This chapter provides a comprehensive investigation into geothermal energy, with a focus on its potential for sustainable energy recovery and the transformative role of Artificial Intelligence (AI) and the Internet of Things (IoT) in optimizing geothermal facilities. The chapter systematically explores the various stages of geothermal energy production, from resource exploration and reservoir characterization to drilling, plant operation, and maintenance. Emphasis is placed on how AI, through machine learning, deep learning, and predictive analytics, enhances efficiency across these stages by improving subsurface temperature prediction, optimizing fluid flow, and managing equipment health in real-time. Additionally, the integration of IoT technologies is highlighted as a key enabler for continuous monitoring, data collection, and dynamic control of geothermal systems, fostering more responsive and adaptive facility management. Specific case studies demonstrate how AI and IoT solutions synergize to address geological uncertainties, predict reservoir performance, and reduce operational risks, contributing to sustainable and cost-effective energy recovery. The chapter also delves into advancements in enhanced geothermal systems (EGS), innovative drilling technologies, and the application of nanomaterials to boost thermal efficiency. A final focus is placed on AI-driven multi-objective optimization, which balances energy output, operational costs, and environmental sustainability. This synthesis underscores the role of AI and IoT in revolutionizing geothermal energy systems, driving them toward greater resilience and long-term viability within the renewable energy landscape.