Articlehybrid2024

Creating AI business value through BPM capabilities

44 citations0/0 files storedBusiness Process Management Journal

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Impact of AI and Big Data on Business and Society Information Technology Governance and Strategy Robotic Process Automation Applications

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.

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References

1981Evaluating Structural Equation Models with Unobservable Variables and Measurement Error 2014A new criterion for assessing discriminant validity in variance-based structural equation modeling 1991Exploration and Exploitation in Organizational Learning 2000Dynamic capabilities: what are they?1977Estimating Nonresponse Bias in Mail Surveys 2003A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research 2000A model for types and levels of human interaction with automation 2002SOMETHING OLD, SOMETHING NEW: A LONGITUDINAL STUDY OF SEARCH BEHAVIOR AND NEW PRODUCT INTRODUCTION.

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