<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Digital Transformation and Administration Innovation</JournalTitle>
      <Issn></Issn>
      <Volume>2</Volume>
      <Issue>Serial Number 3</Issue>
      <PubDate PubStatus="epublish">
        <Year>2024</Year>
        <Month>03</Month>
        <Day>10</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>The Role of Artificial Intelligence in Enhancing Customer Relationship Management (CRM) in Iranian Businesses</ArticleTitle>
    <VernacularTitle>The Role of Artificial Intelligence in Enhancing Customer Relationship Management (CRM) in Iranian Businesses</VernacularTitle>
    <FirstPage>113</FirstPage>
    <LastPage>121</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <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>2024</Year>
        <Month>01</Month>
        <Day>03</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p class="Abstract"&gt;&lt;span style="font-family: 'Palatino Linotype',serif;"&gt;This study aimed to examine the effect of Artificial Intelligence–enabled Customer Relationship Management on business performance through customer identification, acquisition, retention, and development. The research adopted an applied and developmental design using a mixed exploratory approach. The qualitative phase involved expert consultations to refine the conceptual framework, while the quantitative phase employed a survey methodology. The statistical population consisted of managers and specialists working in technology-based marketing and customer management roles within an Iranian insurance organization. A purposive sampling strategy was used, and data were collected through a structured questionnaire. The minimum sample size was determined using power analysis, resulting in 130 valid responses. Data analysis was conducted using SPSS and PLS software. Descriptive statistics were applied to assess data distribution, and reliability was confirmed through Cronbach’s alpha coefficients. Inferential analyses were performed using regression techniques to test the proposed hypotheses. The results indicated that Artificial Intelligence–enabled CRM has a significant positive effect on business performance across all examined dimensions. Customer identification through AI explained 41.7% of the variance in business performance (R² = 0.417, p &amp;lt; 0.001). Customer acquisition demonstrated a significant effect with an explanatory power of 41.1% (R² = 0.411, p &amp;lt; 0.001). Customer retention also showed a meaningful impact, accounting for 41.2% of performance variance (R² = 0.412, p &amp;lt; 0.001). Customer development exhibited the strongest effect on business performance (R² = 0.415, p &amp;lt; 0.001), indicating the critical role of AI-driven value expansion strategies. The findings confirm that Artificial Intelligence significantly enhances the effectiveness of Customer Relationship Management and contributes to improved business performance by strengthening analytical accuracy, relationship continuity, and customer value creation.&lt;/span&gt;&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Business</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Customer Relationship Management (CRM)</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Artificial Intelligence (AI)</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://journaldtai.com/index.php/jdtai/article/download/229/204</ArchiveCopySource>
  </Article>
</ArticleSet>
