How to Use AI to Write a Performance Review (5 Steps + Prompts)

It’s review season. You have six people to write up, a blank form for each, and a calendar that says they are due on Friday. You know who did great work and who struggled. Turning that into fair, specific sentences is the part that eats your evenings.

Here’s the short answer. To use AI to write a performance review, don’t ask it to “write a review for Sam”. Spend ten minutes collecting real evidence first: the goals, three to five concrete examples with results, one or two things to improve, and what you want for next quarter. Remove names and private details, give that to ChatGPT, Claude or Gemini with a clear prompt, then check the draft for vague praise and anything it made up. The AI does the wording. You keep the judgment.

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Can you use AI to write a performance review?

Yes, for the writing. Not for the verdict.

A chatbot is good at structure, tone and turning messy notes into clear paragraphs. It has no idea what your colleague actually did this year. If you feed it nothing, it fills the gap with friendly filler like “consistently exceeds expectations” or “a true team player”. That reads fine and tells the person nothing.

That matters more than it sounds. When Gallup looked at how reviews land, only 14% of employees strongly agreed their performance reviews inspire them to improve. Generic text is a big part of why. A review full of empty praise feels like a form someone had to fill in, because it was.

So the rule for this whole guide: you bring the facts and the decision, the AI brings the clear sentences. If you are in the EU, there is a legal reason too. The EU AI Act lists AI systems “intended to be used to make decisions” about promotion or termination, or “to monitor and evaluate the performance and behaviour” of workers, as high-risk (Annex III, point 4). Using a chatbot to polish your own written assessment is not the same as letting software rate people, but it is a good reason to keep the rating and the decision firmly with you. This is not legal advice; check your company’s HR policy before you start.

Step 1: Collect the evidence (10 minutes per person)

This is the step that decides whether the review is useful. Open a plain note and answer five questions for each person:

1. What were their goals for this period? Copy them from last review, the job description or your one-to-one notes.
2. Three to five specific things they did, with the result. Not “good with clients” but “took over the Jansen account in March, cut response time on their tickets from two days to same-day”.
3. One or two things to improve, with a real example. “Two of the four monthly reports went out late” beats “needs to work on time management”.
4. What you want from them next period. One or two clear goals.
5. The rating or outcome you have already decided. Decide this yourself before the AI writes anything.

Where do the examples come from? Your one-to-one notes, project updates, emails where someone thanked them, the tickets they closed. If you keep meeting notes, our guide on turning meeting notes into a report with ChatGPT shows how to pull the key points out of a pile of notes quickly.

A small tip from doing this myself: if you can’t think of three concrete results for someone, that is information. Ask them or a colleague before you write, rather than letting the AI paper over the gap.

Step 2: Strip names and private details

Performance notes are personal data. Before you paste anything into a chatbot, replace the name with “the employee” or a first initial, and leave out health, family situations and anything about pay you are not allowed to share.

Then check where your text goes:

• ChatGPT: on Free, Plus and Pro, “Improve the model for everyone” is on by default. You can turn it off under Settings, Data controls, or use a temporary chat, which is not used to train models. Business and Enterprise workspaces are not used for training by default (OpenAI, Data controls in ChatGPT).
• Claude: on Free, Pro and Max you choose whether your chats can be used for training, and you can change it in Privacy Settings. Team and Enterprise plans fall under commercial terms and are not part of that setting (Anthropic, Updates to Consumer Terms).
• Gemini: Google says that even with Keep Activity off, it still uses your chats to respond and to keep its service safe, including with help from human reviewers (Gemini Apps Privacy Hub).

The safest option is the AI tool your company already approved. If there isn’t one, anonymise first and use the privacy settings above.

Step 3: Give the AI a clear prompt

Now paste your notes in with a prompt that tells the AI what it may and may not do. This is the one I use:

You are helping a manager write a performance review.
Use ONLY the notes below. Do not invent results, numbers or examples.
If something is missing, list it under "Missing info" at the end instead of guessing.

Write the review in these sections:
1. Summary (3 sentences)
2. What went well (each point = what they did + the result)
3. Where to grow (each point = specific behaviour + what better looks like)
4. Goals for next period (2 goals, measurable)

Tone: warm, direct, plain English. No buzzwords like "rockstar",
"synergy" or "exceeds expectations". Max 400 words.

The rating is already decided: [rating]. Do not change it or argue with it.

Notes:
[paste your notes from Step 1]

Three parts of this prompt do the heavy lifting. “Use only the notes” stops the AI from inventing achievements. The “Missing info” list shows you where your evidence is thin. And stating the rating stops the text from drifting more positive or more negative than your actual decision.

Which tool? Any of the big three can do this. In my experience, Claude tends to write in a softer, more natural tone, and ChatGPT sticks to a fixed structure well. If you are choosing, our comparison of ChatGPT vs Claude for writing walks through the differences.

Step 4: Check for vague praise and bias

This is the step most people skip, and it is where AI can make your review better than what you would write alone.

Research by Shelley Correll and Caroline Simard at Stanford looked at real performance reviews and found that women were less likely than men to get specific feedback tied to business outcomes. In one company’s reviews, vague praise showed up in 57% of reviews for women against 43% for men (Harvard Business Review, 2016). Their advice is simple: use the same criteria for everyone, tie each piece of feedback to a result, and aim for reviews of similar length and detail.

You can ask the AI to check exactly that. After your draft is done, run a second prompt:

Review this performance review draft. Flag:
- any praise or criticism that is not tied to a specific example or result
- personality words ("abrasive", "too aggressive", "nice") instead of behaviour
- anything that is not in my original notes
Suggest a more specific rewrite for each flag.

If you write several reviews for people in similar roles, put them side by side and ask: “Do these reviews use the same criteria and a similar level of detail? Where is one much vaguer than the others?” That one question catches a lot.

Step 5: Make it sound like you

The person reading this knows how you talk. If the review suddenly sounds like a corporate brochure, they will notice, and they will trust it less.

Read the draft out loud. Swap any sentence you would never say in a meeting. Add one line only you could write: a moment you remember, a thank-you in your own words. Then delete anything from the AI that you can’t back up with an example.

If the tone still feels stiff, a quick pass with “make this sound like a friendly, direct manager talking to a colleague” usually helps. We cover more tone fixes in how to make an email sound more professional, and the same prompts work in reverse to make text sound less formal.

Example: the same review, before and after

Vague (what AI writes with no notes):

“Alex had a strong year and is a valued member of the team. Alex consistently delivers high-quality work and communicates well. Going forward, Alex should continue to develop leadership skills.”

Specific (what AI writes from real notes):

“Alex led the move of our client reporting to a shared dashboard in Q2. Clients now get their figures on the first working day of the month instead of the fifth, and two clients mentioned it in their renewal calls. Next period I’d like Alex to run the Monday planning meeting for two months, so the team gets used to coming to Alex with questions about priorities.”

Same person, same tool. The only difference is the ten minutes of evidence in Step 1.

Prompts for the hard parts

Writing constructive feedback without sounding harsh

Rewrite this feedback so it is honest and kind.
Keep the facts exactly as they are.
Structure: what happened, why it mattered, what better looks like next time.
Feedback: [your blunt version]

Write the blunt version first, in your own words. It is easier for the AI to soften an honest sentence than to sharpen a mushy one.

Turning comments into measurable goals

Turn these development points into 2 goals for the next 6 months.
Each goal: one sentence, a clear result, and how we will both know it's done.
Points: [your notes]

Preparing the conversation, not just the document

The written review is half the job. Gallup’s research also found that people who get feedback weekly rather than once a year are far more likely to say the feedback is meaningful (same Gallup article). The review should hold no surprises. Ask the AI: “Based on this review, what three questions might the employee ask me, and how could I answer them honestly?” Ten minutes with that list makes the meeting calmer for both of you.

Mistakes to avoid

• Letting the AI pick the rating. Decide first, then write.
• Pasting full names, health details or salary info into a personal chatbot account.
• Accepting numbers you didn’t give it. If the draft says “increased sales by 20%” and your notes don’t, delete it.
• Using one template for everyone. Six reviews that read the same tell your team you didn’t really look.
• Skipping the read-aloud. If you wouldn’t say it to their face, don’t put it in writing.

FAQ

Is it OK to use ChatGPT to write a performance review?

For the wording, yes, as long as the facts and the judgment are yours and you follow your company’s rules on AI and personal data. Many companies have an approved AI tool; use that if you have one.

Will my employee be able to tell?

They can tell when a review is generic. They can’t tell, and won’t mind, when it is specific, accurate and sounds like you. The edit in Step 5 is what makes the difference.

Can AI help with a self-review too?

Yes. The same steps work: collect your own results first, then ask the AI to structure them. Be extra careful it doesn’t inflate what you did.

How long does this take?

Plan on about 10 minutes for evidence and 10 to 15 for prompting, checking and editing, per person. The evidence step is the one not to rush.

Reviews and interviews have the same weak spot: vague questions. If you are interviewing for a new role or an internal move, see how to use AI to create interview questions tied to the real job.

Where to go from here

Reviews are one of many writing jobs where AI saves real hours once you give it good input. If you are hiring as well, the same approach works for writing a job description with AI, and our guide to using Claude for work shows more everyday tasks you can hand off.

Imagine next review season with your notes already collected, your prompts saved, and Friday evening free. That’s what we build together at Launchpad. Start on our home page, or sign up right here:

On the other side of the table? If your company asks you to rate yourself first, our guide on how to use AI to write a self evaluation uses the same evidence-first approach for your own review.