@article {10.3844/jcssp.2026.947.959,
article_type = {journal},
title = {Adopting Artificial Intelligence in ERP Systems as an Innovation to Support Business Growth: A Systematic Literature Review},
author = {Lawendatu, Amalia Sulfinita and Hidayat, Fajar and Radhia, Fathy and Hartono, Sugiarto},
volume = {22},
number = {3},
year = {2026},
month = {Mar},
pages = {947-959},
doi = {10.3844/jcssp.2026.947.959},
url = {https://thescipub.com/abstract/jcssp.2026.947.959},
abstract = {Digital transformation is driving the integration of Artificial Intelligence (AI) into Enterprise Resource Planning (ERP) systems as an innovative strategy to improve organizational competitiveness. However, consolidated knowledge regarding the benefits and challenges of this integration remains scarce. This study utilizes a Systematic Literature Review (SLR) in accordance with the PRISMA framework to analyze 31 peer-reviewed articles published between 2020 and 2025. The findings are structured through the Technology-Organization-Environment (TOE) framework. The findings demonstrate AI's capacity to augment process automation, data quality, predictive analytics, and operational efficiency, thereby fortifying strategic decision-making and expediting digital transformation. Concurrently, organizations encounter persistent challenges, including integration complexity, data security risks, user resistance, limited expertise, and regulatory pressure. Contrary to previous reviews, this study offers a balanced analysis by comparing small- and medium-sized enterprises (SMEs) with large corporations. Additionally, it incorporates the post-2022 generative Artificial Intelligence (AI) wave, a development that has the potential to significantly impact business operations and strategic decisions. The findings contribute to the theoretical framework of the TOE by deepening the understanding of AI-ERP, and they inform sustainable adoption strategies in a practical sense. Future research must investigate longitudinal Return on Investment (ROI), causal links between governance and benefits, and cross-industry variations. This research will serve to strengthen the evidence for implementation.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}