Abstract
This study introduces a framework aimed at enhancing the role of Artificial Intelligence (AI) in achieving the Sustainable Development Goals (SDGs). The primary objective is to address key challenges in AI applications, such as data scarcity, ethical concerns, and cultural diversity, by integrating explainable AI (XAI), simulation environments, and modular customization. The study emphasizes on region-specific datasets, synthetic data generation, and iterative refinement to improve AI solutions in sectors like poverty, healthcare, and climate action. The findings emphasizes on AI’s potential to transform theoretical solutions into practical, scalable implementations, driving sustainable development. While addressing challenges like data quality, algorithmic bias, and regulatory issues, the study also highlights the importance of ethical principles and contextual adaptability to achieve long-term, inclusive progress toward the SDGs.
References
- Șerbu, Răzvan Sorin, and Bogdan Ștefan Mârza. "From Crisis to Opportunity: Embracing Sustainable Development Goals and Artificial Intelligence in the Transformative Innovations World." In Ukraine's Journey to Recovery, Reform and Post-War Reconstruction: A Blueprint for Security, Resilience and Development, pp. 49-61. Cham: Springer Nature Switzerland, 2024.
- Yadav, Preksha, Luis Antonio Millán Tudela, and Bartolomé Marco-Lajara. "The Role of AI in Assessing and Achieving the Sustainable Development Goals (SDGs)." In Issues of Sustainability in AI and New-Age Thematic Investing, pp. 1-17. IGI Global, 2024.
- Palomares, I., Martínez-Cámara, E., Montes, R., García-Moral, P., Chiachio, M., Chiachio, J., ... & Herrera, F. (2021). A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects. Applied Intelligence, 51, 6497-6527.
- AlSagri, H. S., & Sohail, S. S. (2024). Evaluating the role of Artificial Intelligence in sustainable development goals with an emphasis on “quality education”. Discover Sustainability, 5(1), 1-26.
- Greif, Lucas, Fabian Röckel, Andreas Kimmig, and Jivka Ovtcharova. "A systematic review of current AI techniques used in the context of the SDGs." International Journal of Environmental Research 19, no. 1 (2025): 1.
- J. (2025). A systematic review of current AI techniques used in the context of the SDGs. International Journal of Environmental Research, 19(1), 1.
- Shahvaroughi Farahani, M., and G. Ghasemi. How artificial intelligence plays a role in achieving sustainable development goals? Sustainable Economies. 2024; 2 (3): 66. situations, 2024.
- Rane, Nitin. "Roles and challenges of ChatGPT and similar generative artificial intelligence for achieving the sustainable development goals (SDGs)." Available at SSRN 4603244 (2023).
- Meitei, A. Jiran, Pratibha Rai, and S. S. Rajkishan. "Application of AI/ML techniques in achieving SDGs: a bibliometric study." Environment, Development and Sustainability (2023): 1-37.
- Nahar, S. (2024). Modeling the effects of artificial intelligence (AI)-based innovation on sustainable development goals (SDGs): Applying a system dynamics perspective in a cross- country setting. Technological Forecasting and Social Change, 201, 123203.
- Hannan, M. A., Ali Q. Al-Shetwi, Pin Jern Ker, R. A. Begum, M. Mansor, S. A. Rahman, Z. Y. Dong, S. K. Tiong, TM Indra Mahlia, and K. M. Muttaqi. "Impact of renewable energy utilization and artificial intelligence in achieving sustainable development goals." Energy Reports 7 (2021): 5359-5373.
- Mehmood, H., Liao, D., & Mahadeo, K. (2020, September). A review of artificial intelligence applications to achieve water-related sustainable development goals. In 2020 IEEE/ITU international conference on artificial intelligence for good (AI4G). IEEE. 135-141
- Santos, E., Carvalho, M., & Martins, S. (2023). Sustainable water management: Understanding the socioeconomic and cultural dimensions. Sustainability, 15(17), 13074.
- Olateju, O., Okon, S. U., Olaniyi, O. O., Samuel- Okon, A. D., & Asonze, C. U. (2024). Exploring the concept of explainable AI and developing information governance standards for enhancing trust and transparency in handling customer data. Available at SSRN.
- Ravi, Mudavath, Atul Negi, and Sanjay Chitnis. "A comparative review of expert systems, recommender systems, and explainable AI." In 2022 IEEE 7th International conference for Convergence in Technology (I2CT), IEEE, 2022. 1-8.
