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<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>عنوان مجله</JournalTitle>
      <Issn></Issn>
      <Volume>3</Volume>
      <Issue>Serial Number 9</Issue>
      <PubDate PubStatus="epublish">
        <Year>2026</Year>
        <Month>01</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>The Role of Artificial Intelligence in Transforming Management Systems: A Review of Opportunities, Risks, and Future Directions</ArticleTitle>
    <VernacularTitle>The Role of Artificial Intelligence in Transforming Management Systems: A Review of Opportunities, Risks, and Future Directions</VernacularTitle>
    <FirstPage>21</FirstPage>
    <LastPage>29</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <Abstract>&lt;p&gt;This study aimed to explore how artificial intelligence transforms management systems by identifying its perceived opportunities, organizational risks, and future directions from the perspective of managers and digital transformation experts. This qualitative study was conducted using an exploratory design based on semi-structured interviews. Participants included 22 senior managers, middle managers, digital transformation specialists, human resource managers, and information technology experts working in public and private organizations in Tehran, Iran. Participants were selected through purposive sampling, and interviews continued until theoretical saturation was achieved. Data were collected through face-to-face and online semi-structured interviews focusing on AI-enabled decision-making, automation, managerial control, human–AI collaboration, governance challenges, and future organizational capabilities. Interviews were recorded with participants’ consent, transcribed verbatim, and analyzed using thematic analysis. NVivo software was used to organize codes, compare categories, and develop the final thematic structure. The analysis produced five main categories: AI-enabled decision intelligence, automation and process redesign, human–AI collaboration and changing managerial roles, ethical and governance risks, and future-oriented organizational capability building. Participants described AI as a strategic management infrastructure rather than a simple technological tool. They emphasized that AI improves speed, prediction, monitoring, and evidence-based decision-making, but also introduces risks related to opacity, bias, employee resistance, excessive dependence on algorithms, data privacy, and accountability ambiguity. Artificial intelligence is transforming management systems by shifting organizations from experience-based, hierarchical, and reactive management toward data-driven, adaptive, and predictive forms of coordination. However, this transformation requires responsible governance, managerial reskilling, transparent algorithms, human oversight, and organizational cultures that balance automation with human judgment.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">artificial intelligence</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">management systems</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">digital transformation</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">organizational decision-making</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">AI governance</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">qualitative study</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.msels.com/index.php/msels/article/download/63/54</ArchiveCopySource>
  </Article>
</ArticleSet>
