Google Has Taken It to the Next Step
With its new AI Mode experiment in Search Labs, you can ask anything—and Google AI will respond. Even more impressively, it has the ability to ask follow-up questions and provide results with citations.
Generative AI in Search offers powerful responses that deliver deeper information instantly without requiring you to dig through each article in the SERP. AI in Search can be your best friend when you want a quick overview—but be prepared: AI Mode may sometimes give you weird, unusual, or odd responses, much like the early days of Google AI Overviews.
Richard Uzelac, CEO of GoMarketing, will break down exactly how Google AI works and how it could affect your business.
How to Access AI Mode?
- You can go to google.com/aimode
- You can directly ask the question from the search bar in google.com and tap the ai mode below the search bar
- From the Google app, you can tap AI mode below the search function on the home screen.
How Google AI Search Works as of 2025?
Google explains that AI Mode taps into up-to-date global information by combining web content with sources from within Google itself—like factual data from its Knowledge Graph and product-related info from its Google Product Graph.
It also introduces a new capability called the “query fan-out” method. This technique runs several related searches at once, pulling in insights from various subtopics and data sources, then merging them into a single, streamlined response. According to Google, this strategy offers users a broader and deeper understanding than what traditional search results typically provide.
Users can also continue the conversation by asking follow-up questions. Thanks to contextual awareness, AI Mode remembers your previous query and refines its answers based on your ongoing interaction—making it easier to get specific and relevant responses.
On top of that, AI Mode is multimodal. You’re not limited to typing—you can search using voice, text, or even images and keep the conversation going using any of those methods.
Google AI Just Launched and Is Still in its Experiment Mode.
Google has officially rolled out AI Mode, and it could totally transform how you search online. But don’t be surprised if you come across some strange or unexpected answers—just like we saw in the early stages of Google’s AI Overviews.
How Data Helps Google Develop Generative AI in Search
Google’s generative AI in Search represents a major shift in how we interact with information online. Behind this breakthrough technology lies a vast ecosystem of data, user interactions, and advanced machine learning systems that work together to create more intelligent and helpful search experiences.
To build and improve these AI-driven features, Google draws insights from how people engage with Search and its AI experiences. This includes analyzing what users search for, which results they interact with, how they respond to generated content, and the feedback they submit. All of these interactions become key data points that inform and fine-tune the AI models that power generative Search responses.
How Does Generative AI Work
Generative AI doesn’t just guess answers—it uses a mix of data patterns, contextual understanding, and semantic relationships to deliver informative, concise summaries from across the web. Google’s large-scale machine learning infrastructure allows it to interpret not just keywords but intent. By studying how users phrase questions, what types of answers they prefer, and how they navigate search results, Google can train its AI systems to generate more relevant, high-quality responses over time.
What sets Google apart is the scale and sophistication of its machine-learning operations. The company’s AI systems are capable of handling billions of data points, learning from global patterns while adapting to individual queries. Google’s unique blend of real-time web content, facts from its Knowledge Graph, shopping data from the Product Graph, and its proprietary “query fan-out” technique—where it runs multiple related searches behind the scenes—creates richer, more complete responses than a traditional search.
At the heart of all this is a powerful feedback loop: AI learns from humans, improves based on their behavior, and becomes more useful with every interaction. But as powerful as this system is, Google also understands the critical importance of user privacy and data protection.
Balancing Innovation with Privacy: How Google Protects Users While Training AI
At the heart of all this is a powerful feedback loop: AI learns from humans, improves based on their behavior, and becomes more useful with every interaction. But as powerful as this system is, Google also understands the critical importance of user privacy and data protection.
To ensure that privacy is respected throughout this process, Google implements strong safeguards when using human reviewers to help improve Search’s machine learning models. Data that is seen and annotated by these trained reviewers is deliberately separated from user accounts. Automated tools are used to detect and remove personally identifiable information (PII) and other sensitive data before it’s ever reviewed. This means that while user interactions help shape the future of AI in Search, individuals remain anonymous and protected throughout the process.
Richard Uzelac's Two Cents For SEO Companies
AI systems like Google’s rely heavily on high-quality, clearly written, structured data. Pages that are well-optimized with schema markup, trustworthy content, and E-E-A-T (Experience, Expertise, Authoritativeness, and Trust) principles are more likely to be cited by AI or included in its summaries. Creating expert-level content, using structured data, and building strong authority signals (like backlinks and author bios) will be more important than ever.
