Almost every guide on this lands in the same place: "AI is a starting point, not the finish line." True, and useless — it never says which parts you're supposed to finish.
Short answer: use AI for structure and pressure-testing, not for the claims. The parts of a cover letter that persuade are the parts only you can supply — a specific number, a specific project, a specific reason this company and not the twenty others. AI cannot invent those, and when it tries, it produces the exact sentences that get letters skimmed and dropped.
That sounds like the same advice as everyone else until you make it testable. So here is the test, and then the specific places AI helps and hurts.
First, the question everyone actually has: can they tell?
This is the wrong thing to worry about, and the reason is worth understanding because it changes what you should do.
AI-text detectors are unreliable in both directions. They flag human writing as machine-written and clear machine text as human, and the people running them know it. Very few hiring teams are running your cover letter through one, and the ones that do can't trust the result.
The real risk isn't detection — it's sameness
A recruiter reading forty applications for one role doesn't need a detector. They notice that letters 6, 19, and 33 make the same three points in the same order with the same enthusiastic register. No single letter looks fake. The set looks identical. That's what costs you, and no amount of "make it undetectable" fixes it.
So stop optimizing for not getting caught and start optimizing for not being interchangeable. Those pull in completely different directions: the first one makes you rewrite words, the second one makes you add facts.
The one-minute test
Take the draft — AI-written or not — and highlight every sentence that could appear, word for word, in a stranger's cover letter for a different job. Not the badly written sentences. The transferable ones.
A fully AI-generated letter usually comes back almost entirely highlighted. That is the whole problem, visible in about a minute. It's the same test that catches human clichés — I wrote it up with nine worked examples in cover letter phrases to replace — and AI just produces them faster and more fluently.
Typical AI first draft vs. what survives the test
❌ Before: I am excited to apply for the Product Designer role at Northwind. With my strong background in user-centered design and my passion for creating intuitive experiences, I am confident I would be a valuable addition to your team.
✅ After: Your onboarding flow asks for company size before it asks what the user wants to do — I redesigned almost exactly that sequence at Brightline last year and cut drop-off on step two by a third.
The second version is not better writing. It is the same writing with a fact in it. AI could have produced that sentence structure; it could not have produced the fact.
Where AI genuinely helps
Three jobs it does well, all of them structural rather than substantive:
- Pulling requirements out of the job description. Paste the posting and ask what it is actually screening for, ranked. This is fast, accurate, and boring — exactly what you want a machine doing.
- Reordering what you already wrote. Give it your five bullet facts and ask which order makes the strongest case for this specific posting. It is good at this and you are worse at it, because you are too close to your own history.
- Cutting. "Take this to 200 words without removing any specific number or project name." That constraint is the whole trick — it forces the hedges and adjectives out and leaves the evidence in.
Notice that none of these ask AI to know anything about you. You supply the facts; it handles arrangement, compression, and reading the posting closely.
Where it gets you rejected
- Inventing achievements. Ask for an impressive letter with thin input and you will get numbers you cannot defend. Same failure mode as AI resume rewriting — the invented line is always the one they ask about.
- Guessing at the company. "I admire your commitment to innovation" means the model had nothing to work with. If you cannot name something specific about them, do not let a sentence pretend you can.
- Register drift. Left alone, most models write a register warmer and more formal than how the company writes. Read the job posting's own tone and match it.
- The em-dash-and-triads voice. Not a moral problem — a sameness problem. Three-part lists and heavy em-dashes turn up in every letter in the pile.
Prompts that produce usable drafts
The difference between a usable draft and a discardable one is almost entirely in how much raw material you hand over. These work because they front-load your facts and constrain the output:
- Extract first: "Here's the job posting. List the five things this role is actually screening for, in priority order, quoting the line each one comes from."
- Then supply evidence: "Here are six things I've done, with numbers. Map each to the requirements above and tell me which two make the strongest case — and which of my six are irrelevant here."
- Then draft, constrained: "Write a 220-word cover letter using only the facts I gave you. No adjectives about my character. No sentence that could appear in someone else's letter. Open with the company-specific observation I wrote, not with my name or the role title."
- Then attack it: "Highlight every sentence in this draft that could appear unchanged in a different applicant's letter for a different job." — this one is the most useful prompt on the list.
Same model, same job, different prompt
❌ Before: Write me a cover letter for a product designer role at Northwind. Make it sound enthusiastic and professional.
✅ After: Job posting below. My facts: cut onboarding drop-off 31% at Brightline; ran design system for 4 engineers;
noticed Northwind asks company size before intent on step one.
Write 220 words using ONLY these facts. No adjectives about my character.
No sentence that could appear in another applicant's letter. Open with the Northwind observation.The instruction that changes the output most
"Use only the facts I gave you." Without it the model fills gaps with plausible-sounding invention, and you end up proofreading for lies instead of editing for strength.
A workflow that takes about twenty minutes
- Spend five minutes writing raw facts — numbers, project names, one thing you noticed about the company. Ugly bullets are fine. This step is not optional and AI cannot do it.
- Have AI extract what the posting screens for, and map your facts against it.
- Have it draft under the constraints above.
- Run the highlight test. Replace every highlighted sentence with a fact or delete it.
- Read it aloud once. Anything you would not say out loud to a person, cut.
Step 1 is where the letter is actually won, and it is the step people skip because it is the only part that feels like work.
If you'd rather not assemble the prompt chain yourself, our cover letter tool runs this shape — job posting in, your real experience mapped against it, no invented claims. — Try the cover letter tool
FAQ
Is it dishonest to use AI for a cover letter?
Using it to arrange and compress your own facts is no different from using a spellchecker or asking a friend to read a draft. Using it to generate achievements you did not have is dishonest — not because a machine wrote it, but because the claim is false. The line is the claims, not the tool.
Are free AI cover letter generators good enough?
The model quality is rarely the limiting factor — your input is. A free tool fed six specific facts beats an expensive one fed a job title. Judge a generator by how much it asks you for, not by what it promises: anything that produces a letter from just a role and a company name is producing a letter about nobody.
Why does Reddit tell me AI cover letters don't work?
Because the letters people complain about are the fully-generated kind, which are transferable start to finish — and that criticism is correct. The disagreement isn't really about AI. It's about whether you did step 1.
Should I disclose that I used AI?
Not unless the employer asks, and some now do — a few applications include an explicit question about it. If asked, answer straight: you used it to structure and tighten your own material. That answer is easy to give when it's true, which is another reason to keep the claims yours.
Originally published at resuhive.com.
