A Multi-Case Qualitative Study on the Strategic Socio-Industrial Integration of AI: Insights from China
คำสำคัญ:
Artificial Intelligence, Socio-Industrial Integration, Strategic Development, Multi-Case Studyบทคัดย่อ
This qualitative study explores the technological trajectory and socio-industrial integration of artificial intelligence (AI) in China, addressing the question: How has AI evolved from conceptual research to widespread industrial application? Using a multi-case design, we purposefully selected four sectors—generative AI, computer vision and audition, intelligent connected vehicles and intelligent robotics for analysis. Cross-case analysis is also conducted in the fields of business, news and research. Data drawn from academic literature, industry reports, and policy documents were examined through thematic analysis. Typical and representative cases in the sectors were selected to analyze.
The findings chart AI's progression toward greater multimodal capability and its concurrent penetration into diverse economic sectors. The study’s primary contribution is its systematic, cross-case synthesis of China's application-driven AI development model, revealing both its transformative potential and persistent challenges. The paper concludes that future progress will hinge on pursuing both advanced general intelligence and deeper, more equitable socio-economic integration.
เอกสารอ้างอิง
Amodei, D., Anantha, S., Manubhai, R., Bai, J., Battenberg, E., Case, C., Casper, J., Catanzaro, B., Cheng, Q., Chen, G., Chen, J., Chen, J., Chen, Z., Chrzanowski, M., Coates, A., Diamox, G., Ding, K., Du, N., Elsen, E., Zhu, Z. (2016). Deep Speech 2: End-to-End Speech Recognition in English and Mandarin. Proceedings of the 33rd International Conference on Machine Learning, 48, 173–182.
Cai, W. (2024). Optimization Engine to Enable Edge Deployment of Deep Learning Models. The ITEA Journal of Test and Evaluation, 45(2).
Canny, J. (1986). A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(6), 679–698.
Cao, S. Jiang, W. Wang, J. Yang, B. (2024). From Man vs. Machine to Man + Machine: The art and AI of stock analyses, Journal of Financial Economics,160,103910,
Durrant-Whyte, H., & Bailey, T. (2006). Simultaneous Localization and Mapping (SLAM): Part I. IEEE Robotics & Automation Magazine, 13(2), 99–110.
Hu, J. B. (2024). Creating a virtual host for livelihood programs to enable sustainable innovation in business processes: Jiaxing News Media Center vigorously promotes the integration and transformation of "AI + media". Media Review, (10),16–18.
Huang, Y. C., Zheng, Y. J., & Huang, G. D. (2025). Exploring the integration of artificial intelligence and natural language processing. Wisdom China, (04), 74-75.
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). ImageNet Classification with Deep Convolutional Neural Networks. Advances in Neural Information Processing Systems, 25.
Li, H., Su, L. N., Zhou, H. X., Li, S. S., Wang, M. T., Xie, B. Y., & Liu, G. Y. (2026). Research and countermeasure suggestions on the use of artificial intelligence policies in Chinese scientific journals: An NVivo analysis based on 40 core scientific journal policy texts. Science-Technology & Publication, 1-11.
Lowe, D. G. (1999). Object Recognition from Local Scale-Invariant Features. Proceedings of the Seventh IEEE International Conference on Computer Vision (Vol. 2, pp. 1150–1157).
McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955. AI Magazine, 27(4), 12.
Oord, A. van den, Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., Senior, A., & Kavukcuoglu, K. (2016). WaveNet: A Generative Model for Raw Audio. ArXiv preprint arXiv:1609.03499.
Pan, J. F. (2024). Artificial intelligence is triggering an intelligence revolution. Financial Think Tank, 9(3), 79–96+142.
Peng, F. (2024). Analysis of problems and countermeasures in the intelligent management of commercial bank accounting. China Market, (27), 139–142.
Penman, S. H. (2014). Accounting for Value. Columbia University Press.
Qian, G. M., Yang, Z., & Shi, L. (2025). Reshaping the AI large model industry policy system: U.S. experience and China's path. Technology Economics, 44(01), 14-27.
Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2018). Improving Language Understanding by Generative Pre-Training. OpenAI.
Shang, X. (2024). The three major engines of artificial intelligence development: Algorithm, computing power, and data. Commercial Culture, (17), 34–35.
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., Dieleman, S., Grewe, D., Nham, J., Kalchbrenner, N., Sutskever, I., Lillicrap, T., Leach, M., Kavukcuoglu, K., … Hassabis, D. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587), 484–489.
Tian, Z. N. (2024). Research on the development strategy of the entire low-altitude economy industry chain in the Guangzhou-Shenzhen region. China Journal of Commerce, 33(16), 108–113.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is all you need. Proceedings of the 31st International Conference on Neural Information Processing Systems, NIPS’17, 6000–6010.
Wang, X. N., Li, J. H., & Zhai, Y. (2023). Analysis of the development environment of China's intelligent vehicle industry. Automotive Industry Research, (4), 8–10.
Xu, C. S. (2023). The current situation and future development direction of ChatGPT and generative artificial intelligence. Bulletin of National Natural Science Foundation of China, 37(5), 743–750.
Yan, X., & Ren, B. (2025). Global competition drives differentiated development of China's AI chips. Enterprise Management, (07), 11-15.
Yang, X. (2019). A review of research on power equipment condition monitoring based on computational auditory scene analysis technology. Guangdong Electric Power, 32(9), 24–32.
Yi, Z. (2024). Application of UAV aerial survey technology in the South Open-pit Coal Mine of Xinjiang Tian Chi Energy. Opencast Mining Technology, 39(5), 22–25.
Zhang, X. (2025). Policy-led AI empowerment: Co-creating a new intelligent manufacturing ecosystem. Modern Manufacturing, (09), 3.
Zhang, Y. (2026). Administrative liability pathways for harm caused by algorithmic decision-making in automated administration. Administrative Law Review, 1-13.
Zhao, C. C. (2025). A study on the relevance and regional differences of China's artificial intelligence policies. World Scientific Research and Development, 47(02), 247-259.
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