<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Future of Work and Digital Management Journal</JournalTitle>
      <Issn>3092-720X</Issn>
      <Volume>4</Volume>
      <Issue>Serial Number 12</Issue>
      <PubDate PubStatus="epublish">
        <Year>2026</Year>
        <Month>03</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Design and Explanation of an Artificial-Intelligence-Based Human Resource Management Model</ArticleTitle>
    <VernacularTitle>Design and Explanation of an Artificial-Intelligence-Based Human Resource Management Model</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>17</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>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2025</Year>
        <Month>08</Month>
        <Day>14</Day>
      </PubDate>
    </History>
    <Abstract>&lt;table&gt;
&lt;tbody&gt;
&lt;tr&gt;
&lt;td&gt;
&lt;p&gt;The purpose of this article is to design and explain a human resource management model based on artificial intelligence technology. The present study is a developmental and applied research project; however, given the research procedure, it incorporates a combination of documentary, descriptive, and causal research methods. In this study, library and internet sources—including books, articles, and case studies—as well as field studies, specifically interviews with experts and specialists, were used to propose, design, and validate an AI-based human resource management model. The collected data were analyzed using MAXQDA software. The results of data analysis in the qualitative phase led to the extraction of an appropriate model for AI-based human resource management. The extracted model includes five main dimensions, twelve core categories, and fifty-one subcategories or indicators. In the structural modeling section, the model was examined and validated through MICMAC software, and the results indicate that the variable “process and policy optimization using intelligent algorithms and models” has the highest level of influence. Moreover, the variable “optimization of communication structures and establishment of organizational justice” ranks second in terms of influence. Finally, the variables “assessment and prediction of employee motivation and behavior” rank third, “forward-looking planning for learning, growth, and innovation in the organization” rank fourth, and “performance evaluation and improvement through e-learning” rank fifth in influencing the AI-based human resource management model.&lt;/p&gt;
&lt;/td&gt;
&lt;/tr&gt;
&lt;/tbody&gt;
&lt;/table&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">model design</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">human resource management</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">artificial intelligence</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">futures studies</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalfwdmj.com/index.php/fwdmj/article/download/194/300</ArchiveCopySource>
  </Article>
</ArticleSet>
