A sales proposal brings together the customer's request, catalogue, prices, delivery terms and company template. AI can help when managers repeatedly transfer information between these sources. A language model should not become the price list or promise stock availability without evidence.
Establish source priority
Take product codes and specifications from the approved catalogue, prices from a selected price list, and stock from the business system with an update timestamp. Check customer-specific terms separately. When sources disagree, expose the conflict instead of choosing the most convenient figure.
Separate data from presentation. First create a structured offer containing items, totals and open questions. Move it into the document template after review. This makes errors easier to correct without rereading an entire polished file.
Example: an incomplete product description
A customer requests a pump and specifies flow rate but omits material requirements. The assistant finds candidates and drafts a clarification question. If alternatives are permitted, present them separately with their differences. Silently choosing for the customer can result in an unsuitable supply.
After the manager confirms a product, formal rules calculate totals and produce the document. The outgoing message remains a draft until its recipient, attachments and terms are checked.
Preserve the decision history
- Original request and catalogue or price-list version. - Reasons for substitutions, discounts and unusual terms. - Reviewer identity and the approved document version. - A link to the deal without duplicate creation after a retry.
Evaluate accepted proposals
Use offers of varying complexity. Measure preparation time, corrected items, omitted terms and returns for revision. Reliably assembling one proposal type is a stronger starting point than automatically producing many templates. In AI Office, this workflow could become an initial sales role, later connected to CRM records and follow-up tracking.