Technology leaders presenting to CEOs and other company leaders about AI often need to translate technical terms such as “tokenization,” “retrieval-augmented generation,” and “context window” into everyday business language. Google Gemini can help bridge this communication gap. In Step 1, users open a new chat and explain what they hope to communicate to leadership, being as technical as they wish, such as building a RAG pipeline to vectorize proprietary data or using parameter-efficient fine-tuning methods like LoRA to deploy open-weight models on-premises without exploding cloud inference costs; technical documents can be uploaded directly in the chat window. In Step 2, Gemini translates that vision into language that connects with the audience, using a sample prompt in which the CIO at [company] builds the case to [adopt generative AI solutions] and asks for talking points explaining generative AI to the CEO and board, including how it could help digitally transform, why it is important to growth, how it could re-focus technical talent on more strategic work, enhance workforce productivity, and better serve the global workforce and customers. Gemini might explain RAG by noting it anchors AI to internal data like HR policies and technical manuals, or note the opportunity to shift employees’ focus from low-value, repetitive tasks to innovation. In Step 3, Gemini helps create a more structured pitch.