Do not send an AI proposal before checking prices and data
Friday, just before the end of the working day. You attach the proposal to an email, check the price once more and hit send. By Monday, your message is buried between meeting requests and invoices. Now your customer has to piece together the services, process and costs from several pages. That is where a good proposal can lose its impact. AI can turn the document into a clearer proposal page. But how can you tell whether it will genuinely help the customer, rather than giving your team another round of approvals?
The attachment has to do too much
A PDF is practical. You can send it, save it and print it. But it often leaves the recipient to work through the line items, service descriptions and terms on their own. If several people need to sign off internally, someone also has to forward and explain the relevant sections.
With bespoke services, much of the real work often happens before the proposal goes out. A trades business describes a particular starting point, an agency explains its concept and schedule, and a consultancy sets out its approach and expected results. All this information may be in the document. Whether it is arranged in a way that helps the customer make a decision is another matter.
So the problem is not necessarily the file format. It is the responsibility the format leaves with the reader. If your proposal does not quickly make clear what it is about and what happens next, the key question remains unanswered: what should the customer do after the last page?
Customers read with different eyes
You know every abbreviation and line item in your proposal. The purchasing manager, managing director or technical contact on the other side may know only what came up in the conversation before the document arrived. Terms of art, internal shorthand and several options may be familiar to your team, yet still prompt questions from the customer.
Larger organisations bring another hurdle: the person who receives the proposal may not make the decision alone. They may need to pass the solution on to procurement, IT or senior management. A clear account of the starting point, service, process and next steps makes that internal conversation easier. For a small business, the same clarity can save the owner from explaining the whole scope again on the phone three days later.
McKinsey describes PDFs as a form of unstructured information that generative AI can process. That matters to businesses because an existing document can become the starting point for a different presentation. But who decides which information should come first, and which explanation matters to this particular customer?
AI can organise the proposal, but it cannot know your commitments
An AI system can organise an existing proposal into clear sections and tailor the wording to the recipient. A plain list can become a page that starts with the customer’s situation, explains the service and sets out the next step. The practical benefit is that your team does not have to start from a blank layout every time.
That does not replace a professional review. AI will not automatically know what was agreed verbally in the customer meeting, how limited your capacity is next month, or where an extra request changes the price. An elegant sentence can still create the wrong expectation. Someone who is accountable needs to check prices, dates, scope and terms.
McKinsey reports that, in a B2B Pulse Survey, 19 per cent of respondents were already implementing generative AI applications for buying and selling, while a further 23 per cent were working on it. This does not prove that AI proposals automatically perform better. It shows that businesses are already testing these processes. The key question is: which decisions can AI prepare, and which must stay with your team?
A proposal page will not fix every sales problem
A link can make it easier for customers to share a proposal with colleagues. They do not have to create another file or photograph the relevant pages. A PDF is still useful if procurement or accounts needs a file for its records. Both versions should contain the same information, so two slightly different versions do not end up circulating.
The page itself cannot tell you whether your proposal meets the customer’s needs. If the conversation beforehand was unclear, a polished presentation will not close the gap. And if nobody in your team knows who should follow up after sending it, even the clearest link has nowhere to go.
AI can only work with the information it receives. If the source document does not explain the benefit to the customer, the system should not make one up. That is why checking the proposal before sending it is not a box-ticking exercise. It is part of the service your business stands behind.
What this means for your business
Do not start with every proposal at once. Pick one that is typical of your day-to-day work and regularly prompts questions from customers. Read it from the perspective of someone who was not in the sales meeting. Is the starting point clear? Are the service and process easy to follow? Does the customer know how to accept or ask a question?
Before testing AI, decide what must stay unchanged. That might include prices, deadlines, limits on the service and legal statements. Also decide who will review and approve the revised version. This helps prevent a more polished presentation from quietly turning into a new commitment.
Next, ask a colleague who did not create the proposal what they understood from it. If possible, ask a customer for feedback too: what was clear straight away, and where did they need to ask a question? This simple check tells you more than whether you like the page yourself. Which part of the process takes up most of your team’s time today?
- Choose one specific proposal as a test case.
- Mark the information AI must not change.
- Check clarity and the approval process before sending.
- Compare customer questions and internal discussions with your current process.
A small test is what matters next Monday
Picture next Monday. A colleague opens the familiar proposal document, turns it into a clearly structured page and checks every statement before sending the link to the customer. Anyone who prefers to work on paper can also get the PDF. Your team does not have to overhaul its entire proposal process straight away.
For a small business, a test like this could mean less time spent on formatting and more time for conversations. In a larger sales team, it is also about consistent approvals and making sure different colleagues do not describe the same service in different ways. In either case, first establish what data will be processed and how long it will be stored.
Klarframe’s Smart Offer Optimizer can turn a PDF or Word document into a designed proposal page, with a link and PDF download. AI helps with the structure and wording. Your team reviews the result before it goes out. The question is whether this way of working fits your proposals and approval process.
Frequently asked questions
How can AI improve a proposal from a PDF?
An AI system can read the contents of an existing PDF, reorganise them and make the wording clearer. The result could be a proposal page that explains the starting point, services, process and next steps more clearly. Check prices, dates and scope yourself before sending it, because AI will not automatically know every agreement made in your customer conversation.
Are proposal pages better than PDF proposals?
It depends on what your customer needs. A proposal page can present information clearly and be shared internally by link. A PDF is still useful for records, printing and approvals. If both formats contain the same information, you can offer the benefits of each without limiting the customer to one format.
What should a good proposal page include?
The customer should be able to see what situation you have understood, what service you are offering, how the process works and what to do next. Explain costs and terms without relying on internal abbreviations. The more tailored the service, the more important it is to explain clearly what is included.
Can I use AI to process customer data for proposals?
That depends on the system, the data and the contractual terms. Check what information will be processed and how long it will be stored, and confirm the data protection requirements with the relevant people in your business. Only enter the data you actually need to prepare the proposal.
Does an AI-generated proposal need to be checked before it is sent?
Yes. Pay particular attention to prices, scope, dates, terms and any statements that could amount to a binding commitment. Also check that the wording fits the customer’s actual situation. Someone in your team should approve the proposal before it goes to the recipient.
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Sources
- Klarframe: Smart Offer Optimizer · klarframe.com
- Unlocking profitable B2B growth through gen AI · McKinsey & Company, 2025-03-27
- How agentic AI transforms B2B sales growth · McKinsey & Company, 2026-07-16
This article was researched and written with AI assistance and automatically checked against the sources listed before publication. More on our AI transparency
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Turn a document into a clear, visual proposal with a public link and downloadable PDF. The AI also optimises and personalises the content and makes the proposal more convincing.
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