Home / Volume 9, Issue 3 / The Impact of Digitization on Work Performance Open access · CC BY-NC 4.0
Research Paper Volume 9 Issue 3 83 - 107 May 18, 2026

The Impact of Digitization on Work Performance

Lead author · Corresponding
Boldbaatar GONCHIGJAV
Head at Department of Business Administration, Shihihutug University, Ulaanbaatar, Mongolia
Abstract

digital technologies are being used to help businesses facilitate employee work, improve productivity, make customer service lighter and faster, increase sales, and improve the Coordination of organizational work, and companies must use a balanced symbiosis of human and computer intelligence to create new work experiences. Currently, there is a significant lack of empirical research on how the use of new digital technologies (artificial intelligence) affects the work experience of employees. As such, this study aims to analyze how the work experience of employees who use new digital technologies can be improved. A survey was taken of 92 employees who work in organizations that use digital technologies with artificial intelligence (sales, service stations, restaurants, health care facilities and others that sell cosmetics). The study aimed to indicate that job enrichment, choice and stress management, higher sensitivity, better working conditions, less travel, more payments, job security and protection, more careers, dealing with change, Privacy, working with strangers, identification are key factors in the activities of organizations that use artificial intelligence, which play an important role in the work experience of employees and can directly affect the work experience of employees. So, using the results of this study, it is expected that service organizations will be more effective and profitable if they use artificial intelligence optimally to improve the work experience of their employees.

Type
Research Paper
Information
International Journal of Law Management and Humanities, Volume 9, Issue 3, Page 83 - 107
Creative Commons
CC BY-NC 4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.
Copyright
Copyright © IJLMH 2026
Disclaimer
The views and opinions expressed in this manuscript are those of the author(s) alone and do not reflect the views, policies, or position of the Journal.

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