Radiation therapy is one of the medical fields where artificial intelligence (AI) has emerged as an influential force with enormous potential to change treatment procedures completely and results. The development of radiation therapy and the vital part AI plays in improving accuracy and effectiveness in healthcare. The fundamental ideas of neural networks and machine learning are described, along with important AI techniques that are now used in radiotherapy. AI’s critical contributions to tumor identification, treatment planning, adaptive radiation approaches, outcome prediction, and patient-specific dosimetry are among the applications that are highlighted. The article discusses AI-driven advances that enhance workflow efficiency and treatment homogeneity, including automated contouring, real-time treatment monitoring, and quality assurance. The future of precision and individualized radiation is demonstrated by emerging technologies such as radiomics, federated learning, and AI-assisted advanced therapies. Data privacy, ethical considerations, algorithmic interpretability, and clinical validation are some of the directions in which contemporary AI has been making the technology more efficacious, even though it still maintains constraints. AI strategies should be optimally initiated as a part of a comprehensive, multicentric, and prospective validation process to ensure both their effectiveness in a wide range of clinical scenarios and the quality of their precision. This study reviews AI’s potential for individual precision medication, how to decrease differences in the provision of radiotherapy, and how to embrace collaboration in the research community. The implementation of AI in the radiotherapy workflow can be an effective solution for the increasing complexity of modern radiotherapy without failing to address the need for individualized patient care, radiation dose recommendation refinement, and patient outcome improvement.