Radiology generates almost 90% of the data stored in a modern hospital¹, yet imaging volumes continue to rise faster than the global radiologist workforce can grow. Artificial intelligence in radiology, not merely an add‑on technology but a transformation in clinical culture, has emerged as the pragmatic answer. Modern AI radiology algorithms convert floods of pixel data into high‑fidelity insights in real time, allowing clinicians to move from image interpretation to patient‑impactful decision‑making. More than 340 imaging algorithms have received U.S. regulatory clearance (as of April 2025)², and a growing share of departments worldwide use at least one AI for radiology tools as part of routine practice³. These AI systems in radiology are best understood as cognitive extenders: they surface the invisible, triage the urgent, and automate the repetitive, while the radiologist retains ultimate clinical stewardship. In this brief, we explore why AI in radiology has become the strategic lever for imaging services, how AZmed positions itself within that shift, and what healthcare leaders should prioritise next.
