Google AI Overview is Just a Transitional Phase: Towards the Future of Google AI Mode

Introduction: The Evolution of the Search Landscape

Since the popularization of the internet, search engines have been our primary tool for obtaining information. Google Search has long held a dominant position, becoming the preferred platform for billions of users worldwide to find answers, explore new knowledge, and complete tasks. However, with the rapid development of artificial intelligence (AI) technology, the search domain is undergoing a profound transformation. This report aims to analyze the current status and future of the AI Overview (AIO) feature in Google Search, explore industry discussions and predictions regarding the "AI Mode" search model, and evaluate the impact of the shift from the traditional "search" mode to the "ask" mode on user behavior and information acquisition methods. The core viewpoint is that the current AI Overview is just a transitional phase for Google in integrating AI into its search engine, and "AI Mode" will be the actual form of future search. Users will no longer face ranking pages but will directly interact with AI through questions and answers. This report will delve into this viewpoint, analyzing its feasibility, impact on users, and how businesses and website operators should respond.  

Google's AI Overview: A Transitional Phase?

Google's AI Overview (AIO) is a feature that utilizes artificial intelligence technology to provide users with instant, expanded answers to their queries at the top of Google search results pages. Google extracts information from various sources to provide insights directly on the search page, eliminating the need for users to click through multiple websites to obtain the information they need. AI Overview aims to simplify the user's search process by providing an AI-generated snapshot containing key information and in-depth links, allowing them to find the required information faster and more easily.  

Currently, the functions of AI Overview include presenting answers in the form of concise text paragraphs, bulleted lists, or image lists. Users can click to expand and view more detailed information and cited source links. AI Overview is typically targeted at informational queries, especially longer-tail, complex questions where Google believes AI can provide value beyond traditional search results. For example, when a user searches for "how to bake a cake," AI Overview might provide a summary including steps, required ingredients, and related images.  

Google clearly holds a positive attitude towards the future development of AI Overview. The Gemini 2.0 model has already been applied to AI Overview in the United States to handle more difficult questions, including code, advanced mathematics, and multimodal queries, and will be expanded to more types in the future. AI Overview has been launched in over 100 countries and regions worldwide, reaching more than 1 billion users every month. This shows that Google considers AI Overview a core part of its search strategy and continues to invest resources in its improvement and expansion.  

However, AI Overview also faces some limitations and criticisms. Early versions had inaccurate and even dangerous information, causing strong user backlash. Even after improvements, AI Overview may still generate erroneous information known as "AI hallucinations" . In addition, AI Overview directly providing answers may reduce users' willingness to click on websites, impacting websites that rely on search traffic. These challenges indicate that although AI Overview is an important step for Google in integrating AI, it may only be a transitional phase towards a more comprehensive AI-driven search experience.  

The Arrival of "AI Mode": Foreseeing the Future of Search

In industry discussions and predictions about future search models, "AI Mode" is considered the form of the next-generation search engine. Unlike the current AI Overview, "AI Mode" is expected to provide more advanced reasoning, thinking, and multimodal capabilities, allowing users to ask more complex and nuanced questions and receive more comprehensive responses from AI.  

Under "AI Mode," the user interface may place greater emphasis on conversational interaction. Users can directly ask questions in natural language and follow up based on AI's answers, forming a more fluid information acquisition process. For example, a user might ask, "Where in Boston can I find scenic spots suitable for engagement photoshoots?" AI Mode might provide a series of suggestions and allow the user to further inquire about the characteristics of each location, the best shooting times, etc... This mode aims to simulate the experience of conversing with a knowledgeable assistant, making it easier for users to explore topics, compare options, and reason.  

The main difference between "AI Mode" and traditional search and AI Overview lies in its information presentation method. Some predictions suggest that "AI Mode" may completely replace traditional ranking pages, with users only seeing comprehensive answers generated by AI and related cited links. AI Mode may utilize "query fan-out" technology, simultaneously issuing multiple related searches, collecting information from different data sources, and then integrating the results into an easy-to-understand response. Although AI Mode aims to provide more direct answers, it will still provide links so that users can delve into relevant web content.  

Many industry experts believe that the emergence of "AI Mode" will be a significant shift in the search domain, possibly even marking "the end of search as we know it". This mode will transform search from a process requiring users to actively input keywords and filter results into an experience more like conversing with an AI assistant. However, the success of AI Mode also depends on its ability to provide accurate, comprehensive, and trustworthy information while maintaining users' access to diverse content sources.  

From Search to Ask: The Transformation of User Behavior

The shift from the traditional "search" mode to the "ask" mode is expected to have a profound impact on user behavior and information acquisition methods. In the "ask" mode, users no longer need to think about which keywords to use to find the information they need but can directly ask questions in natural language. This transformation makes search more intuitive and easier to use, especially for users unfamiliar with traditional search techniques.  

The way users obtain information will also change. In traditional search, users usually need to browse multiple search results, click on different websites, and integrate the information themselves to find answers. In the "ask" mode, the AI system will directly provide a comprehensive answer and may conduct a more in-depth exploration based on the user's follow-up questions. This mode can save users time and effort, allowing them to obtain the information they need more quickly.  

The "ask" mode may also prompt users to engage in more interactive and conversational information exploration. Through follow-up questions, users can gradually refine their questions and guide the AI system to provide answers that better meet their needs. This iterative information acquisition method helps in a deeper understanding of complex topics.  

However, this transformation may also bring some potential negative impacts. Over-reliance on direct answers provided by AI may reduce users' critical thinking skills and willingness to explore different information sources. If users only rely on the single answer provided by AI, they may miss other valuable perspectives and information. Therefore, future search systems need to provide convenient answers while also encouraging users to maintain habits of independent thinking and information verification.  

The Fate of Ranking Pages: Information Presentation in the AI Era

Whether traditional search result ranking pages will be completely replaced in the AI-driven search era is a question of great concern. Although some predictions suggest that "AI Mode" may eventually completely replace ranking pages, a more likely scenario is that we will see the emergence of a hybrid model in the foreseeable future.  

In a hybrid model, the AI system might first provide a comprehensive answer to the user's question and then present a reduced version of the traditional search results list below or next to the answer, containing web links cited or deemed relevant by the AI system. This approach can both meet the user's need for quick answers and provide a way to explore and verify information in depth.  

Different types of queries may present results in different ways. For example, for clear informational questions, the AI system may directly provide the answer, while for shopping or navigational queries that require browsing and comparison, traditional link lists may still be more important.  

In addition, the development of visual and multimodal search may also affect the way information is presented. In the future, search results may no longer be limited to text links but may include more images, videos, and interactive elements, directly integrated into the answers provided by AI or presented in a more visual way in traditional search results.  

In summary, although the importance of traditional ranking pages may decline in the AI era, the possibility of their complete disappearance is relatively low. More likely, we will see a smarter, more integrated search result presentation method where AI-generated answers and traditional search results complement each other to jointly meet users' information needs.

The End of Traditional SEO? Adapting to an AI-Driven Future

As AI plays an increasingly important role in the search domain, whether traditional search engine optimization (SEO) strategies are still applicable, or how they need to be adjusted, has become an issue that businesses and website operators must face. Although AI-driven search modes may reduce users' clicks on traditional search results, this does not mean that SEO will become completely obsolete. On the contrary, SEO needs to evolve and adapt to this new environment.  

In "AI Mode," the quality, relevance, and authority of content will become more important. Website operators need to focus on creating in-depth, accurate, and user-centric high-quality content that directly answers questions users might ask.  

Optimizing for natural language and conversational queries will become crucial. Website content should use natural, concise language and cover various ways users might ask questions.  

Implementing structured data and Schema markup will help AI systems better understand the meaning and context of web page content. This can increase the chances of website content being cited in AI-generated answers.  

Building and maintaining strong Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) will be key. AI systems are more inclined to cite content from trustworthy sources.  

In addition to text content, website operators should also consider creating more diverse content formats, such as videos, images, and interactive elements, to adapt to multimodal AI and user preferences.  

Building a brand and enhancing authority will become more important. AI systems may be more inclined to cite well-known brands and websites with authority in specific fields.  

In short, although traditional SEO strategies need to be adjusted, their core goal remains to provide high-quality, relevant, and trustworthy content. In the AI-driven future, the focus of SEO will shift to optimizing content so that it can be understood and cited by AI systems, and to building strong brand authority. This new field is sometimes referred to as "Generative Engine Optimization" (GEO) .  

Expert Opinions: Navigating the Future of Search

Many experts have offered their views on the future development of AI in the search domain and its impact on SEO. They generally believe that AI is not just a feature of search engines but a fundamental transformation.  

A former Baidu search product director pointed out that future searches will no longer just be about queries and lists of links but will help users complete tasks. Tasks such as research, analysis, and content generation will increasingly be transferred to AI chatbots. An expert enthusiastic about the development of search technology emphasized that search is developing towards semanticization, real-time capabilities, and multimodality.  

Regarding the future of SEO, experts unanimously agree that it will be closely linked to the development of AI. Traditional keyword research is still important, but more important is creating meaningful interactions and standing out in the information-overloaded digital world. Some experts predict that website traffic for purely informational content will decline, while websites with high-quality, authoritative backlinks will be more favored. Some even believe that the meaning of SEO is changing from "search engine optimization" to "search everywhere optimization".  

Experts also expect search engine algorithms to continue to evolve, placing greater emphasis on content's E-E-A-T, user experience, and the ability to provide direct, accurate answers. Google's 2025 algorithm update further emphasizes EEAT and conducts stricter reviews of low-quality AI-generated content.  

Overall, experts believe that companies need to deeply understand the capabilities and limitations of AI and focus on creating content that resonates with both users and AI algorithms to succeed in the AI-driven search future.  

AI Overview vs. AI Mode: Comparative Analysis

Feature	AI Overview	AI Mode (Predicted)
User Interface	Appears above traditional search results	May exist as a separate mode or tab, replacing traditional search results
Query Type	Primarily for informational queries	Aims to handle more complex queries requiring reasoning and comparison
Information Presentation	Concise summaries including text, lists, or images, with links	More comprehensive AI-generated responses, possibly including multimodal content, with links provided
Interactivity (Follow-up Questions)	Limited	Emphasizes conversational search and follow-up question capabilities
Query Complexity Handling	Lower	Higher, able to handle more nuanced and multi-layered questions
Presentation of Traditional Search Results	Usually presented below is the AI Overview	May completely replace or be presented in a reduced form as resources for citation or further reading

 

Both AI Overview and the predicted AI Mode utilize generative AI to provide answers to user queries and aim to enhance the search experience, allowing users to obtain information faster and more easily. Both are driven by Google's large language models, such as the Gemini model, which has been applied to AI Mode and the upgraded AI Overview.  

However, there are key differences between the two in terms of functionality, user interface, and intended use. AI Mode is expected to exist as a separate mode or tab, possibly completely replacing traditional search results pages, while the current AI Overview appears above traditional search results. AI Mode places greater emphasis on conversational search and follow-up question functionality, which is not prominent in the current AI Overview. In addition, AI Mode aims to handle more complex queries requiring reasoning and comparison, while AI Overview currently focuses mainly on informational queries.  

The development of AI Overview seems to be a phased step in Google's gradual integration of AI into its search engine. The upgrade of Gemini 2.0 has brought more advanced features to AI Overview, which can be seen as a move towards a more comprehensive "AI Mode". The launch of AI Mode as an early experiment in Labs also indicates that Google is testing and iteratively developing a more immersive AI-driven search experience. The gradual integration of multimodal capabilities in AI Overview may also pave the way for more advanced interaction methods in AI Mode.  

Embracing the "Ask" Era: Response Strategies for Businesses and Website Operators

Traditional SEO Focus	New SEO Focus (for AI)
Keyword Density	Natural Language Understanding
Link Quantity	Link Quality and Authority
Technical Optimization (Crawlability)	Technical Optimization (AI Readability and Structured Data)
Generic Content	Comprehensive and User-Centric Content
Ranking for Keywords	Answering Questions and Building Authority
Click-Through Rate	Impressions and Brand Mentions

 

Facing the upcoming "ask" AI search era, businesses, and website operators need to adjust their strategies to cope with new information dissemination and marketing models. Here are some key response strategies:

The top priority is to focus on creating high-quality, comprehensive content that directly answers questions users might ask. Content should delve deeply into topics, provide accurate information, and be presented in a way that is easy for users to understand.  

Optimizing for natural language and conversational queries is crucial. Think about how users ask questions in a spoken manner and naturally incorporate these language patterns into your content.  

Implementing structured data and Schema markup can help AI systems better understand web page content, increasing the likelihood of being cited in AI-generated answers.  

Building and maintaining strong E-E-A-T will be key to gaining AI's trust. Emphasize the author's experience and expertise, cite authoritative sources, and ensure the overall credibility of the website.  

In addition to text content, also consider creating videos, images, and interactive content to meet the needs of multimodal AI and users.  

Actively build your brand and enhance your authority within the industry, which will help AI systems recognize your website as a trustworthy source of information.  

Continuously monitor the development trends of AI search and adjust your strategies based on the latest algorithms and user behavior.  

Finally, it may be necessary to re-evaluate the metrics for measuring success. In the "ask" era, traditional click-through rates may no longer be the only measure; impressions, brand mentions, and influence in AI-generated responses may become more important.  

The core of these strategies is to focus on creating high-quality, user-centric content, which is consistent with the best practices of traditional SEO. The emergence of AI has only amplified the importance of these principles and requires companies to adopt a more comprehensive online strategy to ensure visibility and influence in the ever-changing search environment.

Conclusion: Embracing the Transformation of Search

This report analyzed the evolution of Google Search from AI Overview to the predicted AI Mode, as well as the trend of shifting from the traditional "search" mode to the "ask" mode. The analysis shows that the current AI Overview can be seen as an important transitional phase for Google in integrating AI into its search engine, and future search is likely to move towards a more conversational and interactive "AI Mode." In this mode, users will be able to ask questions in natural language and receive comprehensive answers directly provided by AI, and traditional ranking pages may be replaced or presented in a different form.

Although the way information is retrieved is changing, the demand for high-quality, trustworthy content remains crucial. Businesses and website operators need to adjust their strategies, focusing on creating in-depth, accurate, and user-centric content, and optimizing for natural language queries and AI systems. Building strong brand authority and diverse content formats will also be key to success in the AI-driven search era.

AI-driven search brings new opportunities for businesses, such as reaching users in a more personalized way, but it also brings challenges, such as the need to adapt to potentially different traffic patterns. Embracing this transformation, and continuously learning and adjusting strategies, will be key for businesses to remain competitive in the ever-evolving digital world.

 

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