I’d like to discuss what the future holds for traditional SEO amid the rapid development of AI search.

This article presents some insightful perspectives drawn from the author’s several years of experience in SEO and ongoing interest in the industry, with the aim of providing useful guidance for SEO research and development. Given the constant evolution of the SEO industry, the suggestions offered here are for reference only; readers are advised to apply them with caution based on their own circumstances.

As an in-house SEO specialist who deals with traffic data on a daily basis, I know this all too well. I believe that the question of “which is better” depends on who you are and what you want.

For the average consumer, AI-powered information retrieval tools are widely used because of their convenience and speed. However, in content production and operations, this technological advancement has caused significant unease among industry professionals. The current situation has gone far beyond a simple process of replacing the old with the new; rather, it represents a state of “coexistence and mutual prosperity”: on the one hand, people can freely choose the information sources they need; on the other hand, industry professionals must navigate an environment comprising a wide variety of AI software and traditional search engines. This represents a transformation for the entire digital content industry as well as an opportunity for the future.


Traditional search engines place higher demands on content, while AI search tools are on the rise

In the past, we were very clear that our job was to research Google’s algorithms and optimize rankings on Baidu. But now, search entry points and methods have become increasingly fragmented.

Traditional search engines still retain significant advantages, but their role is evolving. Major search engines such as Google and Baidu, with their powerful data-gathering capabilities and frequent information updates, play a crucial role in breaking news coverage and searches within specific fields. People generally use them to conduct basic information searches and assess the authenticity of information by comparing results across different websites. Although their business models remain robust and their operational efficiency is high, their function is no longer limited to that of a knowledge service provider; rather, they are increasingly serving as authoritative fact-checking tools.

Recent advancements such as Google’s Search Generative Experience (SGE), Microsoft Copilot, and Perplexity.ai are fundamentally transforming the way users interact with search engines. These advancements are all built on the foundation of accurately understanding user needs, making the quality of “intent recognition” the key criterion for evaluating them. Compared to previous approaches, these systems can provide structured answers rather than just a list of links, significantly improving the speed at which information is conveyed from question to answer. This undoubtedly delivers a better user experience while also impacting content distribution on the internet.

This has brought about a major shift for SEO professionals, as their responsibilities are no longer limited to securing a good ranking for websites on traditional search engine results pages (SERPs), but now include ensuring that their articles are cited more frequently and displayed effectively by new search tools such as Google AI Summaries, Bing Copilot, and Perplexity. This also means that the industry’s focus has shifted from prioritizing “page rankings” to placing greater emphasis on “citation visibility.”


Three Real Challenges I’ve Faced with the Website While Working in a Team

I’ve also experienced this sharp drop in traffic firsthand; traffic to our company’s website has been declining as well. After analyzing the situation, we identified three sources, each with its own set of reasons:

📉 Challenge 1 · The Collapse of Value in Utility Pages: Google’s AI summaries have had a massive impact on the way traditional utility websites generate traffic. In the past, highly practical features such as “holiday lookups” and “currency conversions” served as important sources of traffic due to their convenience and speed. However, with the advancement of artificial intelligence, when people need to look up this information, they can often obtain accurate results directly rather than being redirected to a webpage. This has rendered such pages less meaningful as standalone sources of information and has also reduced the chances of them being viewed.
🔍 Challenge 2 · Refining Brand Search Behavior: Currently, search behavior for brand keywords is becoming more refined. Take “how to set up a store on Amazon” as an example: this keyword, which once had very high search volume on Bing, has gradually lost popularity over time. Against this backdrop, as algorithms continue to evolve and artificial intelligence advances, consumer demand for direct access to brands is growing. Official channels—such as “Temu’s official website”—or specific features (e.g., “Temu’s official website”) are receiving increased attention. The role of traditional referral landing pages has significantly diminished.
⚠️ Challenge 3 · Compound Pressure from the Baidu Ecosystem: Baidu is currently facing pressure from several fronts: First, Baidu’s own core traffic is steadily declining; second, the number of searches associated with its brand is also decreasing; and third, as part of its efforts to streamline its ecosystem, some content that should have been distributed through third-party channels has been incorporated into its own system, thereby affecting the role of external link building and content accumulation in traditional SEO.

Will SEO Die?

In today’s era of rapidly evolving technology, some people express skepticism about the future direction of traditional search engine optimization (SEO). Based on current research and industry trends, while the specific methods may change with technological advancements, its fundamental goal—using various means to ensure that one’s content or website is displayed more prominently by search engines and achieves higher rankings— —remains a timeless goal and is evolving toward new directions represented by AEO (Answer-Oriented Optimization) and GEO (Generative Optimization).

· AEO: Answer-Oriented Engine Optimization

AEO is optimized specifically for certain AI search engines (such as Google SGE or Perplexity), with the goal of making your content a reliable reference source for AI:

  • Ultimate factual accuracy and structure:The content should be clear and precise so that machines can easily understand it and generate a summary.
  • Strong E-E-A-T (Experience, Expertise, Authoritativeness, Trust):This is something Google has always advocated, and it’s even more important in the age of AI, because AI needs to be able to identify the credibility of information sources.
  • Semantic Relevance and Clear Entities:Ensure that the content of the article stays closely focused on the central theme, and that entities such as people, places, and things are clearly defined to facilitate AI understanding.

· GEO: Generative Engine Optimization

As a technological paradigm that plays a significant role in generative AI, the greatest advantage of GEO (Generative Enhancement Optimization) lies in its ability to “significantly improve the quality of generated results without requiring an understanding of its internal workings,” providing generative AI models with a convenient and powerful black-box optimization method. Compared to traditional optimization methods, it offers greater versatility and convenience and has already been applied to various types of generative AI scenarios. Some vendors claim that using GEO can help customers save significant marketing costs (approximately 50%–70%), and this market is growing rapidly, with the market size expected to reach billions in the coming years.


Is GEO a Scam? My Thoughts and Confusions

Recently, “GEO” has garnered significant attention and sparked widespread discussion due to its broad influence. Based on current research, it serves as a form of intellectual capital investment while also depending on the demand and prospects of a particular industry; however, some products in the market exhibit a relatively severe degree of homogeneity and show signs of a bubble.

This article does not propose a “stupidity tax,” but rather illustrates the point with a simple principle: When consumers use artificial intelligence to search for information, if the AI can effectively recommend the products or services they are looking for, that service provides significant value. Relevant research data shows that with the help of geolocation optimization (GEO), some brands can achieve an exposure rate of over 80% and garner more attention. This demonstrates that improving the accuracy of AI recommendations plays a crucial role in brand building.

⚠️ The Black Box Dilemma:
Since mainstream search engines like Google have established a relatively comprehensive level of transparency and partially disclosed their ranking criteria, people generally know how to optimize for SEO. However, the algorithmic decision-making processes of most artificial intelligence (AI) companies currently remain a “black box.” Unlike Google, which, in its *Search Quality Evaluation Guidelines》explains how search engines work and provides website owners with a channel for feedback; however, most AI companies do not fully disclose how their models are trained or how content is selected.
Existing generative pre-training (GEO) methods are largely based on trial and error and lessons learned from experience, and have not yet established a widely accepted and verifiable theoretical framework. This makes it difficult for search engine optimization (SEO) professionals to develop effective strategies to help clients with their optimization efforts, which in turn hinders the development of the digital marketing industry as a whole.

Rampant AI Crawlers, Data Corruption, and Issues with AI Commercialization

This new ecosystem has also been accompanied by chaos and controversy, the most prominent of which is the issue of data scraping.

🤖 The “Gentlemen's Agreement” That's Been Ignored: A case involving iFixit, a major overseas website dedicated to repair guides, is a prime example. In 2024, ClaudeBot—a bot operated by the AI company Anthropic—accessed the iFixit website more than a million times within 24 hours, severely straining its server resources. iFixit CEO Kyle Wiens angrily pointed out that this not only violated the site’s robots.txt protocol but also directly breached its terms of service, which explicitly prohibit the use of its content for AI training. This exposes a harsh reality: in the face of data-hungry AI companies, the binding power of robots.txt—a mere “gentlemen’s agreement”—is extremely limited.
🤝 From Confrontation to Compromise: The Wikipedia Example: Instead of fighting back, Wikipedia chose a different path. Faced with immense pressure from AI crawlers, the Wikimedia Foundation reached paid agreements with several AI companies, including Amazon, Microsoft, and Perplexity. AI companies pay for access to Wikipedia’s structured data, while Wikipedia receives funding to support its ongoing operations. This sets a precedent: high-quality data sources can be compensated for their work rather than being exploited for free.

🧨 Data Corruption and the Hidden Risks of Pay-Per-Click Advertising: This raises two deeper questions.

Could GEO optimization lead to AI database contamination? If a large number of websites engage in targeted optimization to be indexed by AI—or even create “content specifically for AI”—this could affect the quality and diversity of the AI’s training data. (You should have seen the power of GEO during the March 15, 2026, “315 Evening Gala.”)
Will AI companies launch large-scale pay-per-click advertising campaigns like search engines do? It's very likely. Once AI becomes the primary gateway to information, inserting promotional content into it will be an extremely tempting business model. Recently,llms.txt fileThis is also the source of the discussion; it’s like a “new sitemap” for AI crawlers, but Google has made it clear that it does not support it (Added on May 21, 2026,Google has officially stated that it is not used in the Google search engine., It’s unclear what other AI vendors or search engines think of this right now. To be honest, I also think this whole thing is pointless. Take some large websites, for example—they have hundreds of thousands of URLs. If you feed the AI a massive .txt file containing a huge number of URLs, each with a brief description, the sheer volume of data would just be a huge hassle for the AI), Other vendors’ stances remain unclear, and at present, it doesn’t seem very useful; industry standards are far from being established.

What Does the Future Hold for SEO?

So, what should an SEO team like ours do? Simply focusing on PV (page views) numbers is indeed becoming increasingly frustrating. I believe we need to make adjustments in the following areas:

📌 Content Strategy Transformation: From Traffic Acquisition to Value Deepening

Abandon those “tool pages” designed purely to capture simple information traffic. Build a content ecosystem centered on your core business that offers depth, expertise, and unique insights, and establish yourself as a true “authority on the subject.” Only then will your content have the long-term value to be cited and recommended by AI.

⚙️ Technical Optimization and Upgrades: Adapting to AI “Reading Habits”

Ensure the website’s technical architecture is robust and that it loads quickly. Give this the highest priority.Structured Data (Schema Markup)When deploying it, use “language” that AI can easily understand to clearly tell it what the page content is, who created it, and which entities it refers to. This can greatly increase the likelihood of it being accurately understood and cited.

🌍 Keep an eye on new frontiers: particularly international trade SEO and product conversion

I believe that, so far, international trade SEO remains a promising direction. When it comes to product conversions, we can actively explore ways to integrate AI search results. For example, when an AI answers the question, “What do I need to prepare for outdoor camping?” if your tent product information can be recognized and recommended by the AI in a structured way with clear features, this represents an effective form of GEO. Although AI does not yet directly help users place orders, it has become the most influential “recommender” in the decision-making chain. Optimizing product information to make it appear as a reliable and relevant solution in the eyes of AI may be the next untapped source of traffic.

🚀 The era of coexistence between AI search and traditional search has arrived. This transformation isn’t a game of elimination—it’s a process of upgrading. It’s phasing out outdated, mechanical optimization techniques while elevating our understanding of user value, the essence of content, and the rules of the ecosystem. As SEO professionals, our work hasn’t disappeared; rather, it has become more complex and critical—shifting from being “keyword rankers” to “builders of trusted sources in the eyes of AI.” This path is difficult and requires constant learning and trial and error, but we have no other choice.
Next Article How to Enable HTTP/3 for Your Website Using the Baota Panel (Nginx Tutorial)