Several regions across China are advancing the deep integration of artificial intelligence with government administration to enhance the level of digital governance.
Recently, Shenzhen issued its first batch of application scenarios for AI in the government sector, targeting 2026. This initial list encompasses fifteen specific application areas spanning five major fields: decision support, government services, office administration, urban management, and public welfare services. It is reported that the annual plan involves releasing the list in three separate batches.
An expert in the field noted that the deep fusion of artificial intelligence with government functions is an inevitable trend in constructing a digital government. On the efficiency front, AI can handle repetitive administrative tasks, significantly improving service quality and speed. For decision-making, it enables predictive and precise analysis through the mining of vast data sets. Regarding service delivery, it facilitates the implementation of initiatives like "one-stop online services" and "intelligent approvals," offering personalized services and expanding the accessibility of public conveniences. In terms of governance, AI allows for real-time monitoring of urban operational data, shifting management from a reactive to a proactive, preventive approach and enhancing the refinement of governance.
The first batch released by Shenzhen is detailed across the five major fields with fifteen applications. For instance, the city's Emergency Management Bureau is utilizing technologies including large language models for natural language understanding, multi-modal spatial data intelligent fusion, and data mining with visualization. This effort aims to develop an AI agent for simulating disaster evolution trends, a smart model repository for experiential assets, and a digital human for intelligent graphical and textual explanations during simulations. The Shenzhen Water Authority is employing large language models, retrieval-augmented generation, and rule engine technologies to build a knowledge base covering water and soil conservation regulations, review essentials, and typical cases. Meanwhile, the Shenzhen Municipal Government Service and Data Administration is leveraging technologies like intelligent speech recognition, natural language understanding, and smart voice interaction. By deeply integrating these with a government service knowledge base, the administration aims to provide barrier-free, 24/7 voice consultation and response services.
A director from a smart city solutions company highlighted that artificial intelligence provides intelligent support for urban governance that is perceivable, analyzable, dispatchable, and traceable. For example, the integration of AI with emergency and safety management supports regulatory bodies in gaining real-time awareness of risk situations, accurately identifying key hazards, and reducing redundant inspections, thereby shifting the focus from "post-incident handling" to "preventive measures."
Since the beginning of this year, various localities nationwide have continued to intensify efforts in "AI + government services," consistently elevating the level of digital, intelligent governance and service provision. For example, the Administrative Examination and Approval Service Bureau of Yinchuan City previously released its first 2026 batch of "AI + Government Services" application scenarios and simultaneously launched a government AI assistant named "Yin Xiaofu." This list covers nine intelligent application scenarios across three main areas: intelligent guidance, intelligent approval, and intelligent performance evaluation.
Experts point out that artificial intelligence unleashes comprehensive, multi-layered benefits for digital government construction. It can substantially enhance the convenience of handling affairs, optimize the scientific basis of policy formulation, and strengthen capabilities in urban governance areas such as risk early warning and traffic management efficiency.
Looking ahead, the application scenarios for AI in government services across different regions are expected to expand into more directions. A chief expert in the intelligent economy noted that future government AI practices will likely form three differentiated pathways based on a city's functional level, industrial foundation, and governance needs, promoting development in a layered, staggered, and focused manner. Concurrently, regions will also prioritize security, establishing "safety fences" for government large language models to balance intelligent empowerment with the security of government information.
Comments