Potential of AI and ML-Based Models in Energy Demand Forecasting for Sustainable Consumption and Production

The Sustainable Development Goals (SDGs) of the United Nations provide a framework for addressing global challenges like poverty, inequality, and climate change. Out of the seventeen goals that have been adopted by members of the United Nations since 2015, Sustainable Development Goal 12 (SDG 12) focuses on promoting sustainable consumption and production. The goal emphasizes on finding new ways and means to reduce wastage, optimize production, and minimize environmental impact. It emphasizes the need to find ways to manage resources responsibly and reduce wastages across various sectors of the economy (Noliya et al. EDPACS, 1–11, 2025; Ogunmola et al. Int J Technol Policy Manag 24:375–39, 2024). The SDG 12 is closely connected with other SDGs, especially SDG 7, 11, 13, and 15. Where SDG 13 focuses on finding ways to tackle climate change and its consequences, SDG 7 is centered on providing universal access to reliable and affordable clean energy, and SDG 11 is dedicated to creating cities that are inclusive, safe, resilient, and sustainable; meanwhile, SDG 15 focuses on conserving, restoring, and promoting the sustainable management of land ecosystems and natural resources. This interconnectedness between various SDGs highlights the importance of a holistic approach to sustainable development and the multifaceted nature of responsible consumption and production. Energy as a vital resource serves as an important pillar of economic growth, technological progress, and societal well-being. A reliable and continuous energy supply drives industrialization by powering factories, enabling manufacturing, and facilitating the production of goods and services. It supports infrastructure development, including transportation, communication networks, and urbanization, all of which are essential for a thriving economy. Accurate forecasting of energy load requirements can help organizations plan their operations, thus reducing overproduction and minimizing waste and their overall environmental impact. It is also essential for optimizing resource allocation and promoting responsible consumption. In the era of rapid technological development and the emergence of artificial intelligence and machine learning based models, this paper aims to understand the potential of these models to forecast the energy demand of commercial buildings. Such insight can help organizations plan their production and operations, and facilitate better building management, thus contributing to progress toward the attainment of sustainable development goals.