Published date: May 26 2023

Journal Title: KnE Social Sciences

Issue title: International Conference on Advance & Scientific Innovation (ICASI)

Pages: 958–970

DOI: 10.18502/kss.v8i9.13409

Dyah O.S. AgustonoUniversitas 17 Agustus 1945 Surabaya, Indonesia

Riyadi NugrohoUniversitas 17 Agustus 1945 Surabaya, Indonesia

Achmad Yanu Alif FiantoUniversitas 17 Agustus 1945 Surabaya, Indonesia

This study discussed the value of Artificial Intelligence (AI) in Human Resource (HR) Management through the AI Capability Framework (ACF) in the Asian and Indonesian contexts. This study was a literature review conducted by collecting data from various articles and scientific journals relevant to the topics discussed. The results of the literature review showed that the use of AI in HR Management has the potential to increase the efficiency and effectiveness of the HR management process and provide added value for companies in improving their performance and competitiveness. ACF is used as a framework to measure a company’s ability to implement AI in HR Management, considering policies, technology infrastructure, human resource capabilities, and organizational culture. The use of AI in HR Management can also affect decision-making in companies and has implications for company performance. Therefore, this study provided suggestions and recommendations for companies to develop AI capabilities in HR Management, such as conducting human resource training and development, strengthening technology infrastructure, and creating an organizational culture that supports the use of AI technology. In addition, this research also identified several factors that can influence the implementation of AI in HR Management, such as policy, technological, and human factors. Further research can examine these factors more deeply and how companies can overcome obstacles in implementing AI in HR Management.

Keywords: Artificial Intelligence, Human Resource Management, Capability Framework

[1] Chatterjee S, Chaudhuri R, Vrontis D, Thrassou A, Ghosh SK. Adoption of artificial intelligence-integrated CRM systems in agile organizations in India. Technol Forecast Soc Change. 2021 Jul;168:120783.

[2] Mustak M, Salminen J, Plé L, Wirtz J. Artificial intelligence in marketing: topic modeling, scientometric analysis, and research agenda. J Bus Res. 2021 Jan;124:389–404.

[3] Leone D, Schiavone F, Appio FP, Chiao B. How does artificial intelligence enable and enhance value co-creation in industrial markets? An exploratory case study in the healthcare ecosystem. J Bus Res. 2021 May;129:849–59.

[4] Guha A, Grewal D, Kopalle PK, Haenlein M, Schneider MJ, Jung H, et al. How artificial intelligence will affect the future of retailing. J Retailing. 2021 Mar;97(1):28–41.

[5] Kumar A, Kalse A. Usage and adoption of artificial intelligence in SMEs. Mater Today Proc. 2021;(Feb): https://doi.org/10.1016/j.matpr.2021.01.595.

[6] Chatterjee S, Rana NP, Tamilmani K, Sharma A. The effect of AI-based CRM on organization performance and competitive advantage: an empirical analysis in the B2B context. Ind Mark Manage. 2021 Aug;97:205–19.

[7] Mikalef P, Conboy K, Krogstie J. Artificial intelligence as an enabler of B2B marketing: A dynamic capabilities micro-foundations approach. Ind Mark Manage. 2021 Oct;98:80–92.

[8] Shiue W, Tuncdogan A, Wang F, Bredican J. Strategic enablers of service-sales ambidexterity: A preliminary framework and research agenda. Ind Mark Manage. 2021 Jan;92:78–86.

[9] Bag S, Gupta S, Kumar A, Sivarajah U. An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance. Ind Mark Manage. 2021 Jan;92:178–89.

[10] Cobbe J, Singh J. Artificial intelligence as a service: legal responsibilities, liabilities, and policy challenges. Comput Law Secur Rep. 2021 Sep;42:105573.

[11] Pallathadka H, Ramirez-Asis EH, Loli-Poma TP, Kaliyaperumal K, Ventayen RJ, Naved M. Applications of artificial intelligence in business management, e-commerce and finance. Mater Today Proc. 2021;( Jul): https://doi.org/10.1016/j.matpr.2021.06.419.

[12] Pantano E, Pizzi G. Forecasting artificial intelligence on online customer assistance: evidence from chatbot patents analysis. J Retailing Consum Serv. 2020 Jul;55:102096.

[13] Ameen N, Tarhini A, Reppel A, Anand A. Customer experiences in the age of artificial intelligence. Comput Human Behav. 2021 Jan;114:106548.

[14] Lv X, Yang Y, Qin D, Cao X, Xu H. Artificial intelligence service recovery: the role of empathic response in hospitality customers’ continuous usage intention. Comput Human Behav. 2022 Jan;126:106993.