Integrating AI in energy businesses (EB) is essential for achieving the goals set by international energy and climate change agreements. Business models (BMs) play a pivotal role in this framework by facilitating the adoption of renewable energy technologies and promoting energy efficiency practices. AI's predictive capabilities, optimization techniques, and fault detection methods are instrumental in managing energy systems’ safety, reliability, and stability. Furthermore, AI supports demand-side management and distributed energy optimization, enabling prosumers to participate actively in energy production and consumption. The rapid advancement of AI technologies is transforming the energy sector, providing innovative solutions for energy resource management and enhancing grid resilience. This article addresses the adoption of Artificial Intelligence (AI) in operating Energy Business Models (EBMs) in an economy driven by building a more sustainable future. The study aims to provide an overview of AI applications in BMEs. Under this logic, three sections were structured. The first section describes the development of EBMs, while the second section discusses AI applications. The following section discusses the possible impacts of using AI in BMEs. Finally, conclusions and references are presented.