Short answer: yes, for some of it, and it will actively hurt you for the rest. The line between the two is not where most people put it.
Around two thirds of job seekers now use an AI assistant somewhere in their application process. That is not a trend to resist, it is the current baseline. The question worth answering is narrower and more useful: which parts of writing a resume does a language model do well, and which parts does it quietly ruin?
What It Is Genuinely Good At
Cutting your writing down. Paste a bullet you like but which runs to three lines, ask for it in one, and you will usually get something tighter than you would have managed alone. Editing your own writing is hard because you already know what you meant.
Finding repetition. Paste the whole resume and ask which words appear too often. Almost everyone has a verb they lean on without noticing. This takes ten seconds and consistently finds something.
Translating jargon. If your work involves internal systems and team acronyms, a model is good at rendering that into language an outsider understands. Give it the internal version and ask for the plain one.
Reading a job posting back to you. Paste the posting and ask what this employer appears to care about most. It is decent at surfacing the emphasis you skimmed past, which is genuinely useful before you tailor anything.
Interview preparation. Ask it to challenge a specific bullet the way a skeptical interviewer would. This is the best use on the list and almost nobody does it.
What It Is Bad At, and Why
Writing your experience. A model asked to describe a marketing coordinator's achievements will produce a competent description of what marketing coordinators generally do. It reads well. It is also about a hypothetical person, because the model has no access to what actually happened in your job.
The output tends to be smooth, round, and unfalsifiable: "increased engagement by 40%", "streamlined cross functional workflows", "drove significant improvements". Those are the exact sentences four hundred other applicants are also submitting, which we went into in recruiters are drowning in AI resumes.
Numbers. If you did not give it a figure, any figure it produces is invented. This seems obvious and people fall for it constantly, because a plausible number in fluent prose does not feel like a fabrication until an interviewer asks how you measured it.
Formatting and layout. Ask for a formatted resume and you will typically get markdown, or a table, or a layout that falls apart the moment it becomes a PDF. Multi column output in particular is where automated parsing breaks, as our guide on ATS friendly resumes explains. The document you send matters more than the text you generated.
Knowing what to leave out. Models add. Asked to improve a resume, they will lengthen it, because more looks like more effort. Almost every resume improves by getting shorter, and that judgement is yours.
A Workflow That Works
- Write the ugly version yourself. Bullet points, no polish, every fact and number you can remember. This is the only step that cannot be delegated, because it is the only step that requires having been there.
- Hand it over for editing, not creation. "Here is what I did. Make each of these one line, keep every number, do not add anything I did not say." The last clause matters.
- Check every claim against reality. Read the output and confirm each statement is something you could defend for two minutes under questioning. Delete anything that fails.
- Do the layout in a real tool. Not in the chat window. You need something that produces a clean PDF and does not scramble when parsed.
- Read the final version aloud. If a sentence does not sound like something you would say, it will not sound like you in the interview either.
The Detection Question
People ask whether recruiters can tell. Mostly they cannot tell reliably, and the tools claiming to detect AI writing are not dependable enough to bet a hiring decision on.
But this is the wrong thing to worry about. The risk is not being caught by a detector. It is that generated text is generic by construction, so it fails to distinguish you at exactly the moment when four hundred applications need distinguishing. And it is that anything invented has to survive a conversation with someone who does this for a living.
Use it as an editor and it is one of the better tools available. Use it as a ghostwriter and it will produce a resume that is fluent, forgettable, and occasionally indefensible.
One Practical Note
Whatever you generate, get it into a document properly. Copy the final text into a real builder, pick a layout that parses cleanly, adjust the font size until it fits the page without cramming, and export a PDF you have actually opened and looked at.
The writing is the part AI helps with. The document is the part that gets you read.