Work Motivation of Bank Employees in Case of Implementing AI and Robots in the Bank Activities: Comparative Analysis of Russia and Kazakhstan

Vesselin Blagoev, Elena Shustova and Nina Protas

Economic Studies journal, 2022, issue 7, 63-80

Abstract: The dynamic changes in the banking industry as a result of the AI application and robotisation lead to substantial organisational changes and redefining the roles of bank employees. This, of course, has an impact on bank employees’ work motivation. In 2020-2021 the businesses, including banking, encountered one more influencing factor – the Covid-19 pandemic and related quarantine and lockdown measures, leading to forced move to remote work. This research aims to find out if the work motivation of the bank employees has changed, and if yes – in what directions. The analysis is based on the findings of a survey, conducted in the two countries in the period November 2020 – February 2021 and the results show some significant differences between the work motivation in the banking industry in the two countries. The questionnaire items target the main work motivation factors. Two working hypotheses were studied in this research: H1: The intensive implementation of AI in the banking sector positively affects the work motivation of bank employees in Russia and Kazakhstan. H2: The age of the employees matters for appreciation of the AI implementation, as younger employees 18-40 are more positive compared to employees beyond 40. H1 was confirmed, while H2 was confirmed regarding the difference in the opinions and motivation of the two age groups (under 40 and above 40 years of age), but not in regard to the appreciation of the changes by the two age groups. The main beneficiaries of the results of this research are the bank managers, both HRM and line managers, who are directly responsible for supporting the work motivation in the process of intensive implementation of AI and robotisation, e.g., chatbots, in the sector. It is also believed that the managers in the other sectors of the economy may benefit from these findings as well.

JEL-codes: E24 G20 J24 O15 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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