A health services organization is developing a proprietary generative AI chatbot to assist patients with...

AAISM prioritizes training data suitability—lawful sourcing, provenance, quality, representativeness, and safety—especially in health-related applications. The correctness and appropriateness of training data determine clinical safety, reduction of harmful outputs, and compliance with data protection/sector obligations. Larger models or more data do not compensate for inappropriate or low-quality datasets; tuning is secondary to ensuring the right data with rigorous curation, labeling quality, and guardrails aligned to patient safety requirements.