While AI brings enormous promise, it also raises critical challenges:
- Data privacy: Medical data is extremely sensitive, and breaches can have dire consequences.
- Bias in AI models: If training data lacks diversity, AI may produce inaccurate or discriminatory outcomes.
- Transparency: Clinicians and regulators need to understand how AI systems reach conclusions.
- Over-reliance on automation: There’s a risk of losing clinical judgment if AI systems are trusted blindly.
In 2025, health systems are working closely with regulators to ensure AI solutions are safe, explainable, and equitable. The FDA, EMA, and other global authorities have developed frameworks for AI-based medical device approval and post-market surveillance.