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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">IJLTEMAS</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Latest Technology in Engineering, Management &amp; Applied Science (IJLTEMAS)</journal-title>
        <abbrev-journal-title abbrev-type="publisher">IJLTEMAS</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">2278-2540</issn>
      <publisher>
        <publisher-name>IJLTEMAS</publisher-name>
      </publisher>
    </journal-meta>

    <article-meta>
      <!-- IDs -->
      <article-id pub-id-type="publisher-id">51</article-id>
            <article-id pub-id-type="doi">10.51583/IJLTEMAS.2026.150700046</article-id>
      
      <!-- Categories -->
            <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Security</subject>
        </subj-group>
      </article-categories>
      
      <!-- Title -->
      <title-group>
        <article-title>Future Job Security Concerns for Librarians, Records Management, and Health Information Professionals in the Age of Artificial Intelligence</article-title>
      </title-group>

      <!-- Authors -->
      <contrib-group>
                <contrib contrib-type="author">
                    <name>
            <surname>Chukwu Nwali PhD. Cln</surname>
            <given-names>Victoria</given-names>
          </name>
                              <aff>
            Ebonyi State University Abakaliki Ebonyi State                        <country>Nigeria</country>
                      </aff>
                    
        </contrib>
                <contrib contrib-type="author">
                    <name>
            <surname>J. Udumukwu. PhD. Cln</surname>
            <given-names>Ifeyinwa.</given-names>
          </name>
                              <aff>
            Donald Ekong Library, University of Port Harcourt Rivers State                        <country>Nigeria</country>
                      </aff>
                    
        </contrib>
              </contrib-group>

      <!-- Volume / Issue / Pages -->
            <volume>15</volume>
                  <issue>7</issue>
                        <fpage>562</fpage>
            <lpage>573</lpage>
            
      <!-- Dates -->
      <history>
                <date date-type="received">
          <day>28</day>
          <month>07</month>
          <year>2026</year>
        </date>
                        <date date-type="accepted">
          <day>03</day>
          <month>08</month>
          <year>2026</year>
        </date>
              </history>

            <pub-date pub-type="epub">
        <day>08</day>
        <month>08</month>
        <year>2026</year>
      </pub-date>
      
      <!-- DOI Self-URI -->
            <self-uri xlink:href="https://doi.org/10.51583/IJLTEMAS.2026.150700046"/>
      
      <!-- Keywords -->
            <kwd-group kwd-group-type="author">
                <kwd>artificial intelligence</kwd>
                <kwd>job security</kwd>
                <kwd>librarians</kwd>
                <kwd>records management</kwd>
                <kwd>health information professionals</kwd>
              </kwd-group>
      
    </article-meta>
  </front>

  <!-- ============================================================ BODY (Abstract) -->
  <body>
        <sec>
      <title>Abstract</title>
      <p>The rapid proliferation of artificial intelligence (AI) technologies, robotic process automation (RPA), and intelligent document management systems is fundamentally reshaping the landscape of information professions. This paper examines job security concerns among three closely related professional groups — librarians, records management professionals, and health information professionals (HIPs) — in the context of accelerating digital transformation. Drawing on a synthesis of empirical data, workforce projections, and expert discourse, this study investigates the nature, extent, and drivers of job insecurity within these professions, as well as the adaptive strategies being employed in response. Findings indicate that between 55% and 87% of core tasks within these professions carry moderate to high automation risk, with health information management and routine records functions being the most exposed. Despite these threats, the study identifies significant opportunities for professional reinvention through strategic upskilling, ethical AI stewardship, and policy engagement. The paper concludes with a framework of recommendations for professional associations, higher education institutions, and individual practitioners.</p>
    </sec>
      </body>

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