Table 2.

AI competency profiles in healthcare education

Category	Learning objectives	Suggested assessment methods
Consumer	• Identify clinical tasks appropriate for AI assistance	• Multiple-choice questions (MCQs)
	• Interpret AI-generated risk scores or predictions	• OSCE station with AI tool interpretation
	• Recognise limitations and biases in AI outputs	• Structured reflection
Translator	• Critically evaluate the clinical relevance of AI models	• Case-based discussions
	• Communicate AI results to patients or interdisciplinary teams	• Role-play or communication OSCE
	• Propose workflows for integrating AI	• Reflective portfolios
Developer	• Implement basic predictive models using healthcare data	• Project-based assignments
	• Validate models against clinical metrics	• Code walkthroughs
	• Explain algorithmic design choices	• Oral examination of model logic