The rise in global demand for effective and sustainable energy solutions has prompted the integration of advanced Artificial Intelligence (AI) techniques with conventional methods for predicting energy consumption. This chapter offers a comprehensive overview of the role of AI technologies, encompassing machine learning algorithms and deep learning, in producing precise and accurate energy consumption predictions. It commences by examining the primary factors influencing power demand, followed by a presentation key AI techniques, such as supervised learning models (including regression and classification) and advanced deep learning architectures (such as recurrent neural networks and convolutional neural networks). Each technique is assessed in the context of its application to energy consumption forecasting, emphasizing its strengths and limitations. Furthermore, the chapter explores existing energy demand forecasting and prediction systems, evaluating their contribution to sustainability. To conclude, the chapter discusses future trends and challenges in AI-powered energy forecasting, including the requirement for high-quality data, model interpretability, and the ethical implications of AI in energy management.