Sustainable economic planning has become a key concern for emerging economies due to increasing environmental challenges, resource constraints, and social disparities. In this context, Artificial Intelligence (AI)–driven mathematical optimization models have gained importance as effective tools for enhancing economic decision-making and long-term sustainability. This study examines the role of AI-driven optimization models in supporting sustainable economic planning and development, with particular reference to emerging economies. The study is based on both primary and secondary data. Primary data were collected through a structured online survey to assess awareness, perception, and acceptance of AI-based optimization in economic planning, while secondary data were obtained from academic journals, reports, and policy documents. The findings reveal that although awareness of AI-driven optimization models is moderate, a majority of respondents acknowledge their potential in improving sustainable economic growth, reducing environmental impact, and enhancing resource allocation efficiency. However, challenges such as limited technical expertise, data availability, model complexity, and institutional constraints continue to hinder widespread adoption. The study emphasizes the need for developing an integrated framework supported by capacity building, regulatory guidance, and ethical governance to facilitate effective implementation. It concludes that AI-driven mathematical optimization models can significantly contribute to sustainable and inclusive economic development if supported by appropriate infrastructure, skills, and policy frameworks.
Pandey et al. (2026) studied this question.