f7a0057d-f52c-494b-82c3-3b1238d9202d20221230042306069wseas:wseasmdt@crossref.orgMDT DepositWSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS2224-28991109-952610.37394/23207http://wseas.org/wseas/cms.action?id=4016972022123120222010.37394/23207.2023.20https://wseas.com/journals/bae/2023.phpHassan AliAl-AbabnehFaculty of Administrative and Financial Sciences - E - Marketing and Social Communication, Irbid National University, PO Box 2600, Irbid, JORDANVictoriaBorisovaDepartment of Finance, Banking and Insurance, Sumy National Agrarian University, 160, G. Kondratieva Str., 40000, Sumy, UKRAINEAlinaZakharzhevskaDepartment of Management, State University of Telecommunications, 7, Solomyanska Str., 03110, Kyiv, UKRAINEPolinaTkachenkoDepartment of Business Economics and Entrepreneurship, Kyiv National Economic University named after Vadym Hetman, 54/1, Peremoga Avenue, 03057, Kyiv, UKRAINENataliaAndrusiakDepartment of Social Geography and Recreational Nature Management, Yuriy Fedkovych Chernivtsi National University, 2, Kotsyubynsky Str., 58012, Chernivtsi, UKRAINEThe development and implementation of innovations in various areas of business is stimulated by the competitive market environment. The use of artificial intelligence technologies for business process transformation is one of the most promising areas. Artificial intelligence is conductive to not only increasing the business process efficiency, but also to reducing the companies’ costs required for business process implementation. Artificial intelligence also contributes to reducing the need for human resources to perform routine operations. The aim of the study was to make a list of indicators that describe the performance of artificial intelligence technology in the activities of large companies and calculate them based on the example of the banking branch. Credit Agricole — a bank with foreign investment, one of the leaders of the banking sector of Ukraine — was chosen for the study. The methods of statistical and economic analysis were the main research methods used to contrast performance indicators with the use of artificial intelligence and without it. Quantitative indicators such as the duration of the client’s application; the cost of client service; the number of requests processed by the bank’s operators and managers; saving money spent on client service business processes were the main indicators for evaluating the performance of artificial intelligence. The results of the study demonstrated practical advantages of using artificial intelligence, which entail savings of working time and financial resources. These results confirm that the labor productivity of the bank branch employees has increased due to the automation of processes implemented through the artificial intelligence systems and technologies. The study opens up new areas of further research, in particular the impact of the use of artificial intelligence on financial performance and market capitalization of companies.123020221231202230731729https://wseas.com/journals/bae/2023/a585107-1803.pdf10.37394/23207.2023.20.29https://wseas.com/journals/bae/2023/a585107-1803.pdf10.1093/oso/9780197582879.003.0005OECD. Artificial intelligence, machine learning and big data in finance: Opportunities, challenges, and implications for policy makers, 2021. Retrieved from https://www.oecd.org/finance/financialmarkets/Artificial-intelligence-machinelearning-big-data-in-finance.pdf Deloitte. 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