人工智能生成，广告的技术演进与模式变革 人工智能，尤其是以大语言模型和多模态模型为代表的生成式智能，正在全球范围内重塑广告系统的底 层逻辑。当前，数字广告技术已经从上一代的程序化广告推荐系统，向能够理解用户意图、分析用户情 感和行为的智能广告系统演进。广告不再仅是页面中的插图或文字，逐步演化为由人工智能"理解用户 需求、生成内容、决定投放"的完整闭环。不仅如此，生成式智能技术在广告创意生成、智能投放、智 能审核等环节都有广泛应用。以谷歌为例，2025年I/O大会[ I/O大会（Innovatio n in t he Open）即Google 开发者大会，于2025年8月13日召开，聚焦 Google 创新技术，Android、AI、web、cloud 等领域最新动 态。]上发布的"AI模式"将Gemini模型深度嵌入搜索、推荐与广告生成流程中，展示了广告从"被动呈 现"到"主动交互"的彻底转变。腾讯AI广告创意平台——"妙思"借自主研发的混元大模型打通创意制 作、投放流程与广告审核多个环节。 广告的投放逻辑发生质变。如在跨境电商广告投放中，生成式智能技术已被广泛应用于人群洞察、素材 生成与多平台投放策略优化， ...

Core Viewpoint - The article discusses how generative artificial intelligence (AI) is transforming the advertising industry by evolving from traditional advertising methods to intelligent systems that understand user intent and behavior, thereby creating a complete feedback loop in advertising processes [3][4][5]. Group 1: Evolution of Advertising Technology - Generative AI is reshaping the underlying logic of advertising systems globally, moving from programmatic advertising to intelligent systems that can analyze user emotions and behaviors [3]. - The integration of AI in advertising processes, such as content generation and intelligent auditing, is becoming widespread, as seen in platforms like Google's Gemini model and Tencent's "Miao Si" [3][4]. - The advertising logic has fundamentally changed, with generative AI enhancing precision and efficiency in cross-border e-commerce advertising through insights and automated content generation [4][6]. Group 2: Advertising Mechanisms and User Experience - The rise of AI assistants is diversifying advertising entry points, moving away from traditional app-centric models to AI-driven interactions [7]. - Generative AI significantly boosts the efficiency of ad material production, allowing for real-time understanding of user intent and enhancing the effectiveness of supply-demand conversion [8]. - The goal of achieving "one person, a thousand faces" in advertising is becoming feasible, as AI can generate personalized content based on individual user contexts and preferences [9]. Group 3: Transformation of Advertising Agencies - AI is replacing repetitive tasks in advertising agencies, prompting a shift towards higher-value activities such as consumer insights and creative strategy [11]. - New roles are emerging within advertising agencies, such as "model optimizers" and "intelligent material arrangers," reflecting the industry's adaptation to AI technologies [11][12]. - The collaboration between AI and human creativity is evolving, with AI acting as a real-time collaborator in the creative process [12]. Group 4: Regulatory and Governance Challenges - The rapid adoption of AI in advertising raises governance challenges, including the need for a new regulatory framework that balances innovation and risk management [20][21]. - Issues such as algorithmic bias, data privacy, and the need for transparency in AI-generated content are critical concerns for the industry [13][15][17]. - The complexity of cross-border advertising compliance and cultural adaptation presents additional challenges for brands leveraging AI in global markets [18][19]. Group 5: Strategies for Addressing Challenges - Companies are encouraged to explore a "light regulation + co-governance" model to foster innovation while managing risks associated with AI in advertising [22]. - Platforms should enhance their risk control mechanisms by investing in algorithm optimization and ensuring compliance with advertising standards [23]. - Brands are advised to develop their own intelligent systems to maintain consistency in content generation while leveraging AI's efficiency [26].

Core Viewpoint - The article emphasizes that artificial intelligence (AI) is transforming the advertising industry from a "one-size-fits-all" approach to a highly personalized "one-to-one" advertising model, driven by AI's capabilities in understanding user intent and context [4][5][6]. Group 1: AI's Impact on Advertising - AI is evolving from a tool for content production to a core driver of industry growth, reshaping the advertising landscape [4]. - Major platforms like Google, Meta, Tencent, and Kuaishou are actively integrating AI into their advertising processes, enhancing creative production and intelligent ad placement [5]. - The shift from "computational advertising" to "intelligent advertising" is establishing a new infrastructure that allows for deeper understanding of user needs and real-time context [6][9]. Group 2: Intelligent Advertising Infrastructure - The new intelligent advertising infrastructure is built on three pillars: multimodal large models, reasoning engines, and intelligent agent collaboration protocols [9][11]. - Multimodal models enable the understanding of various content types, allowing for dynamic ad generation based on real-time user context [9]. - The reasoning engine enhances AI's ability to plan and execute marketing strategies across the entire customer journey [9]. Group 3: Evolution of AI Agents - AI agents are transitioning from single-function tools to comprehensive "super agents" capable of managing the entire marketing process autonomously [11][12]. - These agents will consist of specialized AI roles that collaborate to optimize advertising strategies, reducing the need for human intervention to high-level oversight [12]. - The interaction between users and ads is being redefined, with AI agents acting as knowledgeable sales consultants that provide personalized recommendations [12][14]. Group 4: Personalization in Advertising - The advertising matching paradigm is shifting from "thousands of faces for thousands of people" to "thousands of faces for one person," focusing on real-time, context-aware ad generation [14][15]. - This transformation allows ads to become more relevant and timely, enhancing user experience by addressing immediate needs rather than relying on past behaviors [15]. Group 5: Industry Transformation and Collaboration - The advertising industry is experiencing a shift towards human-AI collaboration, with platforms enhancing their capabilities and agencies transitioning to more strategic roles [16][18]. - Advertisers are now empowered to build their own intelligent systems, benefiting from the democratization of AI tools [16]. - The demand for talent is evolving, with a focus on strategic creative individuals who can leverage AI and data insights [18]. Group 6: Ethical Considerations and Future Outlook - While AI brings efficiency and scale, the importance of human creativity, emotional resonance, and trust remains paramount in advertising [20]. - The article calls for a balanced approach to AI integration, ensuring that ethical standards and authenticity are maintained in the advertising ecosystem [20].

Core Insights - The article discusses the transformative impact of artificial intelligence (AI) on the advertising industry, marking a shift from traditional methods to a new era of intelligent advertising driven by AI technologies [1][2][5]. Group 1: AI's Role in Advertising - AI is evolving from a supportive tool to a core productivity driver in digital advertising, enhancing efficiency in creative production and intelligent ad placement [2][5]. - The emergence of generative AI is reshaping the advertising landscape, enabling real-time understanding of user intent and context, thus facilitating a transition from keyword matching to intent comprehension [11][14]. - The report highlights a shift from "mass advertising" to "personalized advertising," where ads are dynamically generated based on real-time user context rather than static user profiles [11][12]. Group 2: Infrastructure and Collaboration - The foundation of intelligent advertising is built on multi-modal large models that can comprehend various forms of content, allowing for a more nuanced understanding of consumer behavior [5][6]. - AI agents are expected to evolve from single-function tools to comprehensive "super agents" that manage the entire marketing process autonomously, from strategy formulation to execution [8][9]. - The collaboration between AI agents will redefine the advertising workflow, enabling virtual teams of specialized AI to work together, enhancing efficiency and effectiveness in marketing campaigns [6][8]. Group 3: Industry Transformation - The advertising industry is witnessing a shift in roles, with agencies transitioning from labor-intensive models to intelligence-driven strategies, focusing on AI integration and strategic insights [14][18]. - Advertisers are now empowered to build their own AI systems, allowing for greater control and customization in their marketing efforts, particularly benefiting small and medium enterprises [14][18]. - The demand for talent is changing, with a focus on individuals who can leverage AI, understand data, and provide unique insights, moving away from traditional execution roles [14][18].

Core Insights - The article emphasizes that artificial intelligence (AI) is transforming the advertising industry from a "one-size-fits-all" approach to a more personalized "one-to-one" advertising model, driven by AI capabilities [1][3][8]. Group 1: AI's Impact on Advertising - AI is evolving from a supportive tool to a core productivity driver in digital advertising, enhancing creative production and intelligent deployment [2][3]. - The shift from "computational advertising" to "intelligent advertising" is being facilitated by a new infrastructure based on multi-modal large models that can understand various forms of content [3][10]. - The emergence of AI agents is reshaping product and service models in advertising, transitioning from single-point tools to comprehensive, end-to-end solutions [6][10]. Group 2: Personalization and User Interaction - The advertising matching paradigm is shifting from "thousands of faces" to "one face for each person," allowing for dynamic ad generation based on real-time user context [8][10]. - AI agents will enhance user interaction with advertisements, transforming static ad experiences into personalized, conversational engagements [6][8]. Group 3: Industry Transformation and Collaboration - The advertising industry is experiencing a fundamental restructuring, with a shift towards human-AI collaboration, where AI handles repetitive tasks while humans focus on strategic oversight [10][11]. - The demand for talent is changing, with a focus on strategy-oriented creative professionals who can leverage AI and data insights [11][13]. - The article highlights the need for governance and innovation to address challenges related to content authenticity and regulatory compliance in the AI-driven advertising landscape [11][13].