Enhancing Employee Performance Through AI-Driven Business Communication: A Case Study

Authors

DOI:

https://doi.org/10.51903/jmi.v3i2.29

Keywords:

Employee Decision-Making, AI Integration, AI-driven business Communication, MSMEs, AI Adoption

Abstract

In the current digital age, the incorporation of Artificial Intelligence (AI) into organizational communication has gained growing significance as a means to improve employee productivity and overall performance. This study aims to evaluate the impact of AI implementation on workplace communication processes and how it affects productivity as well as collaboration across divisions. The method used in this research is an experimental approach, involving the analysis of company conditions before and after AI implementation, along with a survey to gauge employees' perspectives on the effectiveness of this technology. The findings show that AI adoption significantly improves decision-making speed, communication effectiveness, and employee productivity. Furthermore, the study identifies challenges faced by employees in adapting to new technology, such as resistance to change and the need for training. The conclusion of this study emphasizes that while AI offers many benefits, the success of its implementation largely depends on the organization's readiness and the support provided to employees. This research provides valuable insights for companies in designing effective AI adoption strategies to improve communication quality and organizational performance.

References

Abidi, M. H., Mohammed, M. K., & Alkhalefah, H. (2022). Predictive Maintenance Planning for Industry 4.0 Using Machine Learning for Sustainable Manufacturing. Sustainability 2022, Vol. 14, Page 3387, 14(6), 3387. https://doi.org/10.3390/SU14063387

Abun, D., Nicolas, M. T., Apollo, E., Magallanes, T., & Encarnacion, M. J. (2021). Employees’ Self-Efficacy and Work Performance of Employees as Mediated by Work Environment. International Journal of Research in Business and Social Science (2147- 4478), 10(7), 01–15. https://doi.org/10.20525/ijrbs.v10i7.1470

Arslan, A., Cooper, C., Khan, Z., Golgeci, I., & Ali, I. (2022). Artificial Intelligence and Human Workers Interaction at Team Level: A Conceptual Assessment of the Challenges and Potential HRM Strategies. International Journal of Manpower, 43(1), 75–88. https://doi.org/10.1108/IJM-01-2021-0052

Azman, N. A., Mohamed, A., & Jamil, A. M. (2021). Artificial Intelligence in Automated Bookkeeping: A Value-added Function for Small and Medium Enterprises. JOIV : International Journal on Informatics Visualization, 5(3), 224–230. https://doi.org/10.30630/JOIV.5.3.669

Badghish, S., & Soomro, Y. A. (2024). Artificial Intelligence Adoption by SMEs to Achieve Sustainable Business Performance: Application of Technology Organization Environment Framework. Sustainability (Switzerland), 16(5). https://doi.org/10.3390/su16051864

Costa, F., & Portioli-Staudacher, A. (2021). Labor Flexibility Integration in Workload Control in Industry 4.0 Era. Operations Management Research, 14(3–4), 420–433. https://doi.org/10.1007/S12063-021-00210-2/FIGURES/4

Dibie, E. J. (2024). Strategic Role of Artificial Intelligence (AI) on Human Resource Management (HR) Employee Performance Evaluation Function. International Journal of Entrepreneurship and Business Innovation, 7(2), 269–282. https://doi.org/10.52589/IJEBI-HET5STYK

Getchell, K. M., Carradini, S., Cardon, P. W., Fleischmann, C., Ma, H., Aritz, J., & Stapp, J. (2022). Artificial Intelligence in Business Communication: The Changing Landscape of Research and Teaching. Business and Professional Communication Quarterly, 85(1), 7–33. https://doi.org/10.1177/2329490622107431

Griffiths, A. J., Alsip, J., Hart, S. R., Round, R. L., & Brady, J. (2020). Together We Can Do So Much: A Systematic Review and Conceptual Framework of Collaboration in Schools. Sage Journals, 36(1), 59–85. https://doi.org/10.1177/0829573520915368

Helo, P., & Hao, Y. (2022). Artificial Intelligence in Operations Management and Supply Chain Management: An Exploratory Case Study. Production Planning & Control, 33(16), 1573–1590. https://doi.org/10.1080/09537287.2021.1882690

Jagatheesaperumal, S. K., Rahouti, M., Ahmad, K., & Al-Fuqaha, A. (2020). The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions. EEE Internet of Things Journal, 9(15), 12861–12885. https://doi.org/10.1109/JIOT.2021.3139827

Joel Prabhod, K. (2024). The Role of Artificial Intelligence in Reducing Healthcare Costs and Improving Operational Efficiency. Quarterly Journal of Emerging Technologies and Innovations, 9(2), 47–59.

Kalogiannidis, S., & Kontsas, S. (2021). Impact of Business Communication Determinants on Business Profitability: An Empirical Evidence of Citibank in Greece 1 Introduction. International Journal of Human Resource Studies, 11(2), 137–150. https://doi.org/10.5296/ijhrs.v11i2.18358

Khan, A. A., Laghari, A. A., Li, P., Dootio, A., & Karim, S. (2023). The Collaborative Role of Blockchain, Artificial Intelligence, and Industrial Internet of Things In Digitalization of Small and Medium-Size Enterprises. Scientific Reports, 13, 1656. https://doi.org/10.1038/s41598-023-28707-9

Li, J. Y., Sun, R., Tao, W., & Lee, Y. (2021). Employee Coping with Organizational Change in the Face of A Pandemic: The Role of Transparent Internal Communication. Public Relations Review, 47(1), 101984. https://doi.org/10.1016/J.PUBREV.2020.101984

Mishrif, A., & Khan, A. (2023). Technology Adoption as Survival Strategy for Small and Medium Enterprises during COVID-19. Journal of Innovation and Entrepreneurship, 12(1), 1–23. https://doi.org/10.1186/S13731-023-00317-9/TABLES/4

Musheke, M. M., Phiri, J., Musheke, M. M., & Phiri, J. (2021). The Effects of Effective Communication on Organizational Performance Based on the Systems Theory. Open Journal of Business and Management, 9(2), 659–671. https://doi.org/10.4236/OJBM.2021.92034

Riyanto, S., Endri, E., & Herlisha, N. (2021). Effect of Work Motivation and Job Satisfaction on Employee Performance: Mediating Role of Employee Engagement”. Problems and Perspectives in Management, 19(3), 2021. https://doi.org/10.21511/ppm.19(3).2021.14

Rožman, M., Oreški, D., & Tominc, P. (2023). Artificial Intelligence Supported Reduction of Employees’ Workload to Increase the Company’s Performance in Today’s VUCA Environment. Sustainability (Switzerland), 15(6). https://doi.org/10.3390/su15065019

Sathupadi, K. (2023). AI-Driven Energy Optimization in SDN-Based Cloud Computing for Balancing Cost, Energy Efficiency, and Network Performance.

Sugiarti, E., Finatariani, E., & Rahman, Y. T. (2021). Earning Cultural Values As a Strategic Step To Improve Employee Performance. Scientific Journal of Reflection : Economic, Accounting, Management and Business, 4(1), 221–230. https://doi.org/10.37481/sjr.v4i1.270

Wang, X., Lin, X., & Shao, B. (2022). How Does Artificial Intelligence Create Business Agility? Evidence from Chatbots. International Journal of Information Management, 66, 102535. https://doi.org/10.1016/J.IJINFOMGT.2022.102535

Yue, C. A., Men, L. R., & Ferguson, M. A. (2021). Examining the effects of internal communication and emotional culture on employees’ organizational identification. International Journal of Business Communication, 58(2), 169–195. https://doi.org/10.1177/2329488420914066

Zahra, R. A., Bhima, Nurtino, T., & Zaki Firli, M. (2023). Enhancing Organizational Efficiency Through the Integration of Artificial Intelligence in Management Information Systems. APTISI Transactions on Management (ATM), 7(3), 275–282.

Zhao, J., & Gómez Fariñas, B. (2023). Artificial Intelligence and Sustainable Decisions. European Business Organization Law Review, 24(1), 1–39. https://doi.org/10.1007/S40804-022-00262-2/FIGURES/1

Downloads

Published

2024-08-22