I am a Clinical Radiologist…And I Am Not Afraid of AI

Artificial intelligence (AI) is one of the most consequential technological advances in modern medicine, and radiology stands at the forefront of this transformation. There are widespread narratives of potential disruption of radiology and replacement of radiologists, which are not unsubstantiated.[ 1 ] As a clinical radiologist, I am, however, enthusiastic about AI rather than apprehensive. I am certainly not afraid of AI, because I recognize it as the next logical phase in the evolution of our specialty. Right from X-rays to cross-sectional imaging, the radiologist's role was never diminished, only redefined, and AI is also not an exception . Imaging data are digital and standardized, which is an ideal substrate for AI development. This makes radiology an ideal testing ground for its safe and effective deployment in the health care ecosystem . While AI excels in speed, scalability, and pattern recognition, radiologists bring contextual understanding, clinical reasoning, and accountability. As AI can perform repetitive, time-intensive tasks, radiologists may engage more deeply in clinical decision-making. This may allow transition from a volume-based model to a value-based approach in radiology . With the integration of imaging with electronic health records, radiologists can deliver patient-centric insights as clinical information specialists.[ 2 ] This integrative role places radiology at the heart of data-driven precision medicine. Powered by AI, quantitative imaging (radiomics), predictive analytics, and opportunistic imaging can be efficiently integrated into routine practice for personalized health care.[ 3 ] Imaging biomarkers based on visceral fat, hepatic steatosis, bone density, vascular calcifications, and muscle mass may emerge as powerful tools for “longevity imaging.”[ 4 ] Thus, radiology becomes an active contributor to population health, disease prevention, and evidence-based lifestyle medicine.[ 5 ] This evolution necessitates a shift in the radiologist's profile—from “doctor's doctor” to “patient's doctor.” [ 6 ] AI-enabled visualization, risk stratification, and personalized reporting can facilitate direct patient engagement, enhancing understanding and empowering individuals in their health care journeys. The adoption and integration of AI, however, must be led by radiologists themselves. Domain expertise and an understanding of workflow are indispensable for developing meaningful and safe AI tools.[ 7 ] Radiologists must actively participate in AI development, validation, and implementation, ensuring that these tools are clinically relevant, unbiased, and ethically sound. Passive adoption of AI is not sufficient; the leadership role of radiologists is essential for the ethical and efficient integration of AI into health care with widespread generalizability and minimal concerns of bias and errors . I am a radiologist with 20 years of work experience in clinical and academic radiology. I see in AI not a threat, but an opportunity of a lifetime to move beyond images and reports, and toward more meaningful clinical impact. And as a clinical radiologist, I am NOT at all afraid of AI, I am ready to again EVOLVE, AI-enabled radiologists are the future… Publication History Article published online: 05 August 2026 © 2026. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/) Thieme Medical and Scientific Publishers Private Limited A-13A, Graphix Tower 1, 6th floor, Sector 62, Noida 201309, Uttar Pradesh, India