AI literacy and certification in healthcare.

In hospitals, general practices and mental health care, AI applications are being introduced broadly. UMC Utrecht uses IMAGR for radiological support; Radboudumc uses the Aiosyn system for quality control on approximately 250,000 digital slides per year; Erasmus MC works with spin-out Quantib on AI for MRI prostate research. AI documentation (ambient scribing) via Dragon Medical One is in use at Maasstad Ziekenhuis, MCL and Jeroen Bosch Ziekenhuis, among others. Yet the organisational foundation remains thin: only 20% of hospitals have their AI readiness substantially in order, and more than half do not know whether models are retested or recalibrated after deployment.

Healthcare handles special categories of personal data under Article 9 GDPR and decisions on which the Wet BIG, the Wgbo and the Wkkgz place direct responsibilities. AI systems that qualify as a medical device under MDR or IVDR automatically fall into the high-risk category of the AI Act (Annex I) when subject to third-party conformity assessment — in practice: diagnostic image analysis, clinical decision support from class IIa onwards and AI in IVD software. IGJ emphasised on 10 February 2025 that the impact of generative AI on patient care is partly unknown; the Toetsingskader Digitale Zorg (IGJ, May 2024) forms the supervisory framework.

For healthcare organisations, the scheme offers a uniform way to organise demonstrable AI literacy across job groups, independent of supplier or trainer — aligned with IGJ review and MDR documentation obligations. For individual professionals, a SAIG certificate provides independent, verifiable proof of tested competence that is portable across employers and that — unlike a training certificate — actually involves an assessment.