<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>4224</id>
    <completedYear>2025</completedYear>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>26</pageNumber>
    <edition/>
    <issue>1</issue>
    <volume>38</volume>
    <type>article</type>
    <publisherName>IGI Global</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2025-08-07</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">ChatGPT in the Working World: A Qualitative Study</title>
    <abstract language="eng">The authors investigated how ChatGPT transforms workplace tasks by analyzing qualitative survey responses from 78 U.S. professionals in the fields of software, marketing, and academia. This study addresses a gap in understanding the malleability of generative artificial intelligence in diverse professional contexts, a need underscored by ChatGPT’s rapid adoption and mixed impact on work practices. Using a qualitative survey deployed via a validated platform, the authors collected open-ended responses about tasks, challenges, and opportunities. Responses were inductively coded to compare domain-specific applications. The findings show that although ChatGPT is widely used across sectors for tasks such as content creation, research, and idea generation, certain tasks—such as coding in software, strategic communication in marketing, and knowledge acquisition in academia—diverge. The results emphasize the importance of context-sensitive integration strategies and bottom-up adoption approaches to maximize the benefits of artificial intelligence while mitigating risks.</abstract>
    <parentTitle language="eng">Information Resources Management Journal (IRMJ)</parentTitle>
    <identifier type="doi">10.4018/IRMJ.386593</identifier>
    <enrichment key="Reviewstatus">Begutachtet/Reviewed</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY-SA - Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Pedro Schötteler Libera</author>
    <author>Volker Bilgram</author>
    <author>Sebastian Schötteler</author>
    <author>Jan Mammen</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Generative AI</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Technology Adoption</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Human-AI Interaction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Organizational Malleability</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Qualitative Research</value>
    </subject>
    <collection role="institutes" number="">Fakultät Maschinenbau und Versorgungstechnik</collection>
    <collection role="institutes" number="">Fakultät Betriebswirtschaft</collection>
    <collection role="Forschungsschwerpunkt" number="5">Digitalisierung &amp; Künstliche Intelligenz</collection>
    <collection role="Forschungsschwerpunkt" number="7">Soziale &amp; ökonomische Transformation</collection>
  </doc>
</export-example>
