Irish radiologists lack confidence in AI despite comfort with technology, study finds

Most Irish radiologists are comfortable with technology but lack confidence in AI, a survey of 59 consultants and trainees found. Time to learn was the top barrier, with trainee preparedness scores nearly half those of consultants.

Categorized in: AI News Education
Published on: Apr 20, 2026
Irish radiologists lack confidence in AI despite comfort with technology, study finds

Irish radiologists lack confidence in AI despite comfort with technology

A new study of Irish radiologists reveals a significant gap between their comfort using technology and their understanding of artificial intelligence systems. Researchers surveyed 59 consultants, fellows, and trainees across the country and found that while most feel at ease with technology generally, fewer express confidence in how AI works or how it applies to their work.

The research, published in Springer Nature Comprehensive Clinical Medicine, identifies education as the critical missing piece. Respondents cited lack of time to learn as the biggest barrier to AI training, with 42% pointing to this obstacle.

Experience shapes readiness

Consultant radiologists reported higher confidence in their ability to implement AI in daily practice than fellows and trainees. Consultants rated themselves as more interested in informatics and felt more prepared to adopt AI tools-a gap the authors attribute to experience and seniority.

Among trainees and fellows, confidence in implementing AI dropped sharply. Their mean preparedness score was 31.1 compared to consultants' 55.3, suggesting that early-career radiologists face particular barriers to adopting these systems.

Education emerges as priority

The study recommends making AI education more accessible across all career levels in Irish radiology. Accessible training could help build the confidence needed for radiologists to use AI tools in their daily work.

The findings apply broadly to AI for healthcare settings where clinical professionals need practical knowledge to adopt new systems. Time constraints remain real, but structured, available education could address the gap between current comfort levels and actual confidence in AI applications.

The full paper is available through Springer Nature Comprehensive Clinical Medicine.


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