TY - JOUR
T1 - Artificial intelligence-powered innovation strategies for ESG impact and sustainable ecosystems: A natural-resource-based and environmental-legitimacy perspective
AU - Alkaraan, Fadi
AU - Elmarzouky, Mahmoud
AU - Venkatesh , V.G.
AU - Hussainey, Khaled
AU - Shi, Yangyan
AU - Zhang, Min
PY - 2026/1/27
Y1 - 2026/1/27
N2 - Artificial Intelligence (AI) serves as a core driver of Industry 4.0 Technologies (I4.0Ts), enabling advanced digital capabilities across industrial ecosystems. This study advances the understanding of Environmental Business Innovation Strategies (Env-BISs) by examining the synergistic interplay between Circular Economy Strategy Practices (CESPs), the integration of AI into I4.0Ts, and governance structures (GS) within the UK context. Grounded in the Natural-Resource-Based View (NRBV) and Environmental Legitimacy Theory, we adopt a robust mixed-methods research design that integrates macro, meso, and micro-level data sources. The empirical analysis draws on the UK Innovation Survey (2023) covering 32,273 firms (released May 2024), data over the period (2012–2021) from FTSE All-Share companies, and narrative disclosures from 2023 annual reports of sector-leading firms. Our findings reveal that AI-powered I4.0Ts are critical enablers of CESPs, collectively accelerating the adoption of Env-BISs and enhancing firms’ ESG and ecosystem-related performance. The use of AI within I4.0Ts is positively associated with the implementation of CESPs, which, in turn, fosters circular ecosystem innovation. Furthermore, internal and external GS significantly moderate the relationship between AI-enabled I4.0Ts and CESPs, reinforcing the strategic alignment of digital transformation with sustainability objectives. The study provides actionable insights for managers aiming to operationalise ESG principles through AI-driven innovation and cross-functional integration. It also highlights the importance of standardised ESG metrics and AI-based assessment tools to address ESG reporting performance decoupling and strengthen stakeholder trust. By bridging theoretical, empirical, and practical domains, this research contributes to the Env-BISs literature and offers a strategic pathway for firms and policymakers to drive sustainable business model transformation toward circular ecosystems in a globally competitive environment.
AB - Artificial Intelligence (AI) serves as a core driver of Industry 4.0 Technologies (I4.0Ts), enabling advanced digital capabilities across industrial ecosystems. This study advances the understanding of Environmental Business Innovation Strategies (Env-BISs) by examining the synergistic interplay between Circular Economy Strategy Practices (CESPs), the integration of AI into I4.0Ts, and governance structures (GS) within the UK context. Grounded in the Natural-Resource-Based View (NRBV) and Environmental Legitimacy Theory, we adopt a robust mixed-methods research design that integrates macro, meso, and micro-level data sources. The empirical analysis draws on the UK Innovation Survey (2023) covering 32,273 firms (released May 2024), data over the period (2012–2021) from FTSE All-Share companies, and narrative disclosures from 2023 annual reports of sector-leading firms. Our findings reveal that AI-powered I4.0Ts are critical enablers of CESPs, collectively accelerating the adoption of Env-BISs and enhancing firms’ ESG and ecosystem-related performance. The use of AI within I4.0Ts is positively associated with the implementation of CESPs, which, in turn, fosters circular ecosystem innovation. Furthermore, internal and external GS significantly moderate the relationship between AI-enabled I4.0Ts and CESPs, reinforcing the strategic alignment of digital transformation with sustainability objectives. The study provides actionable insights for managers aiming to operationalise ESG principles through AI-driven innovation and cross-functional integration. It also highlights the importance of standardised ESG metrics and AI-based assessment tools to address ESG reporting performance decoupling and strengthen stakeholder trust. By bridging theoretical, empirical, and practical domains, this research contributes to the Env-BISs literature and offers a strategic pathway for firms and policymakers to drive sustainable business model transformation toward circular ecosystems in a globally competitive environment.
M3 - Article
SN - 1099-0836
JO - Business Strategy and the Environment
JF - Business Strategy and the Environment
ER -
