<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article">
 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">
    ojbm
   </journal-id>
   <journal-title-group>
    <journal-title>
     Open Journal of Business and Management
    </journal-title>
   </journal-title-group>
   <issn pub-type="epub">
    2329-3284
   </issn>
   <issn publication-format="print">
    2329-3292
   </issn>
   <publisher>
    <publisher-name>
     Scientific Research Publishing
    </publisher-name>
   </publisher>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="doi">
    10.4236/ojbm.2024.126213
   </article-id>
   <article-id pub-id-type="publisher-id">
    ojbm-137491
   </article-id>
   <article-categories>
    <subj-group subj-group-type="heading">
     <subject>
      Articles
     </subject>
    </subj-group>
    <subj-group subj-group-type="Discipline-v2">
     <subject>
      Business 
     </subject>
     <subject>
       Economics
     </subject>
    </subj-group>
   </article-categories>
   <title-group>
    The Tayloristic Trap: How Automation in Recruitment Fails to Identify Transformative Leaders?
   </title-group>
   <contrib-group>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Marijana
      </surname>
      <given-names>
       Karanfiloska
      </given-names>
     </name>
    </contrib>
   </contrib-group> 
   <aff id="affnull">
    <addr-line>
     aSBS Swiss Business School, Kloten, Switzerland
    </addr-line> 
   </aff> 
   <pub-date pub-type="epub">
    <day>
     17
    </day> 
    <month>
     10
    </month>
    <year>
     2024
    </year>
   </pub-date> 
   <volume>
    12
   </volume> 
   <issue>
    06
   </issue>
   <fpage>
    4254
   </fpage>
   <lpage>
    4259
   </lpage>
   <history>
    <date date-type="received">
     <day>
      22,
     </day>
     <month>
      October
     </month>
     <year>
      2024
     </year>
    </date>
    <date date-type="published">
     <day>
      17,
     </day>
     <month>
      October
     </month>
     <year>
      2024
     </year> 
    </date> 
    <date date-type="accepted">
     <day>
      17,
     </day>
     <month>
      November
     </month>
     <year>
      2024
     </year> 
    </date>
   </history>
   <permissions>
    <copyright-statement>
     © Copyright 2014 by authors and Scientific Research Publishing Inc. 
    </copyright-statement>
    <copyright-year>
     2014
    </copyright-year>
    <license>
     <license-p>
      This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/
     </license-p>
    </license>
   </permissions>
   <abstract>
    This opinion paper examines the growing reliance on automation and AI in recruitment processes, particularly for managerial roles. While these technologies streamline hiring by filtering candidates based on predefined criteria, they often perpetuate a Tayloristic approach that favours standardisation and efficiency over creativity and innovation. As a result, unconventional candidates with diverse experiences and critical soft skills are excluded, leading to leadership homogeneity. The paper argues that organisations must rethink their recruitment strategies, moving away from rigid automation towards a more human-centric approach that values emotional intelligence, adaptability, and diverse perspectives in leadership selection.
   </abstract>
   <kwd-group> 
    <kwd>
     Taylorism
    </kwd> 
    <kwd>
      Recruitment
    </kwd> 
    <kwd>
      Automation
    </kwd> 
    <kwd>
      HRM
    </kwd> 
    <kwd>
      HRM Challenges
    </kwd> 
    <kwd>
      Leader
    </kwd>
   </kwd-group>
  </article-meta>
 </front>
 <body></body><back>
  <ref-list>
   <title>References</title>
   <ref id="scirp.137491-ref1">
    <label>1</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Bessen, J. (2019). AI and Jobs: The Role of Demand. MIT Press.
    </mixed-citation>
   </ref>
   <ref id="scirp.137491-ref2">
    <label>2</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Bock, L. (2015). Work Rules! Insights from Inside Google That Will Transform How You Live and Lead. Twelve. 
    </mixed-citation>
   </ref>
   <ref id="scirp.137491-ref3">
    <label>3</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Braverman, H. (1998). Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century. Monthly Review Press.
    </mixed-citation>
   </ref>
   <ref id="scirp.137491-ref4">
    <label>4</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Chamorro-Premuzic, T. (2021). I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique. Harvard Business Review Press.
    </mixed-citation>
   </ref>
   <ref id="scirp.137491-ref5">
    <label>5</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Chamorro-Premuzic, T.,&amp;Yearsley, A. (2017). The Talent Delusion: Why Data, Not Intuition, Is the Key to Unlocking Human Potential. Piatkus.
    </mixed-citation>
   </ref>
   <ref id="scirp.137491-ref6">
    <label>6</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Gerlich, M. (2023). Beyond the Paycheck: Navigating the New Era of Employee Expectations. In Enhancing Employee Engagement and Productivity in the Post-Pandemic Multigenerational Workforce (pp. 125-155). IGI Global.
    </mixed-citation>
   </ref>
   <ref id="scirp.137491-ref7">
    <label>7</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Gerlich, M. (2024). Exploring Motivators for Trust in the Dichotomy of Human—AI Trust Dynamics. Social Sciences, 13, Article No. 251. &gt;https://doi.org/10.3390/socsci13050251
    </mixed-citation>
   </ref>
   <ref id="scirp.137491-ref8">
    <label>8</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group.
    </mixed-citation>
   </ref>
  </ref-list>
 </back>
</article>