AI Features You Should Know

Before we dig into each feature, it’s helpful to understand why AI has become such a big part of Google Search. Modern search isn’t just matching keywords anymore. Google now uses machine learning and generative AI to understand user intent, interpret images and voice, create instant summaries, and help users explore complex topics more interactively.

In this section, we’ll go through the major AI features that Google uses today in search, explain how they work, and show how website owners and SEO learners can align their content strategy accordingly.

1. AI Overviews: Summarizing Answers Quickly

What it is:

When a user types a question or topic that can be answered in a short summary, Google can generate an AI Overview using its Gemini model. This appears usually at the top of the search results, offering a snapshot of key points, often with follow-up links to explore.

Why it matters:

• Users often get their answer from the summary and don’t click further, so appearing here can be a big win for visibility.

• Google tests this feature with more complex queries now (like coding questions, multimodal searches, deeper research topics).

• If your content is well structured, concise, and clearly answers common questions, Google is more likely to pull it into an AI Overview.

What you can do:

• Structure content with clear headings, question-answer format, and direct answers to common queries.

• Use bullet lists or numbered steps when summarizing a process or explaining a concept.

• Ensure your content is up-to-date and factually reliable AI models prefer accurate and timely information.

2. AI Mode: Interactive Search Conversations

What it is:

A newer feature, AI Mode (now rolling out in several markets) turns simple queries into more advanced conversational and exploratory search experiences. Google breaks down a complex question into subtopics (“query fan-out”), runs multiple searches behind the scenes, and presents the results in a more guided, interactive format.

Users can ask follow-up questions, refine the results, and explore deeper without having to manually start new searches.

Why it matters:

• This shifts Google Search closer to a conversational assistant model.

• Users might stay within Google’s AI Mode for longer, exploring multiple facets of a topic in one session rather than visiting many separate pages.

• It raises the bar for content clarity and structure, since Google needs to pull relevant “chunks” of information quickly and serve them coherently.

What you can do:

• Think of your content as having modular sections self-contained mini-answers that can stand alone but also link to deeper content.

• Use question-based subheadings, FAQs, or clearly labeled sections that can respond to follow-up questions.

• Make sure your page handles multimodal queries (text, images, video) cleanly so Google can extract relevant parts easily.

3. Multimodal Search, Google Lens & Visual AI

What it is:

Google Lens and multisearch let users search using images (or a mix of image + text). More recently, Lens has been upgraded with generative AI so it can generate AI Overviews directly from visual queries essentially “seeing” an object and answering questions about it.

There are capabilities to ask voice or text follow-ups after sending an image, creating a more interactive visual search experience.

Why it matters:

• Visual queries are growing fast, and Google’s AI is improving how it turns those images into meaningful search results.

• If your content includes useful images, infographics, or visual elements, properly optimizing them (with alt text, captions, structured data, and contextual explanation) increases the chances Google can pull them into multimodal results or visual overviews.

What you can do:

• Always use meaningful alt text and captions with images.

• Provide context for images in the surrounding text avoid “floating” images with no explanation.

• Use structured data (e.g., image metadata, visual schema, product images) so Google knows what it’s looking at.

Personalization and Context in AI Search

What it is:

Google’s AI features increasingly rely on user context (like past searches, location, preferences, account activity) to customize responses. AI Mode may use this context to suggest actions (e.g., nearby restaurants, timelines for a project) or follow-ups tailored to the user.

Why it matters:

• Personalized results can make Google Search behave more like a smart helper than a simple information retrieval tool.

• For SEO, this means content that is broadly useful and adaptable to different user contexts tends to perform better. Pages that are flexible, up-to-date, and clearly structured will more easily adapt to different user intents.

What you can do:

• Keep content current and refresh it when facts change or when newer developments come in.

• Where possible, anticipate different audience needs (beginners vs intermediates, mobile users vs desktop users, location-specific versions) and structure your content to serve multiple “starting points.”

• Use schema markup for location, events, or user-specific information where applicable (like “Open hours” or “FAQ per country”).

Best Practices Across Google’s AI Features

Putting everything together, here’s a simple evergreen checklist for SEO learners and site owners to stay aligned with Google’s evolving AI-powered search:

1. Write clear, modular content that can serve as mini-answers or sections.

2. Use question-answer structures and FAQs to help Google extract relevant chunks.

3. Connect your multimedia elements (images, videos, infographics) with descriptive text and structured data.

4. Regularly update content so it stays factually accurate and timely.

5. Test how your content appears in Rich Results, Lens, and AI Overviews using Google’s testing tools.

6. Monitor Google Search Console or AI Mode feedback for changes adapt your content when Google starts showing more visual/AI-driven results.