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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">LNE</journal-id><journal-title-group><journal-title>Lecture Notes in Education, Arts, Management and Social Science</journal-title></journal-title-group><issn>TBA</issn><eissn>2705-053X</eissn><publisher><publisher-name>WHIOCE PUBLISHING PTE. LTD.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18063/LNE.v3i10.1162</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Artificial Intelligence Empowering County-Level Statistical Analysis: Practical Exploration and Development Paths</title><url>https://artdesignp.com/journal/LNE/3/10/10.18063/LNE.v3i10.1162</url><author>YangZhibin</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>3</volume><issue>10</issue><history><date date-type="pub"><published-time>2025-11-26</published-time></date></history><abstract>As the foundational cornerstone of the national statistical system, county-level statistics undertakes the mission of collecting, processing, and analyzing data to support local development. With the rapid growth of the digital economy, traditional county-level statistical practices face challenges such as diverse data sources, low processing efficiency, and insufficient service precision. The rise of artificial intelligence (AI) offers new possibilities for transformation. Through deep integration into data collection, processing, analysis, and service delivery, AI can help systematically address practical issues in grassroots statistical work. Based on the realities of county-level statistics and current AI applications in the field, this paper explores the practical value, typical scenarios, and existing dilemmas of AI-enabled county-level statistical analysis, proposing targeted development paths. The aim is to provide a reference for the modernization reform of grassroots statistics.</abstract><keywords>Artificial Intelligence, County-Level Statistics, Statistical Analysis, Grassroots Governance, Modernization Reform</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1]&amp;nbsp;Peng&amp;nbsp;DB,&amp;nbsp;Zhu&amp;nbsp;S.&amp;nbsp;2025.&amp;nbsp;Dilemma&amp;nbsp;Review&amp;nbsp;and&amp;nbsp;Breakthrough&amp;nbsp;Path&amp;nbsp;of&amp;nbsp;AI&amp;nbsp;Assisting&amp;nbsp;Smart&amp;nbsp;Statistics&amp;nbsp;Construction.&amp;nbsp;Journal&amp;nbsp;of&amp;nbsp;East&amp;nbsp;China&amp;nbsp;University&amp;nbsp;of&amp;nbsp;Technology&amp;nbsp;(Social&amp;nbsp;Science&amp;nbsp;Edition),&amp;nbsp;44(2):56-63.[2]&amp;nbsp;Shi&amp;nbsp;WG.&amp;nbsp;2025.&amp;nbsp;Research&amp;nbsp;on&amp;nbsp;Decision&amp;nbsp;Support&amp;nbsp;of&amp;nbsp;Statistical&amp;nbsp;Analysis&amp;nbsp;in&amp;nbsp;the&amp;nbsp;Big&amp;nbsp;Data&amp;nbsp;Environment.&amp;nbsp;Standard&amp;nbsp;Living,&amp;nbsp;38(5):28-33.[3]&amp;nbsp;Zhang&amp;nbsp;JY.&amp;nbsp;2025.&amp;nbsp;Research&amp;nbsp;on&amp;nbsp;the&amp;nbsp;Impact&amp;nbsp;of&amp;nbsp;Artificial&amp;nbsp;Intelligence&amp;nbsp;on&amp;nbsp;Statistical&amp;nbsp;Analysis.&amp;nbsp;Digital&amp;nbsp;Communication&amp;nbsp;World,&amp;nbsp;32(4):95-100.[4]&amp;nbsp;Zhang&amp;nbsp;GJ,&amp;nbsp;Zhu&amp;nbsp;JP,&amp;nbsp;Xie&amp;nbsp;BC.&amp;nbsp;2025.&amp;nbsp;AI&amp;nbsp;Empowering&amp;nbsp;Statistical&amp;nbsp;Applications:&amp;nbsp;Paradigm&amp;nbsp;Reconstruction&amp;nbsp;and&amp;nbsp;Future&amp;nbsp;Outlook.&amp;nbsp;Statistical&amp;nbsp;Research,&amp;nbsp;42(3):15-26.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
