{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T07:44:58Z","timestamp":1776411898610,"version":"3.51.2"},"reference-count":139,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,7,26]],"date-time":"2023-07-26T00:00:00Z","timestamp":1690329600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Regional Development Fund","award":["\u2116 BG05M2OP001-1.002-0023"],"award-info":[{"award-number":["\u2116 BG05M2OP001-1.002-0023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>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\u2013AI engagement are some of the identified challenges to obtaining business value from AI integration.<\/jats:p>","DOI":"10.3390\/a16080357","type":"journal-article","created":{"date-parts":[[2023,7,27]],"date-time":"2023-07-27T02:07:17Z","timestamp":1690423637000},"page":"357","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Artificial Intelligence for Management Information Systems: Opportunities, Challenges, and Future Directions"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9670-823X","authenticated-orcid":false,"given":"Stela","family":"Stoykova","sequence":"first","affiliation":[{"name":"Faculty of Electronics and Automation, Technical University-Sofia, 4000 Plovdiv, Bulgaria"}]},{"given":"Nikola","family":"Shakev","sequence":"additional","affiliation":[{"name":"Faculty of Electronics and Automation, Technical University-Sofia, 4000 Plovdiv, Bulgaria"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,26]]},"reference":[{"key":"ref_1","unstructured":"Thormundsson, B. 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