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| 现代人工智能背景下的财务会计转型研究问题 摘要 大数据时代下，各行各业的新奇运营模式和工作方式层出不穷，人工智能衍生的各种新型工作工具逐渐成为企业工作模式的主导，其在会计行业中的应用更是不容小觑。数据采集（库存机、PC与网络数据采集软件）、数据搜集系统（可视化报告的定义，审计关系的定义，发布报告和批准，数据报告、处理、检查等）与数据处理系统（综合查询统计与其他功能）都促进了会计的转型发展，拓展了数据收集的广度，提高了信息获取与处理的全面性，增强了信息收集网络和数字化审计工作的准确性，加强了财会部门与企业各部门之间联系的紧密性，有助于财务数据分门别类的服务于企业各部门，成为了满足企业经济发展的需要。在信息高速发展的今天，大数据对企业发展有着无法替代的重要性，可以说，掌握大数据就是掌握企业未来的第一步。财务会计领域要求管理会计能够整理和分析大数据，包括半结构化和结构化的多样信息，并拥有发现问题，分析问题和解决问题的能力。 ABSTRACT In the era of big data,novel operation modes and working methods of all walks of life emerge in endlessly. Various new work tools derived from artificial intelligence have gradually become the leading work mode of enterprises, and its application in the accounting industry can not be underestimated. Data acquisition (inventory machine, PC and network data acquisition software),data collection system (definition of visual report,definition of audit relationship, release report and approval, data report, processing, inspection, etc.) and data processing system (Comprehensive query statistics and other functions) have promoted the transformation and development of accounting, expanded the breadth of data collection,improved the comprehensiveness of information acquisition and processing, enhanced the accuracy of information collection network and digital audit work, strengthened the close relationship between the accounting department and various departments of the enterprise, and helped the financial data to serve various departments of the enterprise in different categories, and become the core of accounting It meets the needs of economic development of enterprises. Today, with the rapid development of information,big data plays an irreplaceable role in the development of enterprises. It can be said that mastering big data is the first step in mastering the future of enterprises.The field of financial accounting requires management accounting to be able tosort out and analyze big data,including semi-structured and structured diversified information, and have the ability to find, analyze and solve problems. KEYWORDS AI：Transformation ：Big data |
