The global energy industry is facing a seismic shift, driven by the need to balance energy security, environmental sustainability and economic efficiency. Due to the penetration of renewable energy sources into the current power systems, the management of the generation, transmission, distribution, storage, and consumption has become much more complicated. Artificial Intelligence (AI) has emerged as a vital enabler technology to tackle these issues, translating large volumes of energy data into usable intelligence and real time decision making skills. This talk investigates the hidden power of AI in changing global energy systems and expediting the transition to a resilient, low-carbon future. The talk covers the role of AI in renewable energy prediction, optimisation of wind and solar energy production, predictive maintenance of key infrastructure, smart grid operations and energy storage management. We explore practical applications of AI in self-healing grids, demand response programs, virtual power plants, electric car integration, and industrial energy optimisation. The case studies include large-scale renewable integration projects in China and lessons from the Spain-Portugal blackout, highlighting the revolutionary influence of AI on the reliability and operational efficiency of energy systems. Additionally, the talk will address major obstacles and hazards related to AI adoption, such as cybersecurity vulnerabilities, data privacy issues, algorithmic bias, legal hurdles, and the sustainability consequences of deploying AI on a broad scale. Finally, it addresses future trends in AI-enabled decentralised energy systems, quantum computing, climate modelling and autonomous energy networks. AI is no longer a technological enhancement, but a fundamental driver of the global energy transition. AI enables intelligent, adaptive, and data-driven energy ecosystems and offers unique prospects to enhance dependability, cost, and sustainability and is a key component of future energy systems and climate change initiatives.