The integration of artificial intelligence (AI) into radiation oncology is transforming the field, driving advancements in precision, efficiency, and patient outcomes. AI enables more accurate treatment delivery, streamlined workflows, and data-driven decision-making, reducing clinician burden while enhancing the quality of care. By improving treatment accuracy and reproducibility, AI fosters greater consistency in patient management, ultimately leading to better clinical outcomes. In addition, AI-driven insights support personalized care approaches, ensuring that patients receive tailored treatments based on robust data analysis. Despite its promise, the widespread adoption of AI presents challenges, including standardization, data privacy, algorithmic bias, and regulatory oversight. Ethical and responsible implementation requires rigorous validation, interdisciplinary collaboration, and equitable access to prevent disparities in care. As AI continues to evolve, its role in augmenting, rather than replacing, human expertise will be critical in shaping the future of precision oncology. This paper explores AI’s transformative impact on radiation oncology, addressing its benefits, challenges, and future directions in advancing patient-centered care.
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