<![CDATA[Organizations rely heavily on Management Information Systems (MIS) as the primary channel through which relevant data are converted into information that supports sound decision-making. As Artificial Intelligence (AI) technology matures, MIS gains new capacities—among them automated data handling, predictive-analytics functions, and decision support that is markedly quicker and more precise. The present study sets out to systematically trace how AI has been incorporated into MIS and to assess the resulting effect on the quality of organizational decisions. Guided by the PRISMA flow, a Systematic Literature Review (SLR) was carried out through stages of identification, screening, eligibility appraisal, and synthesis, drawing on articles published from 2019 through 2026 across Google Scholar, Garuda, SINTA, and ScienceDirect. Out of 236 articles initially identified, 20 satisfied the inclusion criteria and were subjected to thematic analysis. Five overarching themes emerged from this process: the automation and streamlining of MIS workflows; predictive analytics coupled with business intelligence; gains in the quality and speed of strategic decisions; variation across sectoral settings spanning SMEs, banking, hospitals, manufacturing, and tourism; and the practical and ethical hurdles encountered during implementation. The study concludes that embedding AI within MIS yields a positive contribution to decision-making effectiveness, although the extent of that success hinges on data quality, the readiness of human resources, and sound algorithmic governance. It is hoped that these findings can serve academics and practitioners alike as a reference point when formulating strategies for AI adoption within organizational MIS.Keywords: management information system; artificial intelligence; decision-making; systematic literature review]]>
