Report information

• Title: Generative Artificial Intelligence Application Development Report (2025)
• Issuing agency: China Internet Network Information Center (CNNIC)
• Release Date: October 2025
• Original link: [Generative Artificial Intelligence Application Development Report (2025)] (https://www.cnnic.cn/n4/2025/0828/c167-11110.html) (Note: This is CNNIC’s typical reporting path, please refer to the official website for details)
• Core Content: Based on the framework of “User Popularization-Industrial Development-Typical Applications-Development Environment”, analyze the development status and future prospects of generative AI.

Comprehensive overview and summary of the report

This report records in detail the explosive growth of generative artificial intelligence (GenAI) in 2025, especially the rapid popularity and technological iteration of the Chinese market.

1. Development characteristics: domestic achievements and efficiency breakthroughs

• Scale Explosion: As of June 2025, the number of GenAI users in China reached 515 million, with a penetration rate of 36.5%.
• The Rise of DeepSeek: DeepSeek-R1 achieves excellent performance at less than 1/10 the cost of similar models, breaking the “computing power determinism” and topping the application list in 140 countries around the world.
• Technical Trends: Logical reasoning capabilities have been significantly improved, multi-modal (Venture Video, Tusheng Audio) has developed by leaps and bounds, reasoning costs have been significantly reduced, and lightweight models (device-side AI) empower more terminal devices.

2. User popularity

• Market structure: Doubao and DeepSeek occupy the leading position in the market.
• Application motivation: Mainly used for answering questions (80.9%), text processing (36.0%) and audio and video generation (33.0%).
• Group Characteristics: Young and middle-aged users are the main force, with users aged 19 and under accounting for 33.8%, showing the young generation’s high acceptance of AI technology.

3. Typical application scenarios

• Industry and Agriculture: From smart irrigation, precision agriculture to industrial robots (such as UBTECH Walker S1) in production line training, AI is reshaping the labor structure.
• Life Services:
  • Smart Search: Shift from “finding links” to “getting answers”, Search as a Service.
  • Content Creation: Sora and Keling AI bring short drama and advertising production into the era of “second-level generation”.
  • Office Assistant: AI code generation (more than 30% of new code is generated by AI) and intelligent document processing become the norm.

4. Development environment and prospects

• Policy Support: Establish an artificial intelligence security governance framework and promote “artificial intelligence +” actions.
• Future Trends: Agent has autonomous decision-making and execution capabilities, Embodied Intelligence allows robots to enter the physical world and interact, Scientific Research (AI for Science) accelerates lunar research and weather prediction.

My understanding

This report is not only a accumulation of technical data, but also reveals the paradigm shift of AI technology from “concept laboratory” to “full employee productivity”.

1. Implications for personal research fields (political work and assistant behavior)

The report pointed out that 80.9% of users’ primary need is to “answer questions”, and in the office assistant scenario, AI’s understanding and polishing capabilities have become the core. For my study of Legislative Assistants’ Use of Generative AI, this provides strong external validity:

• Efficiency Liberated: Political assistants are faced with the collection of data on a large number of public issues and the preparation of press releases. The high usage of AI search and document processing indicates that there will be an “automated revolution” in political work processes.
• Decision Assistance: The “improvement in reasoning capabilities” mentioned in the report means that the assistant will not only use AI to write drafts in the future, but may also use AI to conduct policy impact assessment and voter sentiment analysis.

2. Inspiration for the development of AI in Taiwan and cross-strait

• Lessons from cost advantages: The success of DeepSeek shows that Taiwan, with limited computing resources, should focus on algorithm optimization and deep cultivation of specific vertical fields (Vertical AI) instead of simply pursuing parameter scale.
• Complementarity of application scenarios: Mainland China has a large scale of industrial and agricultural applications, while Taiwan has advantages in semiconductor end-side AI and high-quality service trade. Both sides of the Taiwan Strait face common challenges in AI governance (such as copyright, data privacy), and there is room for cross-regional dialogue.

3. Thoughts on the direction of academic research

• From “use” to “collaboration”: Future academic research should not only focus on whether assistants use AI, but should study how the “human-machine collaboration model” changes the power structure in the political field.
• Update of Technology Acceptance Model: The traditional TAM model may not be enough to explain the changes brought about by Agentic workflow. Research needs to focus on users’ psychological boundaries and ethical trust in AI “autonomy”.

Conclusion

The “2025 Report” marks that AI has entered the “full-scenario penetration” stage from a single breakthrough. As researchers, we need to pay close attention to the dynamic balance between the “efficiency dividend” and “ethical risks” brought by AI, especially in the highly sensitive field of political work.