Creating AI business value through BPM capabilities

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

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.

• Language: English
• Keywords: business process, information technology, artificial intelligence, IT business value, firm performance, business process automation, business process innovation, organisational learning, BPM capabilities, business process performance
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: EF - School of Economics and Business
• Publication status: Published
• Publication version: Version of Record
• Year: 2024
• Number of pages: Str. 1-26
• Numbering: Vol. 30, no. 8
• PID: 20.500.12556/RUL-156198
• UDC: 659.2
• ISSN on article: 1463-7154
• DOI: 10.1108/BPMJ-07-2023-0566
• COBISS.SI-ID: 192624899
• Publication date in RUL: 13.05.2024

Record is a part of a journal

• Title: Business process management journal
• Shortened title: Bus. process. manag. j.
• Publisher: Emerald
• ISSN: 1463-7154
• COBISS.SI-ID: 78187520

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: poslovni proces, informacijska tehnologija, umetna inteligenca

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: P2-0037
• Name: Tehnologije interneta prihodnosti: koncepti, arhitekture, storitve in družbeno-ekonomski vidiki