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AI Search SEO: How to Get Indexed and Drive Traffic
AI is changing how we search online, with platforms like Google’s AI-powered search, ChatGPT, and Perplexity taking the lead. For SEOs, this shift isn’t something to ignore—it’s a huge opportunity to adapt and grow.
The impact is already clear. AI-powered search tools are growing fast, and we’ve seen it firsthand with a big jump in traffic from ChatGPT to our website at the end of 2024.
But getting noticed in this new search world isn’t as simple as sticking to old SEO strategies. AI search works differently, as it favors conversational queries and smarter, more dynamic results.
So, how do you get your site indexed and drive traffic in this AI-driven era? In this article, I’ll explain the types of AI search platforms, share tips for optimizing your content for both search engines and large language models (LLMs), and give you the tools to succeed. Let’s dive in.
How AI search differs from conventional search engines
AI-powered search tools like ChatGPT work differently from traditional search engines like Google. At their core, these platforms rely on large language models (LLMs) to process queries and generate results. Here’s a simple breakdown:
Query processing
Search engines crawl and rank web pages based on relevance, while AI tools like ChatGPT use pre-trained LLMs to understand user intent and generate answers. Instead of retrieving live results from the web, LLMs predict responses based on their extensive training data, creating highly contextual and conversational outputs.
Results format
Google provides a list of links, snippets, and rich results, encouraging users to explore. AI tools deliver direct, conversational answers, saving users time but reducing the need for clicks.
Freshness of information
Search engines continuously update their index to reflect the latest content. AI search tools, unless integrated with live updates, rely on the data within their LLMs, which may occasionally result in outdated information.
Transparency
Google provides links to original sources for easy verification. Similarly, ChatGPT Search, when operating with browsing capabilities, includes links to sources for the information it retrieves. This helps users trace the origin of the answers provided. However, when ChatGPT operates without live browsing (using its pre-trained model), it does not cite sources directly.
Optimizing for both worlds means ranking high on search engines while also creating content that aligns with how LLMs interpret and summarize information. This requires clear, authoritative, and context-rich writing that AI can easily process and incorporate into its results.
Understanding different types of AI search
Each AI-powered search platform has unique strengths and approaches, driven by some of the most influential tech companies. Let’s explore the biggest players on the market.
ChatGPT search
ChatGPT, developed by OpenAI, revolutionizes how people interact with search. Instead of offering a list of links, it generates direct, conversational responses to user queries. Users can refine their questions in real time, turning a single query into an iterative conversation.
ChatGPT reached over 100 million users within two months of its launch in November 2022, making it the fastest-growing consumer app in history. By late 2024, it had over 300 million weekly active users, generating over 1 billion messages daily.
How it delivers search results: ChatGPT is powered by OpenAI’s GPT-4 model, an LLM trained on vast text datasets. It doesn’t crawl the web in real-time but relies on its pre-trained knowledge, updated periodically. When connected to live search capabilities (such as Bing Search), it retrieves real-time results and cites sources, making it a hybrid search experience.
Google’s AI Overviews
Google AI Overviews incorporate AI-powered summaries directly into search results, providing users with quick insights by consolidating information from multiple reliable sources. These overviews appear above traditional search listings, offering concise answers that help users find information faster without navigating through numerous web pages.
How it works: Google AI Overviews utilize the advanced Gemini AI model, previously known as Bard, along with Google's extensive Knowledge Graph. By analyzing content from authoritative sources, it generates precise, intent-driven summaries. The underlying large language model (LLM) refines results based on factors such as search intent, semantic relevance, and content credibility, ensuring users receive the most relevant information efficiently.
Google Gemini
Gemini, formerly known as Bard, is a generative AI chatbot developed by Google. It is part of Google’s strategy to challenge ChatGPT’s dominance, with plans to integrate it more deeply into Google’s products by 2025. Its team operates under DeepMind, Google’s AI research hub.
How it delivers search results: Gemini combines Google’s existing search algorithms with AI-powered language and visual processing. This enables it to provide interactive, multimedia-rich answers, going beyond simple text-based responses.
Bing AI search
Microsoft’s Bing has positioned itself as an AI-powered alternative to Google. By integrating OpenAI’s GPT technology, Bing combines traditional search results with conversational AI features. Microsoft’s $13 billion investment in OpenAI underscores its commitment to making Bing a key player in AI-driven search.
How it delivers search results: Bing AI uses OpenAI's GPT-4 model, providing conversational answers alongside web results. Unlike ChatGPT, it actively retrieves and ranks web pages in real time while offering AI-generated summaries.
Other major players
Apple’s AI-driven Spotlight goes beyond finding files or apps—it offers web search capabilities directly on devices. It personalizes results based on user behavior within the Apple ecosystem. Spotlight uses on-device machine learning for personalization and pulls search results from the web when needed.
Meta’s AI-powered search focuses on personalized content discovery within its social platforms. AI suggests content based on user behavior, preferences, and social connections, making it more about recommendation than traditional search.
Amazon’s AI search enhances eCommerce with personalized product recommendations. It uses user behavior, past purchases, and detailed product data to surface the most relevant options.
Baidu and Yandex lead AI searches in China and Russia, offering region-specific results that cater to local languages and customs. These platforms rely on AI to process complex queries in native languages while integrating localized content and cultural nuances.
AI search optimization strategies: keyword research, content, and beyond
Now that we’ve explored the major players in AI search, it’s time to dive into the practical side—how to optimize your website to get indexed and drive traffic.
To stay ahead in this evolving landscape, here are the key strategies every SEO should master.
1. Nail keyword research for conversational queries
AI search platforms are designed to understand natural, conversational language, making traditional keyword tactics less effective. Instead of focusing solely on high-volume, generic terms, adapt your approach to match how users naturally phrase their queries.
Focus on questions and long-tail keywords
AI tools handle more specific, detailed queries. Use tools like Rank Tracker to find question-based and long-tail keywords. You can start with the Related Questions tool and then get more ideas from Ranking keywords and Autocomple:
If you already have a large list of keywords in your project and want to view only the long-tail phrases, you can apply the keyword length filter and then sort them by search volume or keyword difficulty.
Tip: Think like your audience
AI queries mimic how people speak. Explore “how-to” questions, comparisons, and specific needs to align with user intent.
2. Optimize content for AI-friendliness
Producing well-researched, insightful content that establishes authority increases your chances of being referenced by AI-powered search engines.
A great foundation is aligning your content strategy with Google’s E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) principles. These guidelines emphasize the importance of creating content that not only informs but also builds credibility and trust with both users and search algorithms.
Once you have E-E-A-T in mind, shift your focus to crafting valuable, actionable content that resonates with your audience. Your content should go beyond surface-level information and include elements that enhance its credibility, such as:
- Expert insights: incorporate quotes or perspectives from industry professionals to lend credibility and context.
- Citations from authoritative sources: reference reliable studies and reports to strengthen your claims.
- Balanced viewpoints (pros and cons): presenting a well-rounded discussion makes your content more comprehensive and trustworthy.
- Data-backed analysis: use statistics and case studies to provide tangible evidence and support key arguments.
Additionally, you should align your content with search intent—the underlying reason behind a user's query. Whether someone is looking for information, a product, or a solution to a problem, your content should anticipate and fulfill their needs. Failing to match search intent can result in high bounce rates and lost opportunities.
Finally, work on your content format and structure:
- Use a question-answer format: write headings and subheadings as questions to align with AI-generated responses. Example: “How does AI search work?” instead of “AI search overview.”
Tip: View the Topics and questions hints in the Content Editor tool of WebSite Auditor:
- Be concise and direct: AI platforms summarize content, so lead with short, valuable answers and follow up with more details.
Example: Start with a 2-3 sentence summary, then expand with supporting information.
- Structure your content clearly: use bullet points, numbered lists, and clear subheadings. AI favors well-organized content that’s easy to extract and present.
3. Optimize for featured snippets
Featured snippets are a key entry point for AI platforms like Google AIO.
To increase your chances of being featured:
- Answer questions clearly and succinctly: provide a direct, concise response at the start of your content, followed by supporting details.
- Use structured data: mark up your content with FAQ schema to make it more snippet-friendly.
- Write snippable paragraphs and lists: make sure to include lists and short paragraphs that could be used by Google to generate a featured snippet.
Example: instead of burying the answer in paragraphs, start with: “The best laptops for video editing in 2025 are [Brand A] and [Brand B].” Then expand with features and comparisons.
4. Focus on entities and topics for Google’s Knowledge Graph
Google’s Knowledge Graph plays a significant role in AI search, helping to connect entities like people, brands, and locations with related concepts. Optimizing for entities ensures Google understands your content in context.
How to align with the Knowledge Graph:
- Use precise terminology: clearly define and mention entities (brand names, product categories, locations) in your content to enhance relevance.
- Develop content clusters: build comprehensive, interlinked content around core topics to signal topical authority.
- Leverage structured data: as mentioned earlier, you should use schema markup (such as Organization, Product, and Event schema) to provide additional context about your content.
Focusing on entities improves your chances of appearing in AI-generated summaries and carousel-style search results.
5. Get mentions and reviews
AI search engines factor in brand mentions and user-generated content as credibility signals. Building a strong digital presence through mentions and reviews can boost your search visibility. Here’s how to do it:
- Monitor mentions with tools like Awario: create alerts for your brand name and target keywords and discover what people say about your company and product online.
- Encourage genuine customer reviews: platforms like Google Business Profile, Trustpilot, and industry-specific review sites play a crucial role in building trust.
- Earn citations naturally: Engage in PR, guest blogging, and industry collaborations to secure credible mentions from authoritative sites.
Consistent mentions and positive reviews increase your site’s authority, making it more likely to be surfaced by AI search platforms.
6. Leverage content diversity
AI search engines prioritize multimedia-rich content, which enhances engagement and provides more comprehensive answers. Expanding beyond text can improve visibility and reach.
Content formats to consider:
- Video tutorials, explainers, and interviews can rank in AI-generated results.
- Infographics and visuals: simplify complex topics with engaging visual content.
- Audio content: Podcasts and audio summaries resonate with voice search users and multitaskers.
Diversifying your content portfolio ensures your information is accessible across different AI search formats.
7. Optimize for technical SEO
Even in the AI era, a strong technical SEO foundation remains crucial. Ensuring your site is technically sound allows AI-powered search engines to crawl and interpret your content efficiently.
Here’s what you can do to improve your technical SEO:
- Fix crawl errors: regular audits with WebSite Auditor can help you identify and resolve crawl and indexing issues.
- Enhance page speed: use tools like PageSpeed Insights to identify and fix slow-loading elements.
- Ensure mobile-friendliness: responsive design is critical, as AI search is heavily used on mobile devices.
- Make sure your content is interconnected through strategic internal linking, guiding AI models to understand content hierarchies and topical relevance.
A technically optimized site enhances your chances of appearing in AI-powered search results and improves user experience.
Conclusion
AI-powered search engines are reshaping the SEO landscape, favoring conversational queries, multimedia content, and well-structured answers. Whether you’re optimizing for ChatGPT’s conversational responses, Google AIO’s featured snippets, or Google’s Knowledge Graph entities, the strategies remain rooted in creating user-focused, authoritative, and technically sound content.
By adopting these best practices, you’ll position your website to succeed not just in traditional search engines but also in the evolving world of AI-driven platforms. The key is to stay adaptable, keep your content valuable, and always think ahead to meet the needs of AI-powered search users.
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