AI Resilience Report forNuclear Medicine Technologists

Other core tasks (like planning the study, interviewing patients, or giving radiotracer injections) are mostly done by people right now. We didn’t find any AI that can inject isotopes or decide on a procedure for you – those require careful human training and judgment. Some researchers are studying robots that could handle radioactive materials or even walk patients to scanners, with the aim of reducing worker exposure ^{[3] [3]}.

But for now, the robot examples mostly move objects or check radiation levels; they are assistants, not replacements. Talking with patients about tests, answering their questions, and teaching trainees are also human skills AI isn’t automating. In short, computers help by making imaging faster and clearer, but people still do the hands-on work and patient care ^{[3] [4]}.

On the downside, nuclear medicine is a highly regulated, high-stakes field. New AI tools must be proven very reliable and safe before hospitals use them. Researchers and regulators stress that any AI system needs strong evidence of benefit (like better patient outcomes or cost savings) before it’s widely adopted ^[2].

Testing and approving AI in medicine can take years, especially for something involving radiation safety. In addition, the market for AI in nuclear imaging is still small compared to X-rays or MRIs, so commercial products are limited. For these reasons, clinics will likely add AI features gradually.

Overall, AI is expected to augment – not outright replace – technologists. Human skills like critical thinking, hands‐on care, and teaching remain very important, even as tools make the imaging process easier and safer ^{[3] [2]}.