Foundation Model
Foundation models — GPT, Gemini, Claude, Llama and similar — are large models trained on broad data at scale, then adapted to specific enterprise use cases through prompting, retrieval augmentation, or fine-tuning, rather than being trained from scratch for each task. Which foundation model(s) an enterprise standardises on is one of the first architectural decisions in any AI adoption program.
Primarily affects
The Adoption 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.
Definitions are written for enterprise AI governance context, not a formal legal standard. Suggest a correction →