The Transformative Impact of the Development of Artificial Intelligence on Employment and Work Motivation in Business in the Conditions of the Information Economy

Y. Yakovenko, M. Bilyk, Yevheniia V. Oliinyk
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Abstract

The paper examines how the development of digital technologies, in particular artificial intelligence (AI), affects the labor market and changes the work process. It is argued that the main goal of enterprise management in the conditions of digital transformations is the formation of internal motivation among employees. As a result of this, the employee's dependence on positive and negative reinforcements from management decreases and self-motivation increases. The internal and external factors that contribute to the increase or decrease of the salary are determined. The role of the obtained results in further practical implementation is to make clear how AI algorithms help employees reach goals more efficiently - based on the study of cases of digitalization achievements in the field of motivation on the example of Ukrainian innovative companies the construction of the “needs - interests - incentives (motives) - result” scheme was proposed. Direct economic, indirect economic and non-monetary methods of motivation are considered and the main principles of the development of the motivation system are highlighted. It is emphasized that due to the training and retraining of personnel in such a way that the growth of their wages does not lag behind their productivity, and they receive wider opportunities for career growth, it is possible to ensure the sustainability of personnel policy in the conditions of the transformational impact of digitalization and AI.
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信息经济条件下人工智能发展对企业就业和工作动机的变革性影响
本文探讨了数字技术,特别是人工智能(AI)的发展如何影响劳动力市场并改变工作流程。本文认为,在数字化转型条件下,企业管理的主要目标是员工内部激励的形成。因此,员工对管理层正强化和负强化的依赖性降低,自我激励增强。确定了导致工资增减的内外部因素。所得结果在进一步实际实施中的作用是明确人工智能算法如何帮助员工更有效地实现目标——基于对激励领域数字化成果案例的研究,以乌克兰创新型公司为例,提出了“需求-利益-激励(动机)-结果”方案的构建。分析了直接经济激励、间接经济激励和非货币激励方法,强调了激励制度发展的主要原则。报告强调,由于对人员进行培训和再培训,使他们的工资增长不落后于他们的生产力增长,并且他们获得了更广泛的职业发展机会,因此有可能在数字化和人工智能的转型影响下确保人事政策的可持续性。
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