会计中的人工智能

S. Korol, O. Romashko
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摘要

人工智能(AI)技术为提高业务效率、推动各专业领域的发展、提高生产力和竞争力开辟了广阔的前景。人们正在积极探索将人工智能技术纳入会计领域的方法,有望实现从人工参与到机器参与的无缝过渡。本文旨在总结已有经验,明确在会计师职业活动中使用人工智能技术的相关视角、制约因素和风险。研究基于这样一个假设:在会计师的职业活动中广泛使用人工智能,但职业怀疑和谨慎程度不够,会给会计师和整个企业带来巨大的威胁和风险。本文采用了科学搜索法、比较和批判分析法、理论概括和综合法。在会计领域实施人工智能技术的前提是专家信息系统和企业资源规划系统。对各行各业人工智能技术实施经验的分析表明,人工智能技术在会计领域执行常规任务(自动识别主要文件、处理传入信号和其他标准操作,同时降低出错概率)、分析大型数据集、为决策提供信息支持(处理业务数据和监管文件)、培训专业人员、组织内部和外部交流(特别是人与机器之间的交流)等方面具有重要意义。已发现的潜在风险包括侵犯隐私和数据安全、曲解输出数据、忽视活动背景、外部和内部环境,特别是由于缺乏情商,这影响了对综合信息系统的信任度。规范性文件要求应用专业评估和判断,这限制了人工智能技术在会计领域的应用范围。未来的研究应侧重于探索在会计信息系统中广泛集成人工智能技术的可能性,并在风险评估原则的基础上完善立法。
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Artificial intelligence in accounting
Artificial Intelligence (AI) technologies open up broad horizons for enhancing business efficiency and advancing various professional domains, boosting their productivity and compe­titiveness. There is an active exploration of approaches to incorporating AI technologies in the accounting sphere, promising a seamless transition from human to machine involvement. The aim of this article is to summarize the acquired experience, identify perspectives, constraints, and risks associated with the use of AI technologies in the professional activities of accountants. The research is based on the hypothesis that widespread use of AI in the professional activity of an accountant with an insufficient level of professional skepticism and caution carries significant threats and risks for both the accountant and the business as a whole. Scientific search methods, comparative and critical analysis, theoretical generalization, and synthesis were used. A prerequisite for imple­menting AI technologies in accounting is expert information systems and ERP systems. The analysis of AI technology implementation experience in various industries demonstrates their relevance in the accounting field for performing routine tasks (automated recognition of primary documents, processing incoming signals, and other standard operations with a simultaneous reduction in the probability of errors), analyzing large datasets, and providing information support for decision-making (pro­ces­sing business data and regulatory docu­ments), training professionals, and organi­zing internal and external communication (parti­cularly between humans and machines). Identi­fied potential risks include breaches of privacy and data security, misinterpretation of output data, and the disregard of activity context, external and internal environments, especially due to the absence of emotional intelligence, which influences the trust level in integrated information systems. The requirement for the application of professional assessments and judgments, mandated by regulatory documents, limits the scope of AI technology utilization in accounting. Future research should focus on exploring the possibilities of widespread integ­ration of AI technologies in information systems for accounting and improving legislation based on the principle of risk assessment.
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