Prepare proposals with AI without inventing scope

AI can help prepare a proposal by organizing discovery notes, approved service options and open questions into a reviewable draft. Pricing, delivery promises and contractual terms should come from authorized sources and decisions. Treat the draft as preparation, not an automatically valid offer.

Build the evidence packet

Imagine a prospect asking for help with customer onboarding. The assistant needs the discovery summary, the approved service catalog and the boundaries discussed with the prospect. A similar past proposal may help with structure, but its price and commitments should not silently transfer to the new customer.

Separate reusable wording from customer-specific facts before drafting.

Use a proposal outline

• Problem: the prospect's stated operational need.
• Scope: the work included and explicitly excluded.
• Process: proposed stages and responsibilities.
• Commercial details: approved price and conditions, or fields awaiting a decision.
• Next step: the review or conversation needed to finalize the offer.

Leave placeholders visible when a decision is missing. A blank marked for review is safer and more useful than a plausible number invented to make the document look finished.

Review claims and commitments

Check every result claim against approved public evidence. Do not turn one customer's outcome into a guarantee for another. Have the accountable team review delivery dates, dependencies and terms before the proposal is sent.

This workflow supports drafting and operational review; it does not replace the appropriate commercial or legal review of an agreement.

Validate the delivered artifact

Open the final document, inspect formatting and confirm the recipient can access the intended version. Record which version was approved and sent. If the scope changes later, preserve the earlier version and make the differences explicit. Useful proposal automation improves preparation while keeping the business in control of its promises.

Be Human editorial guidance. Examples are illustrative unless explicitly attributed. Sources provide background; implementation choices depend on your workflow.