Artificial Intelligence for Management Information Systems: Opportunities, Challenges, and Future Directions

Author:

Stoykova Stela1ORCID,Shakev Nikola1

Affiliation:

1. Faculty of Electronics and Automation, Technical University-Sofia, 4000 Plovdiv, Bulgaria

Abstract

The aim of this paper is to present a systematic literature review of the existing research, published between 2006 and 2023, in the field of artificial intelligence for management information systems. Of the 3946 studies that were considered by the authors, 60 primary studies were selected for analysis. The analysis shows that most research is focused on the application of AI for intelligent process automation, with an increasing number of studies focusing on predictive analytics and natural language processing. With respect to the platforms used by AI researchers, the study finds that cloud-based solutions are preferred over on-premises ones. A new research trend of deploying AI applications at the edge of industrial networks and utilizing federated learning is also identified. The need to focus research efforts on developing guidelines and frameworks in terms of ethics, data privacy, and security for AI adoption in MIS is highlighted. Developing a unified digital business strategy and overcoming barriers to user–AI engagement are some of the identified challenges to obtaining business value from AI integration.

Funder

European Regional Development Fund

Publisher

MDPI AG

Subject

Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science

Reference139 articles.

1. Thormundsson, B. (2023). Global Artificial Intelligence Market Size 2021–2030, Statista.

2. Devanport, T. (2018). The AI Advantage: How to Put the Artificial Intelligence Revolution to Work, The MIT Press.

3. The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions;Borges;Int. J. Inf. Manag.,2020

4. Artificial intelligence in information systems research: A systematic literature review and research agenda;Collins;Int. J. Inf. Manag.,2021

5. Face recognition: Literature review with emphasis on deep learning;Moghekar;J. Theor. Appl. Inf. Technol.,2019

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