Artificial intelligence in diagnostic imaging: collaborative asset or looming replacement?

Artificial intelligence (AI) is rapidly transforming diagnostic imaging, raising important questions about its role as a collaborative tool or a potential replacement for human expertise. This rapid communication reviews current evidence on AI applications in diagnostic imaging, focusing on clinical, ethical, and legal challenges. Although AI models show promise in detecting abnormalities and optimizing workflows, many remain limited by narrow training datasets and lack external validation. Ethical issues such as algorithm transparency, bias, and accountability are discussed, alongside the financial and practical implications of integrating AI tools into clinical practice, highlighting the need for clear guidelines and regulatory oversight. Radiologists continue to play a crucial role in interpreting images and validating AI outputs to avoid diagnostic errors, while the potential risks of overreliance on AI, including erosion of diagnostic skills among clinicians, are also emphasized. This communication advocates for responsible AI implementation that supports, rather than replaces, the expertise and judgment of healthcare professionals.