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AI-Enabled Cadre Education and Training: Policy Evolution Pathways and Latest Practices in China

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DOI: 10.23977/socsam.2026.070101 | Downloads: 1 | Views: 35

Author(s)

Luona Gan 1

Affiliation(s)

1 Chinese Academy of Personal Science, Beijing, 100101, China

Corresponding Author

Luona Gan

ABSTRACT

Under the background of merging new technologies into government governance, artificial intelligence is gradually embedded in the governance system and has a positive impact on government training in the public sector. Meanwhile, the relevant policies show obvious characteristics of phased evolution. This paper focuses on China’s policies for AI-enabled cadre education and training, and systematically traces their evolution over the past decade. First, the policy evolution is divided into two stages, including an initial stage of strategic positioning and a subsequent stage of systematic advancement. Then, the characteristics of these policy changes are analyzed in three aspects, i.e., from technology advocacy to governance needs, from macro policy to system promotion and construction, and from general education training to specific capability improvement. Finally, three regions, including Zhejiang Province, Shenzhen City and Yangzhou City, are selected to explain how AI can enable cadre education and training in the latest practices.

KEYWORDS

AI, Cadre Education and Training, Policy Evolution Pathways, Latest Practices

CITE THIS PAPER

Luona Gan, AI-Enabled Cadre Education and Training: Policy Evolution Pathways and Latest Practices in China. Social Security and Administration Management (2026) Vol. 7: 1-7. DOI: http://dx.doi.org/10.23977/socsam.2026.070101.

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