This systematic review examines the evolution, technical architecture, applications, limitations, and future directions of generative artificial intelligence (AI) and large language models (LLMs). Through comprehensive analysis of scientific literature, it was traced the development of these technologies from early linguistic theories to modern transformer-based architectures. The findings presented in this review article reveal the transformative impact of LLMs across diverse domains including healthcare, education, software development, and creative industries. Significant technical limitations were identified, including hallucinations, context window constraints, and reasoning deficiencies, alongside ethical concerns regarding bias, privacy, and environmental impact. The review concludes by exploring emerging trends in model architecture, efficiency improvements, and ethical frameworks that will shape future development. This work provides researchers, practitioners, and policymakers with a comprehensive understanding of the current state and future trajectory of generative AI and LLMs.
