Preprint: Human-AI Co-Evolution in Industrial Organizations: A Comparative Analysis of AI Adoption in Manufacturing and Business Functions in the Trinational Upper Rhine Region

Abstract

This study examines organizational and human drivers of AI adoption and perceived organizational value in industrial organizations in the Trinational Upper Rhine Region, focusing on AI leadership, AI competencies, trust in AI, AI readiness, digital maturity, and explainable AI (XAI). Following a literature review and conceptual model development, a multilingual survey was conducted among professionals in the Trinational Upper Rhine Region. The proposed relationships were examined using Partial Least Squares Structural Equation Modeling (PLS-SEM), complemented by Measurement Invariance of Composite Models (MICOM) and Multi-Group Analysis (MGA). AI leadership positively influences AI competencies (β = .291, p < .001) and trust in AI (β = .335, p < .001), which subsequently enhance AI adoption. AI readiness (β = .285, p < .001) and digital maturity (β = .189, p = .002) further drive adoption. Most notably, AI adoption strongly contributes to perceived organizational value (β = .564, p < .001), whereas XAI shows no significant direct effect. The study integrates leadership, human capabilities, and organizational conditions within a unified AI adoption framework, providing cross-border empirical evidence on how organizations translate AI adoption into organizational value.