How I Slashed My Freelance Proposal Time by 60% Using AI

How can AI help you to spend less time crafting even more personalized offers? 

Sure, artificial intelligence can help you expedite the process. But first of all - you need to have a sound client onboarding process. In this article, I share the AI-powered methodology I have learned — and am still learning — to cut by 60% the time I spend crafting proposals, while feeling more confident every time I send one out.

Here's exactly how it works.

Let's be honest. Who hasn't spent hours crafting a proposal, only to get rejected or worse, ghosted?

In most cases, it comes down to one of two things: you didn't understand the client's needs well enough, or your offer was too hard to digest.

Let’s cover the first pain point.

A discovery call is the first time you exchange for a longer period of time - more than a few written  messages. It plays an important part for you (you get to understand the client needs more accurately) and the client (you are already showing your work methodology).

Without this call, you cannot set up a personalized offer - so don't skip this important step. Most freelancers show up underprepared, hoping the conversation will naturally reveal what the client needs or do not value their potential client’s precious time.

Spoiler alert: it won’t, because many clients are not aware of their actual problem.

Spend at least 30 minutes before the call doing your own research. Not to show off, but to ask better questions that you will feed into your AI. Here's what I look for as an SEO/content strategist helping companies expand to France or Germany:

• Is the website actually localized, or just AI-translated?
• If I type their main keyword, who shows up: them or their competitors?
• Does their local presence inspire trust?
• How do their competitors rank on the top 3 keywords?

The rule of thumb is simple: if you can find 75% of the answers online before the call, don't waste time asking them during it. Save the call for what really matters: convincing them that you are the right person for the job.

A 30 to 45-minute call is enough if it's well structured. Here's the format I use systematically with every new prospect:

I share this agenda with the client before the call. It sets the tone and shows them that I value their time.

One practical tip: record the call with an AI tool like Fireflies or Otter.ai, but also take handwritten notes on the key points. AI-generated summaries are convenient, but they obliterate your ability to remember what actually mattered. The act of handwriting keeps you present.

Before the call ends, agree on a date to send the offer. Not "I'll send it soon." A specific date. It creates accountability on both sides and materializes the relationship.

AI best practices ✅

• Researching the client's market before the call
• Recording and transcribing the call
• Summarising key takeaways after the call

From the moment I started using a template, the time I was spending on crafting the offer started to dwindle. Here is what it contains:

1. The need/problem — restate what you heard: in their words, not yours
2. The main goals — what success looks like: concretely and measurably
3. The strategy — broken into steps: each with sub-goals, methodologies, and deliverables
4. The price — No need to add the full details, but be ready to break down the costs
5. Dashboard/calendar — how the project will be tracked over time
6. How to reach you — frequency and method of communication
7. Next steps — clear, numbered, and actionable

The first time I used this template, it took me four hours to complete it, including back-and-forth with my mentor as part of Alexis Minchella's bootcamp for freelancers. But once it existed, offer crafting went from a dreaded task to a structured, straightforward exercise.

Once the template is solid, feed it to your AI. Not the structure alone -  feed it a real completed offer, so it understands what each section actually means in practice. If you feed the theory only, the quality of the output might not be ideal.

For instance, my AI now knows that "methodology" means only how I will achieve specific goals, not a generic description of my services. And that "deliverables" is a short callout box with three bullet points maximum, not a five-paragraph explanation.

That distinction took one real offer and one correction session to establish. Now it holds every time.

Once the call is done, extract the full transcript from Fireflies, not the AI summary. Add any relevant emails the client sent beforehand. Paste everything into your AI (I use Claude).

Then ask it to draft one section at a time, not the full offer in one go to ensure the best quality. One section, check it, correct it, move on to the next. This keeps you in control and prevents the AI from going off in the wrong direction and hallucinating.

A few mistakes the AI will make if you let it:

It will over-enumerate. Three adjectives in a row, bullet points where a sentence would do, "innovative, results-driven, client-centric" type of language. Tell it explicitly to avoid this.

It can mix up clients. If you use the same chat session across multiple proposals, the AI can start blending contexts. However, I do use the same chat to make sure my AI is learning. Just check that the information is correct, and be sure to let it know when it hallucinates

It will give you random pricing. More on that in the next section, but never let the AI decide what you charge. That part stays human, like you!

AI best practices ✅

• Feed an offer template to your AI
• Feed the call transcript (not the summary, you might miss important details left behind by the tool’s AI) to your own AI
• Drafting each section from the call transcript 

"All of that still doesn't tell me how much I can charge." I know. And if you bluntly ask an AI, the answer will be "it depends". I’d break it down between daily rate and packages:

If you're working with a fixed daily rate, start with an AI-free reality check. Malt gives you a solid overview of what the market actually pays. Filter by what matters: 

• expertise
• location
• industry
• whether the role requires specific languages. 

Then comes the harder part: estimating how long a project will actually take. This is where most freelancers undercharge, sometimes because they don't know their worth or because they underestimate their time.

Here's a simple habit that fixes this over time. At the end of each project, open a dedicated AI chat and debrief: how long did it take, what did you deliver, what would you do differently? Over months, this builds a pricing memory, not a vague feeling that a project was underpaid, but actual patterns.

Packages shift the conversation from time to value. The client stops asking "how long will this take?" and starts asking "what will I get?" That's a much better conversation to be in.

Track your time anyway — I use Toggl for every project — not to bill by the hour, but to understand your own economics. During your first projects, the return on investment might feel thin and it’s ok, the point is to build data to charge better in the future.

Here's a real example. Twice a week, I send a keyword tracking overview to a client I'm helping expand to France. He does not care how long it takes me. But that raises an honest question: is it OK to just copy-paste the summary automatically generated by my SEO tool?

If the client pays little, maybe. But if the client pays well — and in this case, he does — then no. That overview gives him strategic information he uses to make real decisions. Copy-pasting an AI-generated summary would quietly cancel the added value I'm supposed to bring. And honestly, would you like that if you were the client?

What AI does here is cut the donkey work: gathering data, formatting, fixing grammar. What it doesn't do is think, and that part stays mine. Less time spent, more value delivered.

AI best practices ✅

• Debriefing after each project 
• Documenting your economic journey over time 
• Identifying patterns across past offers 

Feed a dedicated AI chat with three things after every project:

1. The offer you sent
2. The time you actually spent (track it on Toggl)
3. A short note on how it went: what you delivered, what drifted, what you'd charge differently

After a few months, you'll have something no tool can generate for you from scratch: a documented economic journey instead of a vague gut feeling. These actual patterns will tell you when you're undercharging, when a certain type of client will consistently expand scope, and when a deliverable is worth more than you think.

AI won't make you a better freelancer or magically tell you what price suits you best. Remember, a bottle of water at the beach bar costs more than from a supermarket, so pricing is based on many factors and context is vital. But used well, AI will help you track your projects and you organize a pricing methodology and routine – that will set you apart from other freelancers. 

The 60% time saving is real. But the remaining 40% –  the judgment calls, the reading of the room, and the decision of what to charge – that part stays yours.

And honestly, that's the part clients are paying for.