Artificial intelligence-driven green innovation for sustainable development: Empirical insights from India's renewable energy transition

Behera B., Behera P., PATA U. K., Sethi L., Sethi N.

Journal of Environmental Management, cilt.389, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 389
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1016/j.jenvman.2025.126285
  • Dergi Adı: Journal of Environmental Management
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, International Bibliography of Social Sciences, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Communication Abstracts, Environment Index, Geobase, Greenfile, Index Islamicus, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Artificial intelligence, Green growth, Green technology innovation, Renewable energy transition, Sustainable development goals
  • Recep Tayyip Erdoğan Üniversitesi Adresli: Hayır

Özet

This paper explores the contribution of artificial intelligence (AI), green technology innovation (GTI), and renewable energy generation (REG) to sustainable development in India, with a specific focus on their alignment with the Sustainable Development Goals (SDGs). Employing data from 1987 to 2020 and applying the Dynamic ARDL simulation approach, the study analyzes both direct and moderating effects of AI on green growth. The outcomes illustrate that while REG alone has a statistically insignificant impact on green growth (0.073 %), AI and GTI significantly promote long-term green growth. Specifically, AI contributes 0.241 % and GTI 0.163 % to long-term green growth, supporting SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure). Moreover, interaction effects show that AI significantly enhances the effectiveness of REG (with an interaction coefficient of 0.017 %), facilitating a cleaner energy transition in line with SDG 7 (Affordable and Clean Energy). Similarly, AI enhances the contribution of GTI (with an interaction coefficient of 0.041 %), reinforcing environmental quality in support of SDG 13 (Climate Action). Robustness checks via the KRLS estimator confirm these relationships. Policy implications suggest that integrating AI into energy and innovation policies can amplify sustainability outcomes. Hence, a coordinated strategy encompassing digital transformation, technology financing, and institutional support is essential for India to meet its SDG targets and transition toward a low-carbon, innovation-driven economy.