Fine-tuning
Fine-tuning takes a general-purpose foundation model and continues training it on a narrower, organisation-specific dataset — improving performance on domain-specific tasks (e.g. insurance claims language, clinical notes) at the cost of additional infrastructure, data governance, and ongoing maintenance versus prompting or retrieval-augmented approaches.
Primarily affects
The Investment dimension of the Australian Enterprise AI Index.
See where this shows up in the Index
The open methodology explains exactly how each dimension is scored and weighted.
Related terms
Definitions are written for enterprise AI governance context, not a formal legal standard. Suggest a correction →