
Survey finds over 75% of radiology organizations using AI lack clear, quantified ROI data.
Key Details
- 1Black Book Research surveyed over 200 hospital and clinic leaders ahead of RSNA.
- 2More than 75% of organizations using radiology AI do not have quantifiable ROI information.
- 3About 24% had measurable ROI data; of these, 36% received AI payments per study.
- 4Other payment structures included bundled payments (25%), enterprise licenses (20%), and per-user pricing (10%).
- 5Despite lack of ROI clarity, most leaders reported positive or neutral feelings about AI's impact.
Why It Matters
As AI becomes more integrated into radiology workflows, the lack of clear ROI data could slow adoption or influence future investment decisions. Understanding payment models and satisfaction levels helps stakeholders adapt strategies for successful AI implementation.

Source
Radiology Business
Related News

•Radiology Business
AI-Powered Tool Streamlines CT Scan Prioritization in Emergency Departments
An AI-based CT queue system significantly reduces wait times for ED patients by prioritizing scans likely to reveal critical findings.

•Radiology Business
AI Workflow Enables General Radiologists to Match Breast Specialists in Screening
AI-powered workflow helps generalist radiologists detect breast cancer at rates comparable to specialists.

•Radiology Business
LLMs Automate Radiology Report Quality Control, Study Finds
LLM-based systems can rapidly automate radiology report quality control, saving significant manual review time.