Success Factors Impacting Artificial Intelligence Adoption - Perspective from The Telecom Industry in Malaysia

Article Sidebar

Article
Published: 15 September 2026
DOI: https://doi.org/10.33093/jetap.2026.8.2.3
Keywords:
Artificial Intelligence, Telecommunication, AI adoption, Technological-Organizational-External framework, TOE, Technology Acceptance Model

Main Article Content

Suvitha Palani
Faculty of Artificial Intelligence & Engineering, Multimedia University Cyberjaya, Cyberjaya, Selangor
Siva Priya Thiagarajah Thiagarajah
Faculty of Artificial Intelligence & Engineering, Multimedia University Cyberjaya, Cyberjaya, Selangor
Farzana Sharmin Nila Nila
Faculty of Artificial Intelligence & Engineering, Multimedia University Cyberjaya, Cyberjaya, Selangor

Abstract

Artificial Intelligence (AI) is playing a growing role in transforming the telecommunications sector by improving customer support, optimizing network performance, and enabling the development of innovative products and services. Despite its advantages, AI adoption in Malaysia's telecom industry faces several challenges, including infrastructure scalability, security issues, and system interoperability. To better understand these barriers, a research study was conducted using a combined Technology Acceptance Model (TAM) and Technology – Organization - Environment (TOE) framework. The study involved surveying network employees from three major Malaysian telecom providers-Telekom Malaysia, Maxis, and CelcomDigi-and examining global best practices to identify key success factors for AI adoption. The framework was validated through statistical techniques such as convergent and discriminant validity tests and Structural Equation Modelling (SEM). The results revealed that organizational and external factors, particularly managerial support, technical capability, market uncertainty, and vendor partnerships, significantly influence AI adoption, with perceived usefulness acting as a key mediator in the adoption process.

Article Details

How to Cite
[1]
Suvitha Palani, S. P. T. Thiagarajah, and F. S. N. Nila, “Success Factors Impacting Artificial Intelligence Adoption - Perspective from The Telecom Industry in Malaysia”, Journal of Engineering Technology and Applied Physics, vol. 8, no. 2, pp. 16–25, Sep. 2026.
Issue
Vol. 8 No. 2 (2026): https://doi.org/10.33093/jetap.2026.8.2
Section
Regular Paper for Journal of Engineering Technology and Applied Physics
Creative Commons License

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

References

[1] U. B. Mir, S. Sharma, A. K. Kar and M. P. Gupta, “Critical success Factors for Integrating Artificial Intelligence and Robotics,” Digit. Policy, Regul. Gov., vol. 22, no. 4, 307-331, 2020, doi: 10.1108/DPRG-03-2020-0032.

[2] S. N. Sekaran and M. R. Basir Khan, “Transforming Telecommunications Infrastructure in Malaysia: The Role of AI in Network Deployment and Optimization,” Malaysian J. Business, Econ. Manag., vol. 3, no. 2, pp. 174–182, 2024.

[3] E. Lim WeiLee, R. Sham, A. Loi, E. Shion and B. Wong, “M-Commerce Adoption Among Youths in Malaysia: Dataset Article,” Data Br., vol. 42, pp. 108238, 2022.

[4] “Maxis Integrated Annual Report 2023,” Maxis Limited, 2023.

[5] “Special Report: Charting A Cohesive National Strategy for AI - Infra Mobile Digital” [Available Online on 28 June 2025.]

https://inframobiledigital.com/special-report-charting-a-cohesive-national-strategy-for-ai/?utm_source=chatgpt.com.

[6] S. Lada et al., “Determining Factors Related to Artificial Intelligence (AI) Adoption Among Malaysia’s Small and Medium-Sized Businesses,” J. Open Innov. Technol. Mark. Complex., vol. 9, no. 4, pp. 100144, 2023.

[7] H. Choung, P. David and A. Ross, “Trust in AI and Its Role in the Acceptance of AI Technologies,” Int. J. Hum. Comput. Interact., vol. 39, no. 9, pp. 1727–1739, 2023.

[8] A. T. Mazikana, “The impact of Customer Relationship Management on Customer Satisfaction in Telecommunication Industry in Zimbabwe,” SSRN Electron. J., pp. 13–52, 2023..

[9] “Malaysia’s Blueprint for AI Dominance in ASEAN - Telecom Review Asia.” [Available online 28 June 2025.] https://www.telecomreviewasia.com/news/interviews/4791-malaysia-s-blueprint-for-ai-dominance-in-asean/?utm_source=chatgpt.com.

[10] T. Davenport and R. Kalakota, “The Potential for Artificial Intelligence in Healthcare,” Futur. Healthc. J., vol. 6, no. 2, pp. 94–98, 2019.

[11] Q. Guo and W. Huang, “Analyzing the Diffusion of Innovations Theory,” Sci. Soc. Res., vol. 6, pp. 95–98, 2024.

[12] R. Pelanek, T. Effenberger, and J. Cechak, “Complexity and Difficulty of Items in Learning Systems,” Int. J. Artif. Intell. Educ., vol. 32, no. 1, pp. 196–232, 2022.

[13] H. Chen, “Success Factors Impacting Artificial Intelligence Adoption: Perspective from the Telecom Industry in China,” PhD Thesis, Old Dominion University, pp. 192, 2019.

[14] P. Mikalef and M. Gupta, “Artificial Intelligence Capability: Conceptualization, Measurement Calibration, and Empirical Study on Its Impact on Organizational Creativity and Firm Performance,” Inf. Manag., vol. 58, no. 3, pp. 103434, 2021.

[15] T. Sever and G. Contissa, “Automated Driving Regulations – Where Are We Now?” Transp. Res. Interdiscip. Perspect., vol. 24, pp. 101033, 2024.

[16] S. Chatterjee, N. P. Rana, Y. K. Dwivedi and A. M. Baabdullah, “Understanding AI Adoption in Manufacturing and Production Firms using An Integrated TAM-TOE Model,” Technol. Forecast. Soc. Change, vol. 170, pp. 120880, 2021.