Article Open Access

Artificial Intelligence (AI) in Telkom Indonesia's Digital Business Transformation

(1) * Acep Arna Hikmat Mail (Universitas Komputer Indonesia, Bandung, Indonesia)
(2) M Yani Syafei Mail (Universitas Komputer Indonesia, Bandung, Indonesia)
(3) Umi Narimawati Mail (Universitas Komputer Indonesia, Bandung, Indonesia)
*Corresponding author

Abstract


Digital transformation has become the key to organizational success in facing the disruptive era. This study aims to analyze the role of artificial intelligence (AI) in supporting the digital transformation of Telkom Indonesia's business. The research method used is qualitative with in-depth interviews with technology experts and key stakeholders at Telkom Indonesia, especially in mobile network management . The results of the study show that the implementation of AI has increased operational efficiency through network management, especially in better mobile networks, accelerated strategic decision-making and autonomous jobs , and created a positive impact on company performance in the form of efficiency and additional revenue and increased customer satisfaction. With this achievement, AI has proven to be one of the key factors in the success of the company's digital transformation. This study makes a significant contribution to understanding the implementation of AI as the main driver of digital transformation in telecommunications companies such as Telkom Indonesia. These findings are expected to be a reference for technology-based business strategies in the future.

Keywords


Artificial Intelligence; Transformation; AI; Telkom; Mobile Network

   

DOI

https://doi.org/10.33122/ejeset.v6i1.404
      

Article metrics

Abstract views : 280 | PDF views : 264

   

Cite

   

Full Text

Download

References


Brock, J. K.-U., & von Wangenheim, F. (2019). Artificial intelligence in customer relationship management: Foundations and future research directions. Journal of Service Management, 30 (2), 156–183.

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3 (2), 77–101.

Bryman, A. (2012). Social research methods . Oxford University Press.

Brynjolfsson, E., & McAfee, A. (2017). The second machine age: Work, progress, and prosperity in a time of brilliant technologies . WW Norton & Company.

Bughin, J., Seong, J., Manyika, J., Chui, M., & Joshi, R. (2018). Notes from the AI frontier: Modeling the impact of AI on the world economy . McKinsey Global Institute.

Chui, M., Manyika, J., & Miremadi, M. (2018). The AI frontier: Modeling the impact of AI on the world economy . McKinsey Global Institute.

Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches . SAGE Publications.

Dasep Suryanto, Slamet Riyanto, & Arffudin. (2024). Implementation of Law Number 27 of 2022 concerning personal data protection in the retail industry: A review of compliance and its impact on consumers. Journal of the Postgraduate Program in Law, 10 (1).

PwC. (2019). Global artificial intelligence study: Exploiting the AI revolution . PricewaterhouseCoopers.

Russell, S., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson.

Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28 (2), 118–144.

Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading digital: Turning technology into business transformation . Harvard Business Review Press.

Yin, R. K. (2018). Case study research and applications: Design and methods . SAGE Publications.


Refbacks

  • There are currently no refbacks.


Copyright (c) 2025 Acep Arna Hikmat, M. Yani Syafei and Umi Narimawati

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0