This study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilingual (Arabic–English) decision-support application was developed to operationalize the model, enabling scenario analysis, risk prediction, and project monitoring under crisis conditions. The findings highlight the potential of Ethical AI to enhance transparency, accountability, and data-driven decision-making in fragile and post-conflict environments, supporting national strategies aligned with the United Nations Sustainable Development Goals (UN-SDGs). © 2026 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/ Author keywords Artificial neural networks, Sustainability indicators; Ethical artificial intelligence; Iraq; Risk management; SMART-AI; SPSS analysis; Sustainable development
