研究内容 本报告深度解析中国互联网媒体行业的现状、AI赋能下的技术突破与转型路径，系统阐述生成式AI技术如何重构互联网媒体内容生态全链路，并提炼技术赋能下的实践成果 与行业价值。 发展概况 ：当前中国互联网媒体行业正迈向AI赋能的智能生态融合阶段。当前用户增长趋缓，竞争转向存量市场。生成式AI加速多模态融合应用，重构内容生态与用户体 验，驱动行业向质量效率转型。 深度赋能 ：AI技术深度赋能互联网媒体行业，推动全链条智能化转型。在生产、审核、分发、消费侧重构媒体生态，驱动行业从信息中介转向智能服务枢纽，实现内容质效 升级与商业模式创新，加速产业价值跃迁。 AI+互联网媒体行业 丨研究报告 前言： 研究意义 在AI技术加速重构传播生态的进程中，AI赋能已成为驱动互联网媒体产业升级的核心引擎。随着用户需求多元化与媒介形态迭代加速，内容生产者不仅需要应对创作效率、 分发精准度等传统挑战，还需在生成式AI驱动的智能时代重塑内容生态。多模态大模型、深度推理算法等技术的突破，正深刻变革互联网媒体的内容生产范式、传播路径和 商业模式。 在此背景下，本次研究聚焦生成式AI技术对互联网媒体全链路的深度赋能，以及标杆平台在智能化 ...

Core Viewpoint - The article emphasizes that AI technology is fundamentally transforming the internet media industry by enhancing content production, distribution, and consumption processes, leading to a more efficient and innovative media ecosystem [1][2][3]. Group 1: Industry Overview - The Chinese internet media industry is entering a phase of AI-enabled intelligent ecosystem integration, with user growth slowing and competition shifting to existing markets [2][6]. - The industry is experiencing a transition from information intermediaries to intelligent service hubs, driven by AI technology that enhances content quality and efficiency [2][3]. Group 2: AI Empowerment in Content Production - Generative AI is reshaping the content production landscape by breaking down professional barriers and enabling users to create diverse content forms from simple text prompts [24]. - The trend of mass content creation is highlighted, with the potential for all 1.1 billion internet users in China to participate in multi-modal content creation [24] . Group 3: AI Empowerment in Content Review - Generative AI technology is innovating content review systems through automated screening, precise judgment, human-machine collaboration, and dynamic strategies [26]. - AI enhances the efficiency and accuracy of content review processes, allowing for real-time adaptation to new types of violations [26]. Group 4: AI Empowerment in Content Distribution and Platform Operations - AI technology improves content distribution efficiency by analyzing user behavior and optimizing recommendation paths, thus enhancing user experience and engagement [28]. - The integration of AI in platform operations allows for better resource allocation, reduced operational costs, and the creation of new business models [28]. Group 5: AI Empowerment in Content Consumption - The shift from one-way communication to interactive engagement is facilitated by generative AI, allowing consumers to become co-creators in the content cycle [31]. - AI technologies lower barriers to information access and enhance user understanding through intelligent summarization and dialogue-based services [31]. Group 6: Challenges in the AI Era - The rise of generative AI raises concerns about content authenticity, necessitating stronger review and regulatory frameworks [46]. - AI video generation faces limitations in physical logic consistency and character identity coherence, posing challenges for commercial applications [49]. - High technical costs create significant entry barriers, leading to a competitive landscape dominated by large players [51]. - Privacy and security issues arise from the use of vast user data, prompting the need for robust governance frameworks to protect user trust [54]. Group 7: Case Studies of AI Implementation - The People's Daily utilizes generative AI to enhance video content creation and streamline the media production process [36]. - The Paper integrates AI tools across its operations to improve content production efficiency and ensure content safety through advanced review mechanisms [38]. - Douyin embeds AIGC technology throughout its content lifecycle, creating a comprehensive ecosystem for content creation and monetization [40]. - Weibo employs its self-developed multi-modal model to enhance its content ecosystem, supporting a full chain of AI services from production to consumption [42].