AI model training is the foundational process by which machine learning systems develop the capability to perform complex research tasks, from recognising conversational hesitation to coding qualitative themes across thousands of transcripts. In the context of AI-moderated research, model training determines how well an AI moderator can probe meaningfully, follow unexpected participant responses, and surface patterns that matter to insights teams. Well-trained models distinguish between surface-level answers and genuine sentiment, making them far more useful for enterprise qualitative research than generic language models. The quality of training data, the diversity of research contexts represented, and the involvement of experienced researchers in shaping model behaviour all directly affect how credible and actionable the resulting findings are.