Testing industry leading generative AI foundational large language models
Description
The AI is intended to address gaps in organizational understanding of how generative AI can support knowledge work. The sprint helps identify potential benefits, limitations, and risks of AI tools, enabling informed decisions on future use, governance, and policy before any deployment.
Detailed example
The AI system produces draft text, summaries, outlines, and alternative wording for non-sensitive content, as well as explanatory responses to user prompts. Outputs are advisory and informational only and require human review; they are not authoritative, binding, or used for regulatory or safety decisions.
AI / analytics pattern
Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Improved staff understanding of generative AI capabilities and limitations; increased efficiency in drafting, summarizing, and organizing non-sensitive information; identification of appropriate use cases and risks; and informed development of policies, guidance, and governance for potential future AI use.
Controls / human review
ATO: No; PIA: Not published