Aleš Zebec (Author), Mojca Indihar Štemberger (Author)

Abstract

Purpose - Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities. Design/methodology/approach - The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU. Findings - The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value. Research limitations/implications - In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined. Practical implications - The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value. Originality/value - While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

Keywords

poslovni proces;informacijska tehnologija;umetna inteligenca;business process;information technology;artificial intelligence;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL EF - Faculty of Economics
UDC: 659.2
COBISS: 192624899 Link will open in a new window
ISSN: 1463-7154
Views: 49
Downloads: 12
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Other data

Secondary language: Slovenian
Secondary keywords: poslovni proces;informacijska tehnologija;umetna inteligenca;
Type (COBISS): Article
Pages: str. 1-26
Volume: ǂVol. ǂ30
Issue: ǂiss. ǂ8
Chronology: 2024
DOI: 10.1108/BPMJ-07-2023-0566
ID: 23668384