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Exploring the artificial intelligence integration in top management team decision-making: an empirical analysis

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F04130081%3A_____%2F25%3AN0000013" target="_blank" >RIV/04130081:_____/25:N0000013 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27350/25:10259102

  • Result on the web

    <a href="https://www.emerald.com/bpmj/article-abstract/31/5/1763/1252656/Exploring-the-artificial-intelligence-integration?redirectedFrom=fulltext" target="_blank" >https://www.emerald.com/bpmj/article-abstract/31/5/1763/1252656/Exploring-the-artificial-intelligence-integration?redirectedFrom=fulltext</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1108/BPMJ-07-2024-0659" target="_blank" >10.1108/BPMJ-07-2024-0659</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Exploring the artificial intelligence integration in top management team decision-making: an empirical analysis

  • Original language description

    PurposeDrawing on upper echelons theory (UET), this study empirically explores how artificial intelligence (AI) has influenced the top management team's (TMT) decision-making process in business management.Design/methodology/approachThis article is based on 21 semi-structured interviews with top managers leading AI integration in their organizations. It adopts an inductive approach and applies the Gioia methodology.FindingsThe research identifies four primary areas of impact of AI for TMTs in managing digital business processes: (1) hybrid decision-making process, (2) AI's ethical implications, (3) TMT governance through AI, and (4) AI-driven competitive advantage. Also, a framework has been developed that provides an initial understanding of how integrating AI in organizations affects the TMT's decision-making process.Practical implicationsThe study provides practical insights for the TMT leveraging AI technologies to enhance decision-making in managing business processes. Additionally, it offers helpful guidance for organizations to stay at the forefront of innovation and adaptability in an ever-evolving world.Originality/valueOur findings highlight the critical role of TMT's decision-making in managing business processes transformed by AI. Moreover, the study extends the UET, highlighting how the integration of AI influences the TMT's decision-making process and how ethical implications impact these decisions and business management.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    50204 - Business and management

Result continuities

  • Project

  • Continuities

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    BUSINESS PROCESS MANAGEMENT JOURNAL

  • ISSN

    1463-7154

  • e-ISSN

    1758-4116

  • Volume of the periodical

    31

  • Issue of the periodical within the volume

    5

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    22

  • Pages from-to

    1763-1784

  • UT code for WoS article

    001473362300001

  • EID of the result in the Scopus database

    2-s2.0-105003191834