AI Adoption and Sustainable Development in Advancing SDG 9 and SDG 13 in Emerging Economies

Evidence From the E7

Bibliographic Data

ID12305835
AuthorsSnovia Naseem (0000-0002-2463-1048, School of Economics and Management Fuzhou University Fuzhou Fujian China), Tang Yong (0009-0009-8682-5217, School of Economics and Management Fuzhou University Fuzhou Fujian China, corresponding author), Samina Riaz (0000-0002-8933-0836, Bahria University Karachi Karachi Pakistan), Khurshid Khudoykulov (0000-0003-3105-9358, Department of Finance and Tourism Termez University of Economics and Service Termez Uzbekistan)
Year2026
Publication date2026-04-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSustainable Development (JOURNAL)
Journal identifiersISSN: 0968-0802 • E-ISSN: 1099-1719
PublisherWiley (PUBLISHER • GB)
DOI10.1002/sd.71033
OpenAlexW7147442934
LanguageEN
References cited27

Artificial intelligence (AI) adoption is increasingly viewed as a driver of productivity and competitiveness, yet its sustainability implications remain underexplored, particularly in emerging economies where environmental constraints and digital gaps persist. This study examines how supply chain digitization (SCD), globalization, environmental pressures, green technologies, and energy structure jointly shape AI adoption in the E7 economies over the period 2000–2022. Using Method of Moments Quantile Regression as the baseline model, the analysis captures heterogeneous effects across different adoption levels, while robustness is ensured through alternative quantile specifications. The results reveal that SCD consistently promotes AI adoption, whereas carbon emissions hinder adoption at lower quantiles. Environment‐related technologies and cleaner energy structures mitigate these constraints, enabling more sustainable diffusion of AI. Globalization contributes positively only when absorptive capacity is sufficiently developed. These findings suggest that AI strategies in emerging economies must be aligned with green technology investment, clean energy transitions, and digital infrastructure development, directly supporting Sustainable Development Goals 9 and 13

Digitization · Emerging markets · Globalization · Greenhouse gas · Productivity · Quantile regression · Robustness (evolution · Sustainability · Sustainable development · Digital Transformation in Industry · Energy, Environment, Economic Growth · Organizational and Employee Performance

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