<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName>The Research Department of Economics and Management of Tadbir Nikan</PublisherName>
      <JournalTitle>Business, Marketing, and Finance Open</JournalTitle>
      <Issn></Issn>
      <Volume>3</Volume>
      <Issue>Serial Number 13</Issue>
      <PubDate PubStatus="epublish">
        <Year>2026</Year>
        <Month>01</Month>
        <Day>06</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Examining the Challenges and Opportunities of Artificial Intelligence in the Accounting Profession in Iran</ArticleTitle>
    <VernacularTitle>Examining the Challenges and Opportunities of Artificial Intelligence in the Accounting Profession in Iran</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>10</LastPage>
    <ELocationID EIdType="doi">10.61838/bmfopen.264</ELocationID>
    <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>2025</Year>
        <Month>03</Month>
        <Day>10</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;The present study investigates the challenges and opportunities of artificial intelligence (AI) in the accounting profession in Iran. This is a mixed-methods research in which thematic analysis was employed for the qualitative phase, and a descriptive-survey method was used in the quantitative phase. Data collection methods included both library and field approaches. Data collection tools consisted of questionnaires and interviews. The statistical population comprised professionals in the Iranian accounting field. Using purposive sampling through theoretical saturation, 13 academic experts were selected for the qualitative phase. In the quantitative phase, a simple random sampling method was employed, and based on Morgan’s table, a sample size of 200 participants was determined. The identified model was analyzed using structural equation modeling and the software packages SmartPLS (version 3) and SPSS (version 23). The research findings revealed that the most significant opportunities provided by AI, in order of priority, include intelligent accounting, cost management, reduction of human errors, and online auditing. The most critical challenges identified include data insecurity, increased fraud, failure to implement organizational policies, and uncertainty. Accordingly, to benefit from artificial intelligence, the Iranian accounting profession must take the identified components into serious consideration.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Artificial Intelligence</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Accounting</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Auditing</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.bmfopen.com/index.php/bmfopen/article/download/264/281</ArchiveCopySource>
  </Article>
</ArticleSet>
