As organizations seek to navigate the complexities of contemporary energy environments, the key role of artificial intelligence (AI) in optimizing energy management has emerged as a critical area in organizations. This study examines the relationship between AI and energy management in organizations. It examines how AI can be used to increase sustainability and efficiency in energy management. Using AI-driven solutions allows organizations to use machine learning algorithms, predictive modeling, and advanced data analytics; gain actionable insights into energy consumption patterns; identify inefficiencies; and implement targeted strategies for optimization. Integration of AI into energy management not only increases efficiency in resource use but also facilitates the transition to sustainable practices. AI enables organizations to dynamically respond to fluctuations in energy demand, optimize operational costs, and minimize environmental impact through real-time monitoring and adaptive control systems. In addition, AI-supported energy management systems contribute to the development of smart and resilient infrastructures, promoting a more harmonious and responsive organizational ecosystem. This study examines the business and management literature on AI and energy management via a systematic literature review. In doing so, this study aims to shed light on the potential of AI to revolutionize traditional energy paradigms and provide a path toward energy sustainability, cost-effectiveness, and environmental responsibility for organizations across a variety of industries. It also explores the many benefits and challenges of the convergence of AI and energy management.