以下文章来源于智能涌现 ，作者邓咏仪 智能涌现 . 直击AI新时代下涌现的产业革命。36氪旗下账号。 为了"骗"过模型，有人每天陪AI聊天，摸透模型的脾气和规则；有人在图片里用透明字体写上诱导语，扰乱模型答案排序。 文 ｜ 邓咏仪 编辑 ｜ 苏建勋 来源｜ 智能涌现（ID： AIEmergence ） 封面来源 ｜ unsplash 让你的产品在DeepSeek的答案里有一席之地，需要多少钱？ 人在哪，流量就在哪，入口就在哪。2025年春节后，DeepSeek的爆火，是一场真正意义上的AI产品出圈，让许多人第一次体验到大模型的力量。 精明的中国商家很快便打起DeepSeek的主意。没多久，上海街头就出现了挂着"DeepSeek推荐"招牌的小面馆；而安克创新在内的知名品牌，直接就在商品 页中打出海报：DeepSeek、豆包大模型推荐品牌。 安克创新充电宝商品图，图源：网络 SEO（搜索引擎优化），这门针对搜索结果做优化的互联网"上古生意"，正以一种新形态复兴——GEO（Generative Engine Optimization，生成式引擎优 化）是它的新名字。 GEO的核心目的只有一个：影响AI生成的答案，让 ...

Core Insights - The rise of DeepSeek has created a new market for Generative Engine Optimization (GEO), which aims to influence AI-generated answers to increase product visibility and traffic [1][3][5] - The GEO market is rapidly becoming competitive, with a significant increase in service providers, estimated to be between 500 to 1000 companies [3][5] - Traditional growth methods are stagnating, leading brands to seek new avenues for traffic, with GEO seen as a potential solution [5][18] Group 1: GEO Market Dynamics - GEO services are priced between thousands to tens of thousands of yuan, with a standardized process involving the creation of tailored articles for AI [6][8] - The effectiveness of GEO relies on understanding the preferences of different AI models, which requires continuous interaction and analysis [9][10] - The market is characterized by a high degree of service homogeneity, making differentiation challenging for providers [6][18] Group 2: Challenges and Limitations - The results of GEO are difficult to measure and maintain over time, as they are influenced by various factors including user context and model algorithms [15][17] - Many brands are experiencing anxiety over the effectiveness of GEO, with some resorting to extreme measures to ensure visibility [5][18] - The perception of GEO as a brand advertising tool rather than a performance advertising tool is growing, with limited actual conversion rates [18][30] Group 3: Information Pollution and Governance - The rise of AI-generated content has led to concerns about information pollution, with many low-quality articles flooding the internet [22][24] - Companies are employing various tactics to manipulate AI training data, leading to a cycle of content quality degradation [20][27] - Platforms are beginning to implement stricter governance measures to combat information pollution, but challenges remain due to the complexity of identifying intent in generated content [26][29] Group 4: Future Outlook and Strategies - The GEO market is expected to evolve as companies seek to establish clearer rules and standards, particularly as AI platforms begin to commercialize [37][38] - Successful engagement with AI models will require a shift from traditional content strategies to more sophisticated approaches that prioritize quality and relevance [32][36] - Companies that have not previously engaged in online marketing may find new opportunities in GEO, as it offers a way to establish an online presence [36]

Core Viewpoint - GEO (Generative Engine Optimization) is emerging as a new marketing paradigm in the AI era, distinct from traditional SEO (Search Engine Optimization), which remains significant in digital marketing [3][4]. Group 1: Conceptual Overview of GEO and SEO - SEO is a classic form of performance advertising aimed at optimizing website content and structure to improve search engine rankings, thereby increasing traffic and conversions [6]. - GEO focuses on optimizing brand performance on AI interaction platforms, establishing trust with AI algorithms to ensure brand information is prioritized in AI-generated responses [7]. Group 2: Current State of Domestic Large Model Applications - Major domestic AI chat applications like DeepSeek and Kimi lack direct e-commerce link functionalities, limiting their role to the "interest generation" phase, akin to the 1.0 version of platforms like Xiaohongshu and Douyin [9][10]. - The integration of AI models with e-commerce faces challenges due to market competition and the complexity of the supply chain, making it uncertain when a mature model will emerge in China [10]. Group 3: GEO as Brand Advertising - GEO enhances brand recognition and image by ensuring frequent exposure of brand information in AI-generated answers, fostering a positive association in consumers' minds [14]. - It emphasizes long-term value and trust accumulation, as brands can build credibility through consistent quality content on AI platforms [15]. - GEO leverages the vast user base of AI platforms to expand brand reach and influence, similar to a large social gathering where brand information is widely disseminated [15]. Group 4: Case Studies of GEO Implementation - A high-end housekeeping brand optimized its content for specific queries, achieving top visibility on DeepSeek, which enhanced its professional image over time [18]. - A medical device company restructured its technical documents into a Q&A format, significantly increasing its citation rate on AI platforms, thereby strengthening its authority in the industry [18]. Group 5: Misconceptions About GEO - Brands focusing solely on short-term ROI may overlook the broader benefits of GEO in brand recognition and reach, risking the loss of valuable AI traffic opportunities [21]. - Misclassifying GEO as performance advertising can lead to misguided strategic decisions, potentially harming brand reputation and long-term growth [21]. - A short-term focus may disrupt the coherence of brand messaging, confusing consumers and undermining established brand positioning [21].

Core Insights - The education industry's traffic landscape is being transformed by the rise of AI platforms, with 300 million users turning to applications like DeepSeek, Doubao, and Yuanbao for educational information, marking a shift from traditional search methods to direct AI inquiries [1][2] - The concept of Generative Engine Optimization (GEO) is emerging as a new focus for educational institutions, replacing traditional SEO strategies [2][3] Industry Trends - As of March 2025, active users of AI-native apps reached 270 million, a year-on-year increase of 536.8%, with DeepSeek leading at 194 million monthly active users [1] - The education sector is cautious in adopting GEO, with many institutions still grappling with the fundamentals of AI SEO [3][4] Challenges Faced by Educational Institutions - Educational institutions are hesitant to invest in GEO due to concerns over ROI and the complexity of the decision-making process in education, which differs from faster-moving sectors like e-commerce [3][4] - There is a significant knowledge gap regarding the new search logic driven by AI, which complicates the ability of institutions to identify valuable keywords and scenarios [3][4] GEO Implementation Strategies - GEO differs from traditional SEO by focusing on how AI models understand and reference content, rather than just improving search engine rankings [5][6] - Effective GEO strategies include embedding clear brand tags, simulating user queries for training AI, and continuously monitoring generated results to refine content [5][6] Investment and Market Signals - The education sector is receiving attention from global capital, as evidenced by Profound's recent $35 million B round funding led by Sequoia Capital, indicating a shift towards AI-driven search optimization [7][8] - The high customer value and information density in education make it a natural fit for GEO, as users increasingly rely on AI for decision-making [8][9] Future Outlook - The competition in the education sector is shifting from traditional marketing channels to securing positions in AI-generated answers, emphasizing the importance of brand authority and information completeness [9][10] - The adoption of GEO in education may require a period of validation and understanding, but it has the potential to become a crucial component of brand building and customer acquisition strategies [10]

Core Viewpoint - The integration of advertising into AI search responses is increasingly prevalent, leading to concerns about user trust and the purity of information provided by AI systems [2][7][9]. Group 1: How Advertising Enters AI Search - Advertisers are subtly infiltrating AI search data sources, utilizing techniques like GEO (Generative Engine Optimization) to ensure their brands appear prominently in AI-generated answers [3][4]. - The process involves creating content filled with brand keywords and placing it on high-authority platforms, which AI systems then passively incorporate into their responses [3][6]. - Some advertisements are cleverly disguised as "recommended" or "selected" content, misleading users into believing they are receiving objective recommendations from AI [4][5]. Group 2: Impact on Users and AI Ecosystem - Users are increasingly finding themselves in an "advertising maze," where their quest for accurate information is interrupted by promotional content [9][10]. - The AI ecosystem faces significant challenges, as the commercialization of search results may lead to a return to traditional search engine practices, where the highest bidder receives the most visibility [10][11]. - The presence of misleading information can degrade the quality of AI responses, as even a small amount of false data can significantly impact the model's accuracy [11]. Group 3: Solutions for Balancing Commercial Interests and User Trust - Implementing clear labeling for advertisements within AI responses can help users distinguish between genuine information and promotional content [14][18]. - Establishing regulations that limit the proportion of advertising in AI responses and making the algorithms behind recommendations transparent can mitigate the issue [16][18]. - Regulatory measures, such as requiring significant labeling of AI-generated advertisements and tracking the advertising process through technology like blockchain, can enhance accountability [17][18].

Core Viewpoint - AI is transforming modern workplaces and daily life, shifting user behavior from "searching" to "asking AI" for solutions, leading to a significant increase in AI search users from 310 million in January 2024 to 1.98 billion by February 2025, a growth rate of 538.7% [1] Group 1: User Experience and Concerns - Users are increasingly questioning whether AI-generated answers contain advertisements, as seen in the experiences of individuals like Zhao Xinting, who noticed brand mentions in AI responses and expressed skepticism about their authenticity [1][4] - Social media platforms are filled with users voicing concerns that AI responses are becoming "advertising spaces," with examples of AI tools like DeepSeek and Doubao incorporating promotional content in their answers [5][9] Group 2: Marketing Opportunities - The rise of AI has created new marketing opportunities, particularly through Generative Engine Optimization (GEO), which aims to influence AI outputs by producing content that aligns with AI preferences, similar to traditional Search Engine Optimization (SEO) [10] - The GEO market is projected to grow significantly, with estimates suggesting a market size of approximately 2.1 billion yuan in 2023, expected to reach 24.2 billion yuan by 2027, indicating a potential market value transformation exceeding 300 billion yuan in the next five years [14] Group 3: Service Providers and Pricing - GEO service companies are emerging, offering services that optimize brand visibility in AI responses, with pricing models based on the number of keywords and entries, ranging from 6,000 yuan for 50 entries to 20,000 yuan for 500 entries per month [12][13] - The effectiveness of GEO services is measured by the frequency of brand mentions in AI responses, with some companies offering guarantees of performance or refunds if results are unsatisfactory [14]

Core Viewpoint - The rise of AI-driven marketing, specifically through Generative Engine Optimization (GEO), is reshaping how brands engage with consumers, shifting focus from traditional search engine optimization (SEO) to AI platforms [2][4][9]. Group 1: AI Marketing Dynamics - GEO is a new marketing strategy where companies create content tailored for AI to enhance brand visibility in AI-generated responses, similar to how SEO optimizes content for search engines [2][4]. - The popularity of AI tools like DeepSeek has led brands to seek increased exposure in AI responses, indicating a significant shift in marketing strategies post the rise of generative AI [4][6]. - Marketing companies are adapting by developing strategies to optimize content for AI, including creating derivative question libraries to enhance brand exposure [4][5]. Group 2: Market Trends and Shifts - The advertising revenue from traditional search engines is being challenged as user behavior shifts towards AI chat platforms, leading to a decline in market share for companies like Google and Baidu [8][9]. - Statcounter data shows Google's search engine market share fell below 90% in October 2022, while Baidu's share dropped from 69.63% in October 2023 to 50.92% by June 2024 [8]. - The emergence of GEO has led to a significant increase in demand for AI-related marketing services, with some companies reporting a 70% decrease in traditional SEO demand since 2020 [9][10]. Group 3: Challenges and Concerns - The integration of marketing content into AI responses raises concerns about the quality and reliability of information, as users may mistakenly trust AI-generated answers as authoritative [10][12]. - The current GEO landscape is characterized by a lack of standardized metrics for measuring effectiveness, leading to challenges in quantifying the impact of GEO strategies [11][12]. - There is a risk of content pollution in AI environments, as some marketing firms resort to producing low-quality or misleading content to increase brand visibility [12][13]. Group 4: Regulatory and Ethical Considerations - The distinction between GEO and traditional advertising is debated, with some industry experts arguing that GEO should be classified as advertising due to its intent to influence consumer behavior [14][15]. - Legal experts emphasize the need for compliance with advertising regulations, suggesting that brands using GEO should clearly label their content to avoid misleading consumers [15][16]. - The evolving relationship between AI and users raises new regulatory questions, particularly regarding the accuracy and integrity of AI-generated content [17][18].

Core Viewpoint - The article discusses the emergence of Generative Engine Optimization (GEO) as a new business model driven by AI, highlighting the challenges and opportunities it presents for brands and startups in the evolving digital landscape [3][4][25]. Group 1: Market Dynamics - Over 60% of consumers are now bypassing traditional search engines like Google and Baidu, opting to ask AI assistants directly for product information [3]. - The global AI search engine market is projected to reach $43.63 billion by 2025, with a compound annual growth rate (CAGR) of 14% from 2025 to 2032 [12]. - A report from Adobe indicates that traffic to U.S. business websites increased by 1200% from July 2024 to February 2025, largely driven by AI assistant referrals [11]. Group 2: Company Insights - Profound, a startup founded in 2024, has quickly gained traction, securing $20 million in funding and being adopted by thousands of marketers from Fortune 100 companies [3][10]. - Profound offers various services, including Answer Engine Insights and Agent Analytics, to help brands understand and optimize their presence in AI search engines [17][18]. - The company has processed over 100 million AI search queries monthly and operates in 18 countries, with early adopters reporting a 25%-40% increase in AI response volume within 60 days [23]. Group 3: Competitive Landscape - Other players in the GEO space include Daydream, which focuses on consumer shopping searches, and Goodie AI, which specializes in AI search visibility [13][14]. - Companies like Ahrefs, which transitioned from SEO to GEO, pose significant competition due to their established customer bases and expertise [14]. - The GEO model faces challenges as it relies heavily on understanding and adapting to the algorithms of large language models, which are subject to frequent changes [25][26]. Group 4: Challenges and Future Outlook - The GEO business model is seen as a "cat-and-mouse game," where startups must continuously adapt to changes in AI algorithms, which can render previous strategies ineffective [5][26]. - The effectiveness of GEO tools is often difficult to attribute, complicating budget decisions for brands [27]. - Despite the challenges, there is potential for GEO companies to evolve by expanding their service offerings and leveraging brand data to create long-term value [28].

Core Insights - The rise of AI assistants like ChatGPT is shifting consumer behavior, with over 60% of users bypassing traditional search engines like Google and Baidu for product inquiries [1] - Profound, a startup founded in 2024, has gained significant traction in the market by helping brands navigate AI-generated content and optimize their visibility in AI search engines [1][7] - The venture capital community is recognizing the potential of Generative Engine Optimization (GEO) as a new frontier, with predictions that it will reshape digital marketing strategies by 2025 [2][8] Company Overview - Profound has raised a total of $23.5 million in funding, with a seed round of $3.5 million in August 2024 and a Series A round of $20 million in June 2025 [7] - The company offers a range of services including Answer Engine Insights, Agent Analytics, and Conversation Explorer, aimed at enhancing brand visibility in AI search environments [14][20] - Profound's user base includes notable companies like Indeed and MongoDB, processing over 100 million AI search queries monthly as of June 2025 [20] Market Trends - The global AI search engine market is projected to reach $43.63 billion by 2025, with a compound annual growth rate (CAGR) of 14% from 2025 to 2032 [8] - The application layer of AI search is expected to dominate the market, accounting for 61.7% of the total share in 2025 [8] - The increasing use of AI search engines is reshaping consumer habits, with 39% of consumers having used AI search tools, indicating a significant shift in digital marketing dynamics [7] Competitive Landscape - Other emerging companies in the GEO space include Daydream, which focuses on consumer-oriented shopping searches, and Goodie AI, which specializes in AI search visibility [9][10] - Profound faces competition from established SEO companies like Ahrefs, which are transitioning to address the needs of the AI-driven market [10][12] - The GEO business model is characterized by a constant battle with evolving AI algorithms, making it essential for companies to adapt quickly to maintain relevance [22][24] Challenges and Opportunities - The GEO model presents inherent challenges, including the difficulty in attributing success to specific strategies due to the opaque nature of AI algorithms [23] - Companies in the GEO space must develop robust technical capabilities and maintain a competitive edge to capitalize on the growing demand for AI search optimization [24] - The potential for long-term value exists for GEO companies that can effectively accumulate brand data and transition into broader service offerings beyond just optimization [24]

Core Insights - Generative AI is transforming information retrieval paradigms, shifting user behavior from traditional "search-filter" to a conversational "ask-answer" interaction [1] - The launch of iPowerAI iGeo marks the introduction of the first domestically developed GEO model product driven by a cluster of ten AI agents, providing a comprehensive AI search optimization solution for brands [2] Group 1: Technological Challenges - The current GEO practices face significant technical challenges in bridging the gap between technology and marketing needs, including a lack of tailored solutions for vertical industries [1] - There is a superficial understanding of user intent, making it difficult to capture complex and dynamic search motivations [1] - The semantic gap across models leads to fragmented brand recognition across different AI engines [1] Group 2: Product Features - iPowerAI iGeo is the first product to feature an AI intent neural network, an AI visibility vector engine, and an automated brand value decoder [2] - The product establishes a closed-loop self-evolving technical system, offering a full-stack technical framework to address the core challenges of "collaboration-understanding-quantification" [2]