Artificial Intelligence and Sustainable Performance: A Sequential Mediation Model of Green Innovation and Technology Deployment

Purpose—Artificial Intelligence (AI) is increasingly recognized as a catalyst for business transformation and sustainability. However, its role in enhancing Sustainable Performance particularly within the context of Small and Medium-Sized Enterprises (SMEs) in developing economies—remains underexamined. This study investigates how AI Capability drives Sustainable Performance through the sequential mediating roles of Green Innovation and Technology Deployment in Pakistani SMEs). Study Design/methodology/approach—Drawing on the Resource-Based View (RBV) and Technology-Organization-Environment (TOE) framework, this study adopts a quantitative research design. Data were collected via structured questionnaires from 450 SMEs operating across key industrial sectors in Pakistan. The hypothesized sequential mediation model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore the pathways linking AI Capability to Sustainable Performance. Findings—The results confirm a significant sequential mediation effect: AI Capability positively influences Green Innovation, which enhances Technology Deployment, ultimately leading to improved Sustainable Performance. All direct and indirect relationships were statistically significant, highlighting the critical role of innovation and technology integration in translating AI potential into tangible sustainability outcomes for SMEs. Research Practical Implications— This study implies that artificial intelligence can act as a catalyst for green innovation and technology deployment, thereby enhancing sustainable performance. The findings provide valuable insights for policymakers and managers to embed AI-driven strategies into sustainability agendas and environmental practices. Originality/value—This research makes a novel contribution by proposing and validating a dual-process mediation model that explains how AI investments foster sustainable development in the SME sector of a developing economy. Unlike prior studies that address these variables in isolation, this study presents an integrated and empirically validated framework. The findings offer actionable insights for Pakistani SME managers and policymakers seeking to leverage AI for economic growth, environmental responsibility, and long-term competitiveness.