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].