Author: Ahmed Mohamed Ajredi¹              Author: Dr. Mohamed Ali S Ajredi²

Affiliation: Faculty of Information Technology, Zawia University, Az Zawia, Libya¹

Affiliation: Faculty of Economic, Zawia University, Az Zawia, Libya²

Corresponding author email: a.ajredi@zu.edu.ly¹             m.ajredi@zu.edu.ly²

ORCID: https://orcid.org/0009-0009-7459-4108¹        : https://orcid.org/0009-0005-4608-5905²

Abstract:

Purpose: This study develops and empirically evaluates an integrated AI-enabled business process management (BPM) capability framework that explains how BPM capability, IT integration, process mining, AI capability and intelligent automation combine to improve business process performance. It responds to a gap between technology-specific studies and the organizational capability perspective needed to understand how these technologies work together.

Design/methodology/approach: A quantitative cross-sectional organizational survey was conducted in Libya. From 578 questionnaires received, 78 were removed using predefined data-quality criteria, yielding 500 valid responses from managers and professionals across banking and financial services, oil and gas, telecommunications, government, manufacturing, logistics and other sectors. The model was estimated with PLS-SEM in SmartPLS 4 using 10,000 BCa bootstrap subsamples.

Findings: All five antecedent capabilities significantly predict AI-enabled BPM capability. AI capability is the strongest antecedent (β = 0.283), followed by process mining (β = 0.224), intelligent automation (β = 0.195), BPM capability (β = 0.187) and IT integration (β = 0.165). AI-enabled BPM strongly predicts business process performance (β = 0.551, p < 0.001). The mediation analysis shows indirect-only mediation for BPM, process mining and intelligent automation, and complementary partial mediation for IT integration and AI capability. Measurement quality, discriminant validity, collinearity and predictive assessment are satisfactory.

Originality: The study conceptualizes AI-enabled BPM as a distinct integrative organizational capability rather than as isolated AI adoption, process mining or automation. It provides empirical evidence from an underrepresented emerging-market setting and shows that process performance gains depend on orchestrating technological and managerial capabilities through an AI-enabled BPM mechanism.

Keywords: AI-enabled BPM; business process management; process mining; artificial intelligence capability; intelligent automation; business process performance; dynamic capabilities; Libya

Article classification: Research paper