During the 2025 World Artificial Intelligence Conference, the State-owned Assets Supervision and Administration Commission (SASAC) of the State Council officially released the first batch of 40 strategic, high-value AI scenarios for central enterprises at the "AI Revitalizes Industries for Win-Win Cooperation" Enterprise Artificial Intelligence Industry Development Forum. The SASAC is building a "Strategic, High-Value AI Scenario Library for State-owned Central Enterprises." Leveraging the advantages of central enterprises' large-scale demand, comprehensive industrial support, and diverse application scenarios, and guided by the principles of "strong strategic significance, high economic returns, and close relevance to people's livelihoods," SASAC is leveraging the power of central enterprises to accelerate the exploration and implementation of these scenarios. By adhering to application-driven initiatives, strengthening open collaboration and cooperation, and accelerating "application-driven" initiatives to empower AI across a wide range of industries, SASAC will further promote the "AI+" initiative for central enterprises, adhere to self-reliance and self-improvement, and emphasize application-oriented approaches to promote the healthy and orderly development of AI in China in a beneficial, safe, and equitable direction. Based on the "Strategic High-Value Scenario Library of Artificial Intelligence for State-owned Central Enterprises", we will encourage central enterprises to continuously explore and actively open up core industry scenarios, coordinate with all parties to build and share, deeply integrate artificial intelligence technological innovation and industrial innovation, and create application benchmarks such as artificial intelligence + science, biomedicine, new materials research and development, embodied intelligence, and new industrialization. We will help traditional industries upgrade their quality, open up new tracks for the development of strategic emerging industries and future industries, and promote the "bonsai-style" pilot to "rainforest-style" large-scale application.