Challenges of Technology Implementation in Accounting Information Systems: A Systematic Literature Review and Bibliometric Analysis

Authors

Dedeh Cahyani Toresa

Hasanuddin University (Indonesia)

Andi Naimah Syakir

Hasanuddin University (Indonesia)

Grace T. Pontoh

Hasanuddin University (Indonesia)

Aini Indrijawati

Hasanuddin University (Indonesia)

Article Information

DOI: 10.51244/IJRSI.2026.1313CS028

Subject Category: Computer Science

Volume/Issue: 13/13 | Page No: 354-366

Publication Timeline

Submitted: 2026-09-09

Accepted: 2026-09-14

Published: 2026-09-29

Abstract

This study aims to identify research developments and map the main challenges of technology implementation in AIS through a Systematic Literature Review (SLR) approach and bibliometric analysis. Data were obtained from the Scopus database using the PRISMA framework, resulting in 52 articles that met the inclusion criteria. Bibliometric analysis was conducted using VOSviewer to map publication trends, countries, affiliations, journal sources, and research keywords. The results show that studies on technology implementation in AIS have increased significantly since 2024, with a primary focus on ERP, AI, automation, machine learning, blockchain, and cloud computing. Thematic synthesis identified five main challenges to technology implementation in AIS: user competence and resistance, organizational readiness and management support, system integration and complexity, cost and resource constraints, and security, privacy, and data quality. These findings indicate that the success of technology implementation is not only determined by system sophistication but also influenced by human, organizational, and information governance readiness. This study contributes to enriching the literature on technology implementation in AIS and serves as a basis for developing more effective digital transformation strategies in the future.

Keywords

Accounting Information Systems, Technology Implementation, Digital Transformation, Enterprise Resource Planning, Artificial Intelligence, Systematic Literature Review

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