From traditional to AI-Driven: How SEO is changing

Search is undergoing its biggest shift in decades. Historically, SEO focused on helping websites earn higher rankings in traditional search results. Now, with Google’s AI Overviews and generative tools like ChatGPT and Perplexity, users are engaging with summarized, conversational answers that often bypass websites entirely.

This shift introduces a new layer of optimization focused on visibility within AI-driven search experiences. While SEO remains important, AI SEO determines whether your content is understood, trusted and cited by AI systems.

In this blog, we’ll explore how traditional SEO and AI SEO work together, what sets them apart and how you can adapt to stay visible in an AI-driven search landscape.

The fundamentals of AI SEO

Defining AI SEO and why it matters

AI SEO is the practice of optimizing content to be discovered, understood and cited by AI-powered search tools like ChatGPT, Perplexity and Google’s AI Overviews. Marketers are still defining the language around this topic, you might also hear people call it Generative Engine Optimization (GEO) or Answer Engine Optimization (AEO), among other terms. Though the terminology varies, they all aim to ensure your content is recognized and cited within AI-generated answers. For consistency, we’ll use “AI SEO” as an umbrella term to cover them all.

Both traditional SEO and AI SEO are essential to a well-rounded digital strategy. Traditional SEO helps your site show up high in search results, while AI SEO aims to get your content included in the AI-generated answers people now see. Together, they help your website show up wherever searches are being made.

We’ll break this down in more detail as we go, but here’s a high-level look at how traditional SEO and AI SEO stack up side by side.

Understanding how AI SEO works

To put AI SEO into practice, it helps to know how generative search tools work behind the scenes. They still crawl websites like Google does to discover and understand content—but what they do with that information is different. Instead of simply ranking pages based on keywords and backlinks, AI systems read, interpret, and blend information from across the web to form a single, conversational answer.

Here’s a high-level look at how AI systems process and interpret content:

• Interprets meaning, not just keywords: AI models use natural language understanding to grasp your content’s context, intent and topical relationships. They identify the main entities like people, organizations and ideas to map how those entities connect, helping the model understand the “story” behind your content rather than just the words.

• Evaluates authority and trust signals: Generative AI systems look for cues that your content is credible and consistent with trusted information online. Clear authorship, cited sources, structured data and alignment with recognized expertise all help strengthen E-E-A-T signals (Experience, Expertise, Authority and Trustworthiness).

• Incorporates first-party data and authentic reviews: AI systems prioritize content backed by original data sources and genuine customer feedback. First-party information, like proprietary surveys and verified reviews—signals authenticity and authority, making your content more likely to be cited by AI platforms.

• Extracts citable, context-rich snippets: Rather than ranking an entire page, AI tools pull concise, well-structured fragments — sentences, paragraphs or bullet points — that directly answer user questions. Content that’s clearly formatted, factually specific and contextually rich is far more likely to be referenced in an AI-generated summary.

In short, AI SEO is about making your expertise readable, reliable and reusable by machines. When your content is structured for meaning, backed by authority and easy to extract, it stands a far better chance of being included in the AI-driven answers shaping how people discover information today.

Key optimization takeaways for the AI era

With that foundation in mind, let’s talk about optimization. Optimizing for AI search doesn’t replace traditional SEO; it builds on it. The same fundamentals that help your content rank still matter, but AI introduces new factors that determine how your content is interpreted and cited.

Optimization factors for AI discovery and citation

Much of what matters for AI SEO will look familiar if you’ve been practicing traditional SEO. AI SEO puts greater weight on clarity, context and credibility. Some of the optimization areas that are especially important in the context of AI search include:

Prioritizing clarity and structure

AI models prefer content that’s easy to parse. Use clear headings, short paragraphs and logical flow. Lead with the key takeaway, then follow with supporting details — similar to how featured snippets are written. This makes your content easier for models to segment and summarize.

Writing with context, not just keywords

Go beyond keywords by using context-rich language. Reference people, organizations and products by name, and describe how they relate. This helps AI understand the relationships between entities, not just the terms themselves.

Building authority through E-E-A-T

E-E-A-T (Experience, Expertise, Authority and Trustworthiness) has always mattered for SEO — but it’s even more critical for AI SEO. Generative models rely on clear authorship, credible sourcing and consistent online signals to determine which content to trust and cite. Keep author bios, credentials and publication dates up-to-date, and make sure your brand’s expertise is reflected consistently across your site, LinkedIn and Google Business Profile.

Adding structure behind the scenes

Schema markup, a type of code that helps search engines and AI understand what your website content is about, adds essential context. Use schemas for FAQs, How-To content, organizations, people, products and reviews to help AI recognize your web content’s purpose and hierarchy. Adding this type of structure can involve back-end website work, so collaborating with a web developer can help with the technical side.

Monitoring how AI represents your brand

Test your priority topics in ChatGPT, Perplexity and Google’s AI Overviews. See how (or if) your brand is mentioned, and refine your content’s formatting or phrasing when summaries are inaccurate or incomplete. Treat these insights like a new layer of performance analytics. As AI SEO continues to evolve, the way we measure success is changing, too.

Traditional SEO factors still matter

Even as AI introduces new optimization opportunities, the fundamentals of traditional SEO are still important. Paying attention to core SEO factors makes your content more likely to appear both in search results and in AI-generated answers.

• Technical SEO: Fast load times, mobile performance and crawlable architecture ensure your content can be accessed and understood.

• Content depth: Comprehensive, high-quality articles that explore a topic in full provide the context AI systems need to connect ideas accurately and understand subject relationships.

• Backlinks and mentions: Backlinks — links from other credible sites referencing your content — continue to be one of the strongest indicators of authority, reinforcing trust for both traditional search engines and AI systems.

• User engagement: Longer on-page time and interaction reinforce your content’s real-world relevance.

• Topical consistency: A clear internal linking structure and defined content hierarchy strengthen your perceived expertise.

Where to start with AI SEO

AI search is changing fast, and there’s a lot of new information to take in. If you’re looking for a place to start, begin with this priority checklist for getting your website AI-ready.