIOs.
This supports the ongoing conversation around “zero-click search”—where users get their answer directly in the AI-generated overview and never click through. We’ve seen a mixed bag when it comes to impressions: some AIO-ranking pages are up, and others are down. But across the board, year-over-year trends show a drop in clicks and a significant rise in impressions, along with improvements in average position.
Are AI Chatbots Driving Quality Referral Traffic?
Beyond AIOs, we’ve also started monitoring referral traffic from AI tools like ChatGPT and Perplexity. Although it is still a small portion of our total traffic, we’re seeing consistent month-over-month growth—along with stronger performance metrics, such as longer average session durations compared to the site average.
This is a clear signal that these channels are bringing in highly engaged, qualified traffic.
We’re also earning more relevant featured snippets and gaining presence in more AIOs each month. In some cases, the same piece of content is achieving both—a sign that we’re moving in the right direction.
How Are We Optimizing for AIOs and AI Chatbots?
Restructuring Content
One of the most impactful shifts we’ve made is in how we structure content—especially for question-based queries.
We now prioritize answering the user’s question clearly and concisely within the first few sentences of a post. That means trimming the fluff, avoiding overly “catchy” headlines, and leading with a direct, helpful response.
We also treat each subheading of an article as a new opportunity to answer alternative queries that could be related to the main topic of the article. This gives us more opportunities to show up for an AIO throughout the article, even if the H1/title does not perfectly answer a query.
We’ve seen this approach pay off. The content we’ve re-optimized using this strategy has started appearing in featured snippets and AIOs.
As you can see in this example, even though the main title “What are Entities in SEO?” doesn’t exactly answer the question, the AIO ended up pulling the highlighted content it deemed relevant to the query from a different question-based subheading that did.
Implementing Schema Markup
Another key area of focus is how we implement Schema Markup to help AI systems understand our content. On top of implementing robust Schema Markup across our website, we also performed external entity linking within our markup.
By linking the entities in our articles to corresponding entities in authoritative sources like Wikipedia and Google’s Knowledge Graph, we were able to clarify the meaning of terms on our pages—especially branded terms or industry-specific language that could be misinterpreted.
Learn more about how to disambiguate the entities within your content using entity linking.
This process of disambiguation supports both search engines and AI chatbots by making content more machine-readable and context-aware. As a result, our content is more likely to surface for relevant AIO responses and generate accurate, useful outputs from AI systems.
What’s Next: Creating Citable, Data-Driven Content
In Search Engine Journal’s article, Kevin Indig notes:
The biggest lever seems to be citable content on and off of Google: Industry reports with exclusive research and data, original surveys and case studies, and thought leadership content from recognized experts.”
This reflects where we’re headed.
We’re encouraging collaboration across Marketing, Customer Success, and Product teams to surface internal testing results, customer outcomes, and new data. These “mini case studies” not only validate our value but also help us stand out as trusted voices in a rapidly changing SEO environment to provide support and guidance to the industry.
How Are You Responding to AI’s Impact on Search?
As the search landscape continues to evolve with AI integrations, Schema App is leaning into what we do best—testing, measuring, and adapting with evidence-based strategies. While Google still dominates, we’re watching and optimizing for the rising tide of AI-powered search experiences.
Have you noticed similar trends on your site? What are you doing to optimize for AI Search? Let us know—this is just the beginning of a new era in search.
Andrea Badder is the Digital Marketing Specialist at Schema App. She specializes in SEO and develops educational resources to help marketing teams understand the value of Schema Markup and Content Knowledge Graphs for semantic search, content strategy, and AI-driven initiatives. Prior to joining Schema App, Andrea worked as a brand strategist and copywriter at a marketing agency. She is also a graduate from the University of Guelph.