广电绝地反击！揭秘多彩新媒「不烧钱」的AI生存法则

Core Insights - The traditional broadcasting industry is facing a profound survival crisis due to increasing external competition, with smart voice device penetration exceeding 68% and short video platforms occupying an average of 2.8 hours of user time daily, leading to a structural shift in user attention [1] - The average ARPU for provincial IPTV users is projected to be below 15 yuan in 2024, a 22% decline compared to three years ago, indicating a significant revenue drop [1] - The essence of user loss and revenue decline stems from the traditional broadcasting service model's inability to meet new user demands for television [1] - National policies are increasingly supportive of the broadcasting industry's intelligent transformation, emphasizing media integration and digital cultural strategies [1] Strategic Choices - The company has chosen to abandon a "big and comprehensive" approach, focusing instead on three core areas to address current challenges: maintaining "entry rights," enhancing "service value," and seeking "new growth" through AIGC tools [4][5] - This pragmatic strategy reflects a typical mindset of budget-constrained operators, prioritizing core business stability while exploring key areas with controlled investments [5] Technical Path - The technical implementation emphasizes a layered architecture and "lightweight" practices, integrating mature external capabilities rather than building a complete AI system from scratch [7] - The architecture focuses on core needs of IPTV, including safety, service, and efficiency, with plans to utilize lightweight models to control costs and develop industry-specific AI models [7] Scene Implementation - The AI practices of the company will be evaluated based on specific scene implementations, focusing on internal efficiency, user service upgrades, and ecosystem expansion [9] - Internally, the company plans to enhance content production efficiency through tools like intelligent posters and coding, aiming for full-process automation [10] - User experience will shift from passive viewing to active usage, with features like natural language commands for content search and tailored services for specific demographics [12][15] Ecosystem Collaboration - The company emphasizes an "internal and external linkage" strategy for ecosystem building, leveraging external resources to quickly establish service capabilities [20] - The approach includes collaborating with major content providers and integrating local services to enhance user engagement and service diversity [20] Value Outlook - The AI transformation is expected to yield not only direct commercial returns but also serve as a practical reference for other industry players, with plans to accumulate valuable data assets for future growth [22] - The initiative aims to establish new standards for intelligent broadcasting, facilitating a shift from content distribution to service operation across local broadcasting entities [22] Conclusion - The intelligent transformation of the broadcasting industry is a systemic change focused on redefining survival space and value, with the company's approach providing a pragmatic path for regional operators seeking to adapt [23][25]