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    <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">208</article-id>
            <article-id pub-id-type="doi">10.51583/IJLTEMAS.2026.150800014</article-id>
      
      <!-- Categories -->
            <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artificial Intelligence</subject>
        </subj-group>
      </article-categories>
      
      <!-- Title -->
      <title-group>
        <article-title>The Legal and Ethical Grey Area of Skill Ownership in the Era of Generative AI</article-title>
      </title-group>

      <!-- Authors -->
      <contrib-group>
                <contrib contrib-type="author">
                    <name>
            <surname>Esha</surname>
            <given-names>Esha</given-names>
          </name>
                              <aff>
            Assistant Professor, Department of Management, Oxford Business College, Patna, Bihar, India                        <country>India</country>
                      </aff>
                    
        </contrib>
              </contrib-group>

      <!-- Volume / Issue / Pages -->
            <volume>15</volume>
                  <issue>8</issue>
                        <fpage>217</fpage>
            <lpage>221</lpage>
            
      <!-- Dates -->
      <history>
                <date date-type="received">
          <day>20</day>
          <month>08</month>
          <year>2026</year>
        </date>
                        <date date-type="accepted">
          <day>25</day>
          <month>08</month>
          <year>2026</year>
        </date>
              </history>

            <pub-date pub-type="epub">
        <day>03</day>
        <month>09</month>
        <year>2026</year>
      </pub-date>
      
      <!-- DOI Self-URI -->
            <self-uri xlink:href="https://doi.org/10.51583/IJLTEMAS.2026.150800014"/>
      
      <!-- Keywords -->
            <kwd-group kwd-group-type="author">
                <kwd>Skill ownership</kwd>
                <kwd>legal and ethical concerns</kwd>
                <kwd>intellectual property</kwd>
                <kwd>psychological contract</kwd>
                <kwd>employee right</kwd>
                <kwd>employment law</kwd>
                <kwd>generative AI.</kwd>
              </kwd-group>
      
    </article-meta>
  </front>

  <!-- ============================================================ BODY (Abstract) -->
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        <sec>
      <title>Abstract</title>
      <p>The rapid integration of generative - AI into an organisation create a challenge for the workforce. AI based system become capable of replicating human technique ranging from complex into artistic style. The critical grey area has most regarding the ownership of human skill. This study examine the issue of skill ownership in the age of generative AI from legal and ethical perspective. Employee developed  the knowledge &amp; expertise after spending number of years. when their skills, work pattern and professional knowledge are used to train or develop organisational AI system, the boundary between the individual contribution and organisational ownership should become unclear. This practice leaves many workers feeling as though their life’s work is being harvested to build their own automated replacements.It explore a clear question regarding the intellectual property, privacy, ownership, consent, and the moral responsibility of any organisation employee knowledge is converted into AI based system. Through qualitative approach, research aims to understand the experience and perception of employee and identify the challenges facing by the organisation to identify whether the work is completed by AI or it is done by employee. This ambiguity not only complicates performance evaluation, but it also creates an environment of mutual suspicion where human authenticity must constantly be proven.An organisation also faces challenges in balancing technological innovation with employee rights and ethical responsibility. The research considered for the employee may perceive the trust, job security, fairness, and psychological contract.</p>
    </sec>
      </body>

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