Proposals are where the stakes are highest and where advisors are most cautious about AI, for understandable reasons. A proposal that sounds templated or generic does not just fail to win the booking: it actively undermines the impression of bespoke expertise that the whole interaction has been building toward.
The caution is right. But the solution is not to avoid AI for proposals. It is to use the specificity principle more rigorously than anywhere else.
A proposal that wins does so because it reflects a specific understanding of a specific client’s specific brief. Every element of the proposal language should carry evidence of that understanding: the destination choices, the pace, the experience types, the way the options are framed. If the language could apply to any client, it will read that way.
The prompt framework for proposal language therefore has more situational context than any other content type. Everything you know about this client, everything they communicated about what they are looking for, any preferences or sensitivities that have emerged in the conversation, any previous trips they have taken and what they said about them: all of that goes in before you ask the tool to draft a word.
With that level of input, AI can produce proposal language that reflects genuine understanding, because you have provided the understanding and asked it to express it. Without that input, it will produce language that sounds like a proposal but reads like a template.
The companion PDF framework for proposals covers the opening paragraph, the options framing, and the closing recommendation. These are the three sections that do the most persuasive work and the most common places where proposal language either lands or falls flat.
