A Systematic Review Integrating the Perspectives of Artificial Intelligence for Sustainability and Sustainability of Artificial Intelligence
Öz
While artificial intelligence technologies offer significant opportunities for achieving the Sustainable Development Goals (SDGs), they also present ethical, environmental, and economic challenges. This study provides a comprehensive systematic literature review that maps the dimensions of “AI for Sustainability” and “Sustainability of AI” within an integrated theoretical framework. Using the PRISMA methodology, 167 records were compiled from Web of Science, Scopus, and Google Scholar; after applying inclusion and exclusion criteria, 81 articles were analysed in depth. Studies focused primarily on engineering and technical computation were excluded to ensure alignment with the study’s social sciences and sustainability management orientation. Findings in the “AI for Sustainability” dimension reveal that AI makes significant contributions to SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure). However, empirical research on SDG 5 (Gender Equality), SDG 10 (Reduced Inequalities), and SDG 13 (Climate Action) remains insufficient, with social and environmental SDGs systematically underrepresented. In the “Sustainability of AI” dimension, the literature predominantly focuses on the ecological sub-theme (energy consumption and carbon emissions), while the organisational, social, and economic dimensions remain comparatively neglected. Notable findings include the context-dependent nature of energy-efficiency strategies and evidence that current AI infrastructure creates an unsustainable carbon lock-in. This study offers a thematic and normative mapping that addresses the limitations of prior reviews in integrating both dimensions. The findings point to three priorities: advancing empirical research on social sustainability, integrating a lifecycle perspective into ecological analyses, and examining the adaptability of governance models across diverse regional contexts.
Anahtar Kelimeler
Kaynakça
- Abulibdeh, A., Zaidan, E., & Abulibdeh, R. (2024). Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. Journal of Cleaner Production, 437. https://doi.org/10.1016/j.jclepro.2023.140527
- Adewale, B. A., Ene, V. O., Ogunbayo, B. F., & Aigbavboa, C. O. (2024). A systematic review of the applications of AI in a sustainable building’s lifecycle. Buildings, 14(7), Article 2137. https://doi.org/10.3390/buildings14072137
- Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial intelligence in sustainable energy industry: Status quo, challenges and opportunities. Journal of Cleaner Production, 289, Article 125834. https://doi.org/10.1016/j.jclepro.2021.125834
- Ali, S., Fapi, E. T., Jaumard, B., & Planche, A. (2024). Focus on Carbon Dioxide Footprint of AI/ML Model Training. 524–529. https://doi.org/10.1109/imsa61967.2024.10652803
- Alshahrani, R., Yenugula, M., Algethami, H., Alharbi, F., Goswami, S. S., Naveed, Q. N., Lasisi, A., Islam, S., Khan, N. A., & Zahmatkesh, S. (2024). Establishing the fuzzy integrated hybrid MCDM framework to identify the key barriers to implementing artificial intelligence-enabled sustainable cloud system in an IT industry. Expert Systems with Applications, 238. https://doi.org/10.1016/j.eswa.2023.121732
- Bolón-Canedo, V., Morán-Fernández, L., Cancela, B., & Alonso-Betanzos, A. (2024). A review of green artificial intelligence: Towards a more sustainable future. Neurocomputing, 599. https://doi.org/10.1016/j.neucom.2024.128096
- Bolte, L., Vandemeulebroucke, T., & Wynsberghe, A. van. (2022). From an Ethics of Carefulness to an Ethics of Desirability: Going Beyond Current Ethics Approaches to Sustainable AI. Sustainability, 14(8). https://doi.org/10.3390/su14084472
- Bossert, L. N., & Hagendorff, T. (2023). The ethics of sustainable AI: Why animals (should) matter for a sustainable use of AI. Sustainable Development, 31(5), 3459–3467. https://doi.org/10.1002/sd.2596
Ayrıntılar
Birincil Dil
İngilizce
Konular
İş Sistemleri (Diğer)
Bölüm
Derleme
Yazarlar
Taner Turgut
*
0000-0002-3084-7515
Türkiye
Selis Güler Siler
0009-0000-2430-1295
Türkiye
Büşra Alma Çallı
0000-0001-7411-4295
Türkiye
Erken Görünüm Tarihi
30 Haziran 2026
Yayımlanma Tarihi
30 Haziran 2026
Gönderilme Tarihi
28 Aralık 2025
Kabul Tarihi
20 Haziran 2026
Yayımlandığı Sayı
Yıl 2026 Cilt: 8 Sayı: 1
