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Han, T.A., Pandit, D., Joneidy, S., Hasan, M.M., Hossain, J., Hoque Tania, M., et al. (2023) An Explainable AI Tool for Operational Risks Evaluation of AI Systems for SMEs. 2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Kuala Lumpur, 8-10 December 2023, 69-74.
https://doi.org/10.1109/skima59232.2023.10387301

has been cited by the following article:

• TITLE: Navigating the Challenges of AI Integration into Business Analytics Platforms for SMEs: A Systematic Literature Review

  AUTHORS: Cihan Yilmaz, Anja Hanisch-Blicharski

  KEYWORDS: Artificial Intelligence, Digital Solutions, Business Analytics, Systematic Literature Review

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.15 No.7, July 17, 2025

  ABSTRACT: This study investigates the growing attention around the integration of Artificial Intelligence (AI) into Business Analytics (BA) platforms within Small and Medium Enterprises (SMEs). The objective is to provide an overview of the existing literature related to this topic, with a systematic literature review, highlighting the challenges and potential benefits of AI integration in SMEs. A central finding is the critical importance of training programs to develop AI competencies which is essential for maintaining competitiveness. However, implementation is often hindered by technical and financial barriers. Additionally, there is a range of opinions regarding the ethical implications and long-term effects of automation. The research indicates that successful AI integration can yield in efficiency gains alongside social and ecological benefits when suitable conditions are established within enterprises. This underscores the necessity for further examination of the impacts of AI on organizational structures, workforce dynamics and ethical standards. The findings offer valuable insights for developing and implementing AI strategies and highlighting the need for empirical studies to better understand the long-term effects of AI integrations.