{"title":"会计中的人工智能","authors":"S. Korol, O. Romashko","doi":"10.31617/1.2024(154)08","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":487010,"journal":{"name":"SCIENTIA FRUCTUOSA","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence in accounting\",\"authors\":\"S. Korol, O. Romashko\",\"doi\":\"10.31617/1.2024(154)08\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":487010,\"journal\":{\"name\":\"SCIENTIA FRUCTUOSA\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SCIENTIA FRUCTUOSA\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.31617/1.2024(154)08\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SCIENTIA FRUCTUOSA","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.31617/1.2024(154)08","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.