Generating quotes with AI: faster, still personal

From four hours to a draft that's actually right

Writing a quote takes many SMEs more time than it deserves. Not because it's hard, but because every quote starts from scratch again: finding the right wording, retyping prices, adjusting tone for the client, and hoping you didn't forget anything. Generating quotes with AI promises to speed up that process. The question is: where exactly, and what stays human work?

Specialist quoting tools like Offorte and Offri show in demos how a briefing plus a template produces a full quote within minutes. That works well for companies already using such a tool. For SMEs still drafting quotes in Word, a CRM, or loose PDFs, the real gain lies elsewhere: connecting AI to the data you already have, without switching to an entirely new platform.

What AI actually does when creating quotes

There are two distinct tracks, and it matters that you keep them apart before picking a tool.

Track 1: AI as a writing assistant inside a quoting tool. You upload a briefing (notes, email, PDF), pick a template, and the AI fills in text, structure and tone based on that. This is what Offorte and Offri offer.

Track 2: AI that generates quotes straight from your own systems. Instead of working inside a separate quoting tool, an AI agent pulls customer and product data from your CRM or ERP (for example Exact or AFAS), assembles a quote from that data, and formats it in your own house style. This requires more upfront build work, but fits better for businesses with recurring quote structures and high volume.

5 concrete use cases

1. Standard quote from an intake conversation. Notes from an introductory meeting get turned into a structured quote with the right modules and prices.
2. Quote generated directly from CRM data. Customer details, past purchases and pricing agreements are pulled in automatically, so nobody has to retype rates by hand.
3. Multiple quote variants at once. Generate a basic, mid-tier and premium variant simultaneously from the same template, so the client can choose.
4. Rewriting and sharpening existing quotes. Let AI turn an old, overly long or vague quote into a shorter, more persuasive version while keeping the numbers correct.
5. Automatic follow-up after sending. No response after a few days? A connected workflow automatically sends a friendly reminder, keeping the quote top of mind.

Comparison: which approach fits your business

How to approach implementation

1. Gather your best past quotes. The ones that won, not the ones you rushed together. This becomes the basis for your template or prompt.
2. Describe your tone of voice explicitly. Formal or informal, show VAT or not, which sales approach (needs-based or price-driven). AI doesn't know this by default.
3. Choose your starting point. Begin with an existing tool (Offorte, Offri) if your volume is low, or investigate a CRM connection if you send dozens of quotes per month.
4. Test on historical data. Have the AI process five to ten old briefings and compare the output to what a colleague would write. Watch for factual errors in prices and terms, not just style.
5. Build in a review step. Never send a quote automatically without human review, especially on price and delivery terms.
6. Measure after a month. How much time does a quote take now versus before, and has the win rate stayed stable or improved?

Not sure if this pays off for your business? A free AI scan shows where most time gets lost in your quoting process.

Where it often goes wrong

I see two pitfalls come up most often. The first: companies let AI generate and send a quote fully without checking whether the prices still hold. Price lists change, discount agreements are client-specific, and an AI working with outdated data presents that with just as much confidence as correct data. Always build in a check against current pricing, separate from the text quality.

The second pitfall: too little input, too high expectations. A one-line prompt ("write a quote for a website") produces generic text barely better than a free template found online. Output quality is directly proportional to briefing quality. Companies that invest ten minutes in a good briefing per client get back a quote that needs five minutes of fine-tuning before it goes out. Companies that skip that step still end up rewriting for half an hour.

For companies quoting in multiple languages (say, Dutch and English for international clients), there's a third point worth noting: don't have the AI translate literally, ask it to rephrase in the target language while keeping the same structure. Direct translation of sales language usually sounds unnatural.

What it actually costs

For off-the-shelf tools (Offorte, Offri) you pay a fixed monthly fee per user, usually as an add-on to an existing quoting subscription. For a custom integration with your own CRM or ERP, there's a one-off build cost on top. for a simple integration (customer data from CRM into a quote template) budget a few thousand euros one-off, plus a modest monthly cost for maintenance and AI usage. For more complex projects with multiple systems and approval steps, this climbs.

Also see our broader explanation of what an AI agent typically costs and which SME processes are best suited for automation first to get a realistic picture of investment versus time saved.

When it (still) doesn't pay off

• You send fewer than five quotes per month: the setup time of a tool rarely outweighs the gain.
• Every quote is genuinely unique custom work with no repeating pattern in structure or pricing.
• You don't yet have a fixed quote structure or pricing model: AI can't bring consistency to a process that's inconsistent to begin with.
• Your sales process is about to change significantly (new CRM, new service line): stabilize first, then automate.

Privacy and data sensitivity

A briefing often contains customer data, sometimes also pricing agreements that are competitively sensitive. The moment you paste that information into an AI tool, that party is processing personal data and possibly commercially sensitive information. For standalone AI tools (like a generic ChatGPT prompt), check whether a data processing agreement exists and where the data is stored, especially for business clients with their own procurement terms. If in doubt, a conversation with an AI advisor is a small effort compared to a data breach.

Frequently asked questions

Can AI send a complete quote independently?

Technically yes, but it's not advisable. Always build in a review step where a human checks the quote, prices and terms before it goes out the door.

Does this work if I don't have fixed templates?

It works better with a template, because the AI draws structure and style from it. Without a template you get a generic quote that still needs substantial editing. Invest a few hours in one solid template first, it pays for itself very quickly.

Is a standalone AI subscription (like ChatGPT) enough, or do I need a quoting tool?

For small volumes and a fixed structure, a well-crafted prompt in ChatGPT or Claude works fine. Once you work with multiple employees, need CRM integration, or require automatic follow-ups, a specialized tool or custom agent is more stable.

Does AI increase the chance a quote gets accepted?

That depends entirely on the content, not on the fact that AI wrote it. An AI-generated quote that's factually correct, well-structured and matches the client's request performs better than a rushed one, but the quality of your briefing and template determines the result.

Can I use AI if I work in a niche industry with specific terminology?

Yes, provided you feed the AI with your own example quotes and industry terms in your template or prompt. Without that context, the AI defaults to generic language that lands less convincingly in your industry.

Ready to create quotes faster that actually hold up?

Want to know whether a quoting tool or a custom AI agent fits your business better? Request a free AI scan, or get in touch via contact for a no-obligation introduction.