Artificial intelligence assimilation shapes sustainable performance through dynamic capabilities

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Authors: Mingyang Zhang, Wenwen Dong
Cited by: 1
References: 94

Abstract

Beyond the hype of disruptive technologies, achieving sustainability requires assimilating artificial intelligence (AI) into organizational dynamic capabilities. Yet conflicting evidence on the sustainability outcomes of AI assimilation (AIA) motivates this study to unveil its underlying capability logic. Grounded in the Natural Resource-Based View and Dynamic Capabilities Theory, this study employs meta-analytic structural equation modeling (MASEM) to systematically investigate the intrinsic mechanisms through which AIA affects firms’ sustainable performance (SP). The findings reveal several key insights. First, AIA directly enhances SP and exerts indirect effects through the multiple mediating pathways of organizational agility (OA), green innovation (GI), and organizational resilience (OR). Second, GI serves as a core mediating pathway, playing a pivotal role in connecting AIA with sustainable development goals. Third, OA generates performance gains through short-cycle resource reconfiguration, whereas OR provides stable support in uncertain environments; these two capabilities exhibit complementary characteristics across different time scales. Finally, the research elucidates the complete pathway wherein AIA influences SP through the serial mediation of OA, GI, and OR. This reveals the underlying logic of how AI drives sustainable development through the evolution of dynamic capabilities. By integrating findings across existing studies, this research helps to reconcile discrepancies in prior conclusions. It provides a novel theoretical explanation for understanding the complex mechanisms of AI-enabled corporate sustainable development and also offers practical implications for businesses advancing digital and intelligent transformation.

Fields of Study & Subjects

Ecosystem dynamics and resilience Innovation Sustainability Human-Machine Systems Earth Systems and Cosmic Evolution

Publication details

Journal / source
Scientific Reports
Publisher
Springer Science and Business Media LLC
Volume
16
Issue
1
Publication date
8 April 2026
Language
EN