…Qapqal Xibe Autonomous County held a special training session on DeepSeek Localized Service Capability Training… to thoroughly implement the national Digital China strategy…
…察布查尔县举办DeepSeek本地化服务能力培训… 专题培训，深入贯彻落实国家数字中国战略…
Guan Hanyu, “Qapqal Xibe Autonomous County Holds Special Training Session on ‘DeepSeek Localized Service Capability Training: Empowering Government Affairs and Serving the People’s Livelihood,'” China.com, March 12, 2025
Milestone Summary
What happened: In March 2025, Qapqal Xibe Autonomous County in Xinjiang conducted a formal DeepSeek training session for local Party-state personnel. The training focused on using large language models in government affairs, public services, social governance, and People’s Livelihood functions.
Why it matters: The event provides concrete evidence that Digital China’s AI ambitions were reaching county-level institutions, including a remote border region, through organized training and preparations for local application.
Strategic function: Connects national Digital China objectives with grassroots administrative modernization, demonstrating how AI capabilities are being introduced into local governance systems.
Systemic significance: Illustrates the role of state-owned technology enterprises, local Party-state organizations, and coordinated training in translating AI innovation into government capabilities.
Long-term signal: AI is becoming an increasingly important instrument of Party-state governance. The significance lies not simply in model performance but in China’s capacity to integrate intelligent systems into administrative and social-governance processes at scale.
Author’s Note: For a full translation of the China.com report and a closer examination of the Qapqal Xibe training session, see DeepSeek Builds Digital China, Right to the Kazakhstan Border.
The Development
In March 2025, Qapqal Xibe Autonomous County in Xinjiang, located along China’s border with Kazakhstan, held a formal training session on the localized deployment of DeepSeek, a Chinese-developed large language model. The stated purpose was explicit: to support implementation of the national Digital China strategy and associated regional work plans.
Participants were trained on applying AI tools to government services, public administration, social governance, and “People’s Livelihood” domains, including healthcare, education, employment, and housing. The session emphasized improving administrative efficiency, optimizing service delivery, and advancing digital transformation at the county level.
The training was delivered by an artificial intelligence R&D expert from China Unicom, underscoring the role of state-owned technology firms in deploying AI capabilities within government systems. In closing remarks, a senior county Party official urged participants to seize the “policy dividends” of Digital China and accelerate the adoption of AI tools, invoking a now-standard governance principle: “The people should run less errands and run more data.”
On its face, this appears to be a routine local training session. In reality, it reveals something far more significant.
From Technology to Governance Infrastructure
This development signals a transition in how artificial intelligence is being positioned within China’s strategic system. DeepSeek is no longer being treated solely as a standalone productivity tool or experimental application. Local Party-state institutions are actively preparing to incorporate large language models into administrative processes, public service delivery, and grassroots governance. The Qapqal training session provides a concrete illustration of that transition, even if it does not by itself establish the extent of operational deployment.
This distinction is critical. It marks the shift from viewing large language models as technological innovations to treating them as components of governance infrastructure. In this context, AI is no longer confined to research labs or commercial platforms. It is becoming part of the institutional machinery through which the state exercises administrative capacity, delivers services, and manages society.
Digital China Reaches the Grassroots
The location of this initiative is as important as the technology itself. Xinjiang has long served as a testing ground for new models of digital governance, particularly in areas related to social management and public security. The extension of AI-enabled governance tools into county-level institutions in this region suggests that Digital China is no longer operating primarily at the level of national architecture or major urban pilots. Instead, it is being systematically extended downward into the “last mile” of governance.
This reflects a broader pattern in China’s digital strategy: the integration of advanced technologies into a vertically integrated system that connects central policy design with local implementation. The Qapqal training session demonstrates that efforts to introduce large language models into local governance now extend to county-level institutions in a remote border region. It provides an early indication of how Digital China’s national AI ambitions are being translated into local administrative practice.
System Competition: From Models to Systems
This development also carries implications beyond China. Much of the global discourse on artificial intelligence remains focused on model performance: benchmarks, capabilities, and competition between leading firms. China’s approach, as reflected in this milestone, suggests a different axis of competition. The central question is not only who builds the most advanced models, but who can integrate those models into functioning, large-scale systems.
In China’s case, the answer increasingly lies in the ability to embed AI within a state-coordinated architecture that links data, computing power, platforms, and governance institutions into a unified system. This approach transforms AI from a discrete technology into a multiplier of state capacity.
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