Writing a commercial proposal

How can you use AI to write a clear commercial proposal that faithfully reflects the need?

1250 € per session, excl. VAT

In short

“Writing a commercial proposal” is a private in-person session of half a day for salespeople, account managers and pre-sales consultants or sales assistants who format proposals. It helps you build a proposal outline based on a validated need. Groups of up to 12 participants, in French, with exercises on your own work cases.

Why this training?

A commercial proposal must show that the need has been understood and make the decision easy. All too often, it reuses a generic template, omits elements that were discussed or contains imprecise commitments. This session starts from a restatement validated by the client and uses AI to structure and write, while commitments (scope, prices, timescales) remain written and checked by the salesperson. Running case study: ‘Hydra Services’, a fictional industrial cleaning company, responds to the validated need of a fictional production site. Participants write the complete proposal and its summary for the decision-maker. Transfer to the workplace: Participants apply the method to their next proposal and have the commitments reviewed through the internal approval process.

Objectives of this training

  • Build a proposal outline based on a validated need
  • Use AI to write the context, challenges and solution sections
  • Write and check the commitments yourself: scope, prices, timescales, terms
  • Write a one-page summary for the decision-maker
  • Carry out a full review before sending

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Salespeople, account managers and pre-sales consultants
  • Sales assistants who format proposals

Prior skills

  • Have already used a generative AI assistant for a few simple tasks (AI Fundamentals level or equivalent).
  • Know your company’s sales cycle and main offerings.

What you will work on

  1. What a proposal must contain

    Objective: Structure a proposal that makes the decision easier. Standard outline; link to the validated restatement; common mistakes; sections that AI can or must not write.

  2. Writing the context, challenges and solution

    Objective: Obtain clear text that faithfully reflects the need. Give AI the restatement and outline; check each sentence against the validated need.

  3. Commitments and terms

    Objective: Safeguard the contractual elements. Scope, deliverables, schedule, prices and terms written according to internal rules, without delegating them to AI.

  4. Decision-maker summary and review

    Objective: Make the proposal readable in two minutes. One-page summary; final review: consistency, figures, names, next steps.

What you take away

  • Annotated proposal outline
  • Complete commercial proposal (fictional case study)
  • One-page summary for the decision-maker
  • Commitments review checklist

Method and assessment

  • Short explanations followed by immediate practice on the running case study.
  • Individual work followed by work in pairs, with participants reviewing each other’s work.
  • Guided group discussion: what works, what needs correcting and what remains a human decision.
  • Preparation: Bring your current proposal template (without client data). Know the internal rules for approving prices and terms.

Observable criteria: Each element of the solution addresses a need in the validated restatement; Prices, timescales and terms are written and checked by the participant; The summary fits on one page and specifies the decision expected; The review checklist is applied in full.

Frequently asked questions

Can AI calculate the price?

No. Prices and terms follow your internal rules and are written by the salesperson; AI only helps with writing and structure.

Can we reuse our template?

Yes, the method adapts to your existing template, which the session helps to clarify.

How does this relate to the training on restating needs?

It is the logical next step: the proposal is based on a restatement validated by the client.

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