A significant advancement in the creation of intelligent systems is represented by the convergence of quantum computing with artificial general intelligence (AGI). Although traditional AI has advanced significantly, especially in machine learning, it is still constrained by the limits of traditional computing systems. With its capacity to carry out any intellectual job that a human can, artificial general intelligence (AGI) requires hitherto unheard-of levels of efficiency, flexibility, and processing power. This is where the revolutionary promise of quantum computing, which makes use of the concepts of superposition, entanglement, and quantum parallelism, lies. Enhanced by quantum AGI presents a novel paradigm in which quantum computing can manage extremely large, multidimensional data sets, optimise problem-solving techniques, and exponentially speed up learning methods. AGI's capacity to search enormous spaces of potential solutions, mimic cognitive processes, and resolve issues with higher dimensional complexity in ways that classical systems find difficult to accomplish could be significantly enhanced by quantum algorithms like Grover's search and Shor's factoring algorithm. Furthermore, knowledge representation and reasoning processes in AGI systems may need to be radically rethought in light of quantum computing. AGI may be able to process, interpret, and adjust to changing environments much more efficiently than current models, thanks to quantum neural networks, hybrid quantum–classical architectures, and quantum machine learning models. In addition to improving the capacities of intelligent systems, this collaboration between AGI and quantum computing will create new opportunities to address difficult global issues in fields like cybersecurity, healthcare, and climate change. The whole definition of intelligence and computational problem-solving may be redefined by quantum-enhanced AGI as research progresses.