Practical Approaches and Development Strategies for Enhancing Local Industrial Capabilities through AI Empowerment - Gao, Jia; Qiang, Guanglei; Zhu, Lihua (Scientific Journal of Technology, 2026)
In the era of the digital economy, Artificial Intelligence (AI), as the core driving force of the new generation of information technology, has become a key support for promoting the transformation and upgrading of local industries and enhancing industrial core competitiveness. Currently, local industries in China are facing development bottlenecks such as homogeneous competition, low-end locking of industrial chains, insufficient innovation capability, and relatively low production efficiency. The deep integration of AI technology can effectively address these industrial development pain points and drive local industries toward intelligent, high-end, and green transformation. This article, based on the practical development of local industries, avoids experimental verification, dataset analysis, and review-style writing patterns, focusing instead on the practical logic, core pathways, and safeguarding strategies for AI to empower the capability enhancement of local industries. By combining typical local industry application scenarios, it clarifies AI's empowerment pathways in key fields such as agriculture, industry, and services. Through the use of charts to present key content, it provides actionable practical references for local governments and enterprises to promote deep integration of AI and industry and to enhance comprehensive industrial capabilities, thereby supporting high-quality local economic development. The AI empowerment practices of China's local industries summarized in this paper provide a reference model for the digital transformation of regional industries in emerging economies and offer a Chinese example for the global integration of digital technology and the real economy.