Category: AI at Work

The project went well. The client said so on the last call. And the case study you promised yourself you’d write has now been sitting on your to-do list for three weeks, because every time you open a blank document you don’t know where to start.

Here’s the short answer. To write a case study with AI, don’t ask ChatGPT or Claude to write one from nothing. Give it the real material first: a client interview transcript, the before and after numbers the client agreed to, and your own project notes. Ask the AI to pull out the challenge, the solution, the results and the best direct quotes, then draft it in a simple Challenge, Solution, Results shape. You check every number and every quote, and the client approves it before it goes anywhere. The AI does the sorting and the first draft. You do the truth.

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Why case studies stall, and what AI actually fixes

Most case studies don’t fail because people can’t write. They fail at three points:

• The blank page. You know the project was good, but turning a messy three-month engagement into a clean story feels like a whole afternoon.
• Scattered material. The results are in a spreadsheet, the nice thing the client said is in a Slack message, and the timeline lives in your head.
• The approval loop. You write it, send it to the client, and it waits in their inbox.

AI is genuinely good at the first two. It can read a 40-minute interview transcript and hand you the five strongest quotes in a minute. It can take bullet points and turn them into readable paragraphs. What it can’t do is know what happened. If you give it gaps, it fills them with confident, plausible sentences that may be false. That’s the one rule for this whole process: the AI only works with facts you give it.

Using AI to write is not a problem for search either. Google’s own guidance says it rewards helpful, original content however it is produced, and that using automation mainly to manipulate rankings is what breaks its rules (Google Search Central). A case study built on a real client and real results is about as original as content gets.

Step 1: Collect the raw material (15 minutes)

Before you open any AI tool, put these in one document or folder:

• The client interview. A 20 to 30 minute call is enough. Record it with the client’s permission and use the built-in transcript. Microsoft Teams can produce a live transcript during the meeting (Microsoft Support), and most other meeting tools have something similar.
• Before and after numbers. Hours spent per week, response times, error rates, revenue, whatever you actually measured. Only numbers the client knows about and agrees with.
• Your project notes. What you did, in what order, which tools, what went wrong and how you fixed it.
• Anything the client already said in writing. A thank-you email or a message after go-live is often the best quote you’ll get.

If you already turn meetings into notes with AI, the same habit works here. Our guide on summarizing meeting notes with ChatGPT covers that part.

What not to paste: client financials they haven’t agreed to share, personal data of their customers, or contract details. Check your AI tool’s data settings before you upload anything sensitive. ChatGPT, for example, lets you switch off “Improve the model for everyone” in its data controls (OpenAI Help Center). If the client hasn’t agreed to be named yet, replace their name with “the client” in what you paste.

Step 2: Let AI prepare the client interview

A good case study depends on good answers, and good answers depend on good questions. Most people ask “so, how did it go?” and get “great, really happy”. Ask AI to help you dig for the specific stuff.

I'm writing a customer case study about a project I did for a client.
Project: [one or two lines on what you did]
Client type: [e.g. 6-person design studio]

Write 8 interview questions for a 25-minute call with the client.
* Cover: the situation before, what they had tried, why they picked us, what changed, what they would tell a peer.
* Ask for specifics: numbers, moments, examples. No yes/no questions.
* Keep each question short enough to read out loud.

Questions that tend to pull out the best material sound like this:

• “What was a normal Monday like before we started?”
• “What had you already tried, and why didn’t it stick?”
• “Was there a moment you noticed it was working? What happened?”
• “If a friend in your industry asked about this, what would you tell them?”

That last one is gold. People answer it in their own words, and it often becomes the headline quote.

Step 3: Extract the story from your material

Now paste the transcript and your notes into ChatGPT, Claude or Gemini and ask it to sort, not write. This is where you save the most time.

Below is a client interview transcript and my project notes.
Use ONLY what is in this text. Do not add facts, numbers or quotes.

Give me:
* The challenge: what was going wrong before, in the client's words where possible
* What they tried before
* Why they chose to work with me
* What I did, step by step
* Results: every number mentioned, exactly as stated, with who said it
* The 5 strongest direct quotes, word for word, with the timestamp
* Missing information: questions I should ask the client to fill the gaps

[paste transcript]
[paste notes]

The last line matters most. Instead of guessing, the AI tells you what is missing (“the transcript mentions faster invoicing but gives no number”). You send those questions to the client in one short email.

Claude handles long transcripts well, and if you write case studies regularly, a Claude Project lets you keep your template, your past case studies and your instructions in one place so every new one starts from the same base (Claude Help Center). We go deeper on that in how to use Claude for work.

Step 4: Draft it with a shape buyers can scan

People rarely read a case study top to bottom. They look for “is this company like mine?” and “what was the result?”. Nielsen Norman Group’s research on web reading found that most users scan pages rather than reading word by word (Nielsen Norman Group). So the shape does half the work:

1. Headline with the result: “How a 6-person studio stopped chasing invoices” beats “Case study: Studio X”.
2. Summary box: client, challenge, solution, result, in four short lines.
3. The challenge: the before picture, with a client quote.
4. The solution: what you did, in plain steps. No jargon.
5. The results: the numbers, bolded, plus one quote about how it feels now.
6. What’s next: one or two lines, and a way to contact you.

Then ask the AI to draft into that shape:

Using only the extracted facts above, write a customer case study.
Structure: headline with the main result, a 4-line summary box (Client, Challenge, Solution, Result), then sections Challenge, Solution, Results, What's next.

Rules:
* 600 to 900 words
* Use the client's quotes word for word. You may cut a quote shorter, never change its meaning
* Every number must come from the facts above. If a number is missing, write [NUMBER NEEDED]
* Plain, warm language. No buzzwords like "game-changer", "seamless" or "revolutionize"
* Write for a reader who runs a business like the client's

The [NUMBER NEEDED] rule is the trick. It stops the AI from inventing a “37% improvement” to make the paragraph sound better.

A worked example

This example is made up to show the shape. Your case study uses your client’s real words and numbers.

Say you’re a freelance automation consultant. You set up an invoice reminder workflow for a small design studio. In the interview, the owner says: “I used to spend Friday afternoons going through who hadn’t paid. Now I don’t think about it.” Your notes say the studio sends around 30 invoices a month and the owner estimated about three hours a week on chasing before.

A first AI draft from that material might open like this:

How a 6-person design studio stopped spending Friday afternoons chasing invoices

Client: independent design studio, 6 people
Challenge: about 3 hours a week spent checking and chasing unpaid invoices
Solution: an automated reminder workflow connected to their invoicing tool
Result: [NUMBER NEEDED: hours per week now]. "Now I don't think about it."

Notice what it did right: it used the owner’s exact words, kept the “about” in “about three hours”, and flagged the missing after-number instead of making one up. Your job is to get that number from the client, and to read the rest line by line.

Step 5: Fact-check, then get the client’s approval

This step is not optional, and it’s where your reputation lives. A case study is a public statement about a real business. If a quote is twisted or a number is inflated, the client sees it first.

There’s also a legal side. In the US, the FTC’s Endorsement Guides say endorsements must reflect the honest opinions and experience of the person giving them (FTC), and since October 2024 an FTC rule explicitly bans fake testimonials, including AI-generated ones (FTC press release). Rules differ by country, but the safe habit is the same everywhere: real quotes, real numbers, written approval.

Make the check fast with one more prompt:

Go through the case study draft and list every sentence that contains:
* a number
* a direct quote
* a claim about the client's business or results
For each one, show where it came from in the transcript or notes. If you can't find a source for it, say "NOT IN SOURCE".

Anything marked “NOT IN SOURCE” gets cut or confirmed with the client. Then send the draft with a short note: “Here’s the draft. Can you check the quotes and numbers, and let me know if you’re happy for us to use your name and logo?” Keep that reply email. It’s your written approval.

If the client says yes to the story but no to their name, you can still publish an anonymized version (“a 6-person design studio in Rotterdam”). It’s less strong, but it’s honest and still useful.

Step 6: Turn one case study into four useful pieces

Once it’s approved, the hard work is done. Ask the AI to reuse it:

From this approved case study, write:
1. A LinkedIn post (under 150 words) that tells the story from the client's problem, with one quote
2. A 3-sentence version I can paste into proposals
3. A short follow-up email to a prospect in the same industry
4. Text for one presentation slide: headline, 3 bullet points, 1 quote
Use only the facts and quotes in the case study.

The proposal snippet is the one people forget, and often the most valuable. If you write proposals with AI, our page on ChatGPT for proposal writing shows where proof like this fits. And if a client result is big enough for news, the same material can feed an AI-written press release.

Which AI tool should you use?

Honestly, any of the big ones will do this well, because the quality comes from your material, not the model. A few practical differences:

• ChatGPT: good all-rounder, easy for the extract and draft steps, and handy for the social and email versions.
• Claude: comfortable with long transcripts, and Projects keep your template and past case studies together.
• Gemini: practical if your transcripts and notes already live in Google Docs and Drive.
• Copilot: the natural choice if your company runs on Microsoft 365 and Teams transcripts.

What about a dedicated “AI case study generator”? Most of them are a prompt like the ones above with a form on top. They can be convenient, but they still need your real facts, and you still need to check the output. Try the prompts here first before paying for another subscription.

A finished case study is also strong proof for funding applications. If you are applying for one, see how to use AI to write a grant proposal to turn those results into a Statement of Need.

Common mistakes to avoid

• Asking AI to “write a case study about how I helped a client save time”. You’ll get a generic story with invented numbers. Always start from the transcript.
• Polishing quotes until they sound like marketing. Real people don’t say “leveraged a streamlined solution”. Keep their words. Trim, don’t rewrite.
• Burying the result. If the best number sits in paragraph six, most readers never see it. Put it in the headline and the summary box.
• Making it about you. The hero of a case study is the client. You are the guide who helped.
• Skipping approval because “they’ll be fine with it”. Most clients are. Ask anyway, in writing.

FAQ

Can AI write a case study for me?

It can write the draft, and do it well, if you give it real material: a transcript, notes and numbers. It can’t write a true case study from nothing, because it doesn’t know what happened. Treat it as a fast assistant that organizes and drafts, not as the source.

How long should a business case study be?

Long enough to show the before, the change and the result, and short enough to read in a few minutes. Around 600 to 900 words works for most service businesses, plus the summary box for people who only skim.

Do I need the client’s permission?

Yes. Get written approval for the quotes, the numbers and the use of their name and logo. Even if your contract doesn’t require it, it protects the relationship, and in many places it’s also the legally safer route.

What if the client won’t share numbers?

Use what they’re comfortable with. “Invoices now go out the same day the project closes” is a real result without a percentage. Ask the AI to rewrite the results section around concrete changes instead of metrics, and never let it guess numbers.

Can I use the same prompts for a UX or portfolio case study?

Mostly, yes. Swap the client interview for your own process notes, research findings and screenshots, and change the structure to problem, process, decisions and outcome. The same rule applies: only facts you provide.

A finished case study also gives you strong proof for your website. To turn those results into clear page copy, read how to write website copy with AI.

Your next 30 minutes

Pick the client project you’re proudest of from the last six months. Send them a short message asking for a 25-minute call. While you wait for a reply, run the interview question prompt from Step 2. That’s the case study started, and the hardest part, getting going, is behind you.

If you’d like to build more workflows like this one, from meeting notes to proposals, start on our home page or grab the free Launchpad below.

Get one practical AI workflow in your inbox every week.

When the case study feeds a client pitch, our guide to AI proposal writing software covers when chat tools are enough and when dedicated software helps.

You have real news. A new product, a second location, a partnership you worked on for months. Now someone says “send out a press release” and you’re staring at a blank page, wondering how the big companies make it sound so official. You don’t need an agency for this. You need your facts in order and a good first draft.

Here’s the short answer. To use AI to write a press release, first write a short fact sheet yourself (what happened, who, when, where, why it matters, one real quote, one contact). Paste it into ChatGPT, Claude or Gemini with a prompt that asks for the standard press release structure and forbids hype words. Then run two checks: a hype pass and a fact pass. The AI handles the format and the wording. You own every fact.

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Why most AI press releases get ignored (and how to avoid it)

Press releases are not dead. In Cision’s 2025 State of the Media survey of more than 3,000 journalists, 72% called press releases the most useful resource PR teams can give them. The same survey found that 72% worry about factual errors in AI-generated PR content.

That’s the whole story in two numbers. Reporters want releases. They don’t trust sloppy AI ones. Among newspaper journalists, Cision reports that half are opposed to receiving AI-generated pitches or press releases.

Muck Rack’s 2025 State of Journalism survey points the same way: the top reasons journalists delete a pitch are that it’s irrelevant to them (86%) or overly promotional (71%). And what does a chatbot do when you ask it to “write an exciting press release”? It reaches for “revolutionary”, “game-changing” and “industry-leading”. Exactly the tone that gets deleted.

So the trick is not to ask AI for a press release. The trick is to give it facts and rules, and let it do the part it’s actually good at: structure, clear sentences and the right length.

Step 1: Write a 5-minute fact sheet (this is the part AI can’t do)

Before you open any chat, answer these in plain notes. Half sentences are fine.

• The news in one line: what is new, today, that wasn’t true yesterday?
• Who: your company, plus any partner, with names spelled correctly.
• When and where: the date of the announcement and the city it comes from.
• Why it matters, and to whom: the customer, the town, the industry. Be specific.
• Two or three facts with proof: numbers you can back up, a price, an opening date, how many people it affects.
• One quote in your own words: say out loud why you did this, record it on your phone and type what you said. Rough is fine.
• Media contact: a real name, email and phone number.
• Boilerplate: three sentences about your company that you’d be happy to see printed.

If you can’t fill in “why it matters, and to whom”, stop here. That’s not a writing problem, and no AI will fix it. Find the angle first, then write.

Step 2: Use the drafting prompt

Paste your fact sheet into a new chat, then paste this underneath. It works in ChatGPT, Claude, Gemini and Copilot.

Act as an experienced PR writer who used to be a journalist. Above is my fact sheet.

Write a press release using ONLY the facts above. Do not add numbers, names, dates or claims that are not in my notes. If something important is missing, ask me instead of guessing.

Structure:
* Headline: under 12 words, states the news plainly
* Subheadline: one sentence with the most useful detail
* Dateline: [CITY], [DATE]
* First paragraph: who, what, when, where and why, in 2 to 3 sentences
* Second paragraph: the most important supporting facts
* One quote, based on my words, kept sounding like a real person
* Practical details: price, date, address, link, availability
* About [company]: use my boilerplate
* Media contact
* End with ###

Rules:
* Keep it to one page
* No hype words: revolutionary, game-changing, cutting-edge, leading, innovative, excited to announce, thrilled
* Short sentences. Write for a busy reporter who reads only the first paragraph.

The line “ask me instead of guessing” is the most important one. Without it, many chatbots fill gaps with plausible numbers. With it, you’ll often get two or three good questions back, like “Is the opening date confirmed?” Answer them, and the draft gets better.

Step 3: Run the hype pass

Even with rules, adjectives sneak back in. Ask for a second look:

Read the press release again as a skeptical local reporter.
* List every word or sentence that sounds like marketing instead of news.
* For each one, suggest a plain replacement that uses a fact from my notes.
* Tell me which sentence a reporter would most likely copy into their story. If none, say so and tell me what is missing.

That last question is a good test. A reporter with little time often lifts the first paragraph and the quote. If neither works on its own, rewrite them before anything else.

Step 4: Run the fact pass (never skip this one)

This is where AI press releases go wrong, and where journalists lose trust. Ask the AI to show its work:

Make a table of every factual claim in the press release: names, numbers, dates, prices, places, titles.
For each claim, quote the line from my fact sheet it came from.
Mark any claim that is NOT in my fact sheet with "CHECK".

Then you go through the table yourself. Check the spelling of every name, every date against the calendar, every number against your own records. Anything marked “CHECK” either gets a source from you or gets deleted. Two minutes of checking protects your name with the reporter for the next five releases.

Step 5: Make the quote sound like a person

AI quotes all sound the same: “We are thrilled to bring this exciting solution to our valued customers.” Nobody talks like that, and a reporter has no reason to print it.

Use the voice memo from Step 1. Ask the AI to tighten what you actually said, not to invent a new quote:

Here is what I said out loud about why we did this: [paste your words].
Turn it into a quote of 2 to 3 sentences. Keep my words and my opinion. Remove filler words only. No new claims.

A good quote says something the facts can’t: a reason, a story, an opinion. “Half our customers drove 40 minutes to reach us. Now they don’t have to.” That’s a quote someone will print.

An example: before and after

A made-up example, so you can see the difference. A bakery opens a second shop. Here’s the kind of opening paragraph a chatbot writes when you just say “write a press release about our new bakery location”:

Sunrise Bakery, a leading artisanal bakery, is thrilled to announce the exciting launch of its innovative new location, bringing its passion for exceptional baked goods to even more valued customers.

And here’s what the same prompt gives you after the fact sheet, the rules and one hype pass:

AMERSFOORT, 14 November 2026. Sunrise Bakery opens its second shop on Langestraat on Saturday 21 November, three years after starting from a single oven in Leusden. The new shop bakes on site from 6:00 and adds a lunch counter with 20 seats.

The first version tells a reporter nothing. The second one answers who, what, when and where in two sentences, and they could paste it straight into a short local news item.

Step 6: Write the pitch email (shorter than you think)

A press release on its own doesn’t get coverage. The email you send it with does the work. In the same Muck Rack survey, 69% of journalists preferred pitches under 200 words, and half said one follow-up is fine.

Write a pitch email to [reporter name] at [outlet], who covers [beat]. Here are two of their recent articles: [titles or short summaries].
* Under 150 words
* First line: why this matters to THEIR readers, not to us
* Subject line: plain, no capitals, no clickbait
* Mention the press release is pasted below the email, not attached
* Offer one concrete thing: an interview, photos, or a visit

Notice the prompt asks you to name the reporter and their recent stories. That’s the relevance part, and irrelevance is the top reason journalists give for deleting a pitch. If you write outreach emails often, our guide to ChatGPT prompts for cold email outreach goes deeper on the first email and the follow-up.

Which AI is best for writing a press release?

Honestly, the prompt matters more than the tool. All the main assistants can follow the structure above. Some practical differences:

• ChatGPT is quick and handles the structure well, but tends to add enthusiasm. Your hype pass will catch it.
• Claude often writes a calmer, more natural tone, which helps with quotes.
• Gemini or Copilot are handy if your notes already live in Google Docs or Word.

If you’re choosing between them for writing in general, we compared ChatGPT vs Claude for writing side by side.

What about dedicated “AI press release generators”? Many are a form with fields (headline, quote, boilerplate) on top of the same kind of model. They’re fine if you like filling in boxes, but the fact sheet and the two passes on this page do the same job in the chat tool you already use.

Where to send it, and one SEO trap

• Your own website. Put the release on a news page on your site. It’s the version you control, and you can link to it from your pitch.
• Directly to the right reporters. Five well-chosen local or trade reporters beat a list of 500 random ones.
• A wire service, if it fits. Useful for companies that need broad distribution, but it costs money and doesn’t replace a personal pitch.

The trap: some people stuff press releases with keyword links to push their Google rankings. Google’s spam policies list links with optimized anchor text in press releases distributed on other sites as an example of link spam. Keep links in a distributed release plain and few, like your company name and homepage. Write the release for reporters, not for search engines.

What not to paste into an AI chat

Press releases often deal with news that isn’t public yet: an acquisition, a funding round, a launch date. Before you paste anything confidential, check how your AI account handles your data. OpenAI explains the options, including turning off training on your chats, in its data controls FAQ, and business plans usually have stricter settings. If your company has an AI policy, follow it. When in doubt, use placeholders like [PARTNER] and [AMOUNT] in the chat and fill them in yourself afterwards.

Common mistakes

• No news. “We updated our website” is not a press release. Ask the AI: “Would a local reporter care about this? Be honest.” It’s a useful gut check.
• Burying the news. If the first paragraph is about your company history, the reporter has already moved on.
• Trusting the numbers. Every figure in the release must come from you. The fact pass exists for this.
• The same release to everyone. Keep one release, but change the pitch email for each reporter.
• Forgetting the contact. A reporter on deadline who can’t reach you will write a different story.

And when the release is out and a reporter replies, answer in your own voice. If you want help polishing a reply, these prompts to make an email sound more professional keep it friendly without the stiff tone.

FAQ

Can AI write a press release for me?

It can write a solid draft in a few minutes, and it’s good at the standard format. It can’t know your news, your numbers or why it matters to a specific reader. Give it a fact sheet, and check every fact before you send anything.

Is there a free AI press release generator?

You don’t need a separate tool. The free versions of ChatGPT, Claude and Gemini can all follow the drafting prompt on this page. Paid generators mostly add templates and distribution, and distribution is the part worth comparing if you need it.

Will journalists know it was written with AI?

They notice the signs: hype words, vague claims, quotes nobody would say out loud, and factual errors. A release built from your own facts, your own quote and a hype pass reads like a careful human wrote it, because a careful human checked every line.

How long should a press release be?

Aim for one page. The news belongs in the first paragraph, so a reporter who reads only that still gets the story. Everything after it is supporting detail.

Should I attach the press release or paste it?

Paste it into the email below your short pitch, and link to the version on your website. Many people prefer not to open attachments from senders they don’t know.

Write your first one this week

Pick a piece of real news, even a small one. Write the fact sheet, paste the drafting prompt, run the hype pass and the fact pass, and send it to three reporters who actually cover your area. That’s an hour of work, and most of it is thinking, which is exactly the part that should stay yours.

If your news is a client win, the same facts can also become a story for your own site. Here is how to write a case study with AI.

And if you share news like this with your list every month, here is how to use AI to write a newsletter people actually read.

Want more workflows like this, one practical win at a time? Start on our home page, or join Launchpad right here:

It’s 8:40. Your inbox already has 31 unread emails, there’s a call at 10, a report due by end of day, and a list in your head that keeps getting longer while you stare at it. You don’t need another productivity app. You need someone to look at the mess and say “do this first”.

Here’s the short answer. To use AI to plan your day, dump every task into ChatGPT, Claude, Gemini or Copilot in three minutes, give it your fixed meetings and your real working hours, and ask it to build a time-blocked plan with only three must-do items, a time estimate on every block and buffer between them. Then you push back once: cut what doesn’t fit and move the rest to tomorrow. The AI does the sorting. You make the calls.

Want one practical AI workflow like this every week, free?

Why your to-do list isn’t a plan (and what AI fixes)

A to-do list tells you what exists. A plan tells you what happens at 9:30. The gap between those two is where most days go wrong.

Two pieces of research explain why. First, we are bad at guessing how long our own work takes. In the classic “planning fallacy” studies by Buehler, Griffin and Ross (1994), fewer than half of the participants finished their tasks in the time they predicted. The optimism disappeared when people were asked to connect the estimate to similar past tasks. That is exactly the question an AI can ask you every morning.

Second, open tasks keep pulling at your attention. Masicampo and Baumeister (2011) found that unfinished goals caused intrusive thoughts during an unrelated task, and that making a specific plan for those goals removed that effect. A written plan with a time slot for the report is not just tidier. It lets you stop thinking about the report while you’re on the 10 o’clock call.

So the job for AI is clear: turn the pile into a sequence, put honest times on it, and make the trade-offs visible before 9 instead of at 4.

Step 1: Do a 3-minute brain dump

Open a new chat and type everything that’s on your mind for today. Don’t sort, don’t format. Half sentences are fine. Include the small stuff (“reply to Sanne about the invoice”) and the big stuff (“Q4 report, still need numbers from finance”).

Add three facts the AI can’t guess:

• Your fixed points: meetings, calls, school pickup, anything with a time on it.
• Your real hours: not 9 to 5 on paper, but when you actually start and stop.
• Your energy pattern: are you sharp in the morning and useless after lunch, or the other way round?

Speaking it out loud works too. Most AI apps on your phone let you dictate, and talking for two minutes on the way to your desk is often faster than typing.

Step 2: Use the planning prompt

Paste this under your brain dump. It’s built to stop the two classic problems: a plan that’s too full, and estimates that are too optimistic.

Act as my no-nonsense planning assistant. Above is everything on my mind for today.

My working hours today: [08:30 to 17:30]
Fixed appointments: [10:00 to 10:45 client call, 14:00 to 14:30 team stand-up]
My best focus time: [mornings]

Build a time-blocked plan for today:
* Pick a maximum of 3 must-do items. Tell me why you chose them.
* Put my hardest task in my best focus time.
* Give every block a time estimate, and add 25% to anything I have never done before.
* Leave a 10 to 15 minute buffer after every meeting.
* Batch small tasks (emails, quick replies, admin) into one or two blocks.
* Keep at least 60 minutes unplanned for surprises.
* Anything that doesn't fit goes into a "Tomorrow or later" list. Don't squeeze it in.

Before you plan, ask me up to 3 short questions if something is unclear (deadlines, who is waiting on what).

The last line matters. A good assistant asks “is the report due to your boss or to the client?” before it guesses. If the AI skips the questions and plans straight away, that’s fine too. Just read the plan with that in mind.

Step 3: Push back once (the 2-minute reality check)

The first plan always looks good. That’s the problem. Before you accept it, ask the question from the planning fallacy research:

Here is how long similar tasks took me last time:
* [the monthly report took about 3 hours, not 2]
* [inbox clean-up usually takes 45 minutes]

Redo the time estimates with this in mind. If the day no longer fits, tell me which item to move and what the cost is of moving it.

This is where AI earns its place. It has no ego about the plan, so it will tell you plainly that four big items don’t fit in a day with three meetings. You decide what moves. Sometimes the honest answer is a quick message to someone: “I’ll have this to you tomorrow at 11.” The AI can draft that message too.

An example: a messy Tuesday, before and after

The brain dump (as typed):

q4 report needs finance numbers, call client 10am, prep slides for thursday, reply to 3 supplier mails, expense claims, check new hire contract, stand-up 2pm, gym??, call mum back

The plan the AI returned (shortened):

Must-do today: 1) Q4 report draft  2) New hire contract check  3) Client call

08:30 to 08:45  Email finance for the Q4 numbers (unblocks the report)
08:45 to 09:45  Q4 report: write structure and text, leave number gaps
09:45 to 10:00  Buffer + prep notes for the client call
10:00 to 10:45  Client call
10:45 to 11:00  Buffer: write call follow-ups
11:00 to 11:45  New hire contract check
11:45 to 12:15  Supplier emails (3) + expense claims
12:15 to 13:00  Lunch
13:00 to 14:00  Open slot for surprises / finance numbers into report
14:00 to 14:30  Stand-up
14:30 to 15:45  Q4 report: finish and send
15:45 to 17:30  Open (gym at 17:30 if the report is sent)

Tomorrow or later: Thursday slides (start Wednesday morning), call mum back during lunch or this evening

Look at what changed. The first task is a two-minute email that unblocks the biggest job. The slides moved to tomorrow with a reason. The vague “gym??” became a reward tied to finishing the report. Nothing here is clever. It’s just sorted, which is the part that’s hard to do when you’re the one drowning.

Let AI see your calendar (so you don’t type it)

Typing your meetings every morning gets old fast. The big assistants can read your calendar directly once you connect it:

• Claude: the Google Workspace connectors let Claude look at your Google Calendar, including events and availability, when you ask about your schedule. On Team and Enterprise plans an admin has to switch it on first. If you want the full setup, our guide on how to use Claude for work walks through connecting email, calendar and files.
• Gemini: Google’s help page explains how to create and manage calendar events with Gemini. Add @Google Calendar to your prompt to point it at your calendar. Keep Activity has to be on for the connection to work.
• Copilot in Outlook: Microsoft’s chat-assisted scheduling lets you schedule meetings and block time straight from the Copilot chat in Outlook.

With a connected calendar, your prompt shrinks to: “Look at my calendar for today, here’s my brain dump, build the plan using the rules from yesterday.” One tip: let the AI suggest focus blocks, but put them in your calendar yourself the first few weeks. You’ll learn fast which estimates you trust.

Make it a morning habit with a scheduled task

The best plan is the one you actually make every day. ChatGPT can remind you. Its scheduled tasks run a prompt at a time you choose, one-time or recurring. On the free plan, recurring tasks can run at most once a day, which is exactly what you need here.

Ask it something like:

Every weekday at 08:15, ask me for my brain dump for today. When I answer, build my plan with these rules: max 3 must-dos, hardest task in the morning, 25% extra on new tasks, buffer after meetings, 60 minutes unplanned, the rest to "Tomorrow or later".

Now the habit runs itself. You get a nudge, you talk for two minutes, you get a plan.

When the day breaks at 11: replan in 60 seconds

Every plan meets reality. A client calls, a colleague is sick, the finance numbers don’t arrive. The old way is to abandon the plan and run on panic. The better way is to go back to the same chat:

It's 11:20. I lost 90 minutes to an urgent client issue. Done so far: [finance email, client call]. Replan the rest of my day with the same rules. Tell me what drops off and draft a short message for anyone who is waiting on something I'm moving.

Because the chat already knows your morning, the new plan takes a few seconds. This is the part most planner apps don’t do well, and it’s where talking to an AI feels like having a calm colleague next to you.

End the day with a 3-line review

At the end of the day, give the AI three lines: what got done, what didn’t, and how long the big task really took. Ask it to carry the unfinished items into tomorrow’s list. After a week, you have exactly what the planning fallacy research says helps: your own track record. Your estimates get better because they’re based on what happened, not on what you hoped.

If you track your work for your manager or team, the same notes feed nicely into a weekly update. We showed that in using Gemini for automated status updates.

What not to paste into an AI planner

Your day plan often contains names, client details and sometimes health or HR matters. A few simple habits:

• Use first names or roles (“new hire”, “client A”) instead of full names and details you’d never put in an email to a stranger.
• If you use ChatGPT for work, check its data controls to decide whether your chats may be used to improve models.
• If your company provides Copilot or Gemini through your work account, use that one for work planning. It’s what your IT team has approved.

Common mistakes (and quick fixes)

• Letting it plan 10 must-dos. Then nothing is a priority. Keep the hard limit of three.
• No buffer. A plan with back-to-back blocks breaks at the first overrun. The buffer rule is not optional.
• Planning tasks that are really projects. “Write the strategy” is not a 2-hour block. If something is bigger than a day, plan it first. Our guide to creating a project plan with AI breaks it into steps you can drop into a day.
• Accepting the first draft. The pushback step is where the plan becomes realistic. Two minutes, every time.
• Using it as a guilt list. If items keep moving to “tomorrow” for a week, ask the AI: “Which of these should I delegate, drop or say no to?” That’s a real answer too.

FAQ

Can AI really plan my day?

It can do the sorting, the time estimates and the replanning well, especially when you give it your fixed meetings and real past timings. It can’t know that your boss will be in a bad mood or that the report matters more than it looks. That’s why you stay the one who decides. Think of it as a fast first draft of your day.

What’s the best AI to plan my day?

The one that already sees your work. If your calendar is in Outlook and your company has Copilot, start there. If you live in Google Calendar, Gemini or Claude with the calendar connected saves typing. If you just want a quick plan from a brain dump, any of them, including ChatGPT, will do the job with the prompt above.

Is there a free AI daily planner?

You don’t need a separate app to start. The free versions of ChatGPT, Claude and Gemini can all turn a brain dump into a time-blocked plan with the prompts on this page. Calendar connections and higher limits can depend on your plan, so check what your account includes.

How long does this take each morning?

Plan on about five minutes: three for the brain dump, one for the AI, and two to push back and adjust. Less once you have a scheduled task and a connected calendar.

Start tomorrow morning

Pick one day this week. Do the brain dump, paste the planning prompt, push back once, and see how 4 p.m. feels compared to a normal day. If it helps, make it a scheduled task and let the habit run itself.

Want more workflows like this, one practical win at a time? Start on our home page, or join Launchpad right here:

You have the idea. Maybe you have the first clients. What you don’t have is the document a bank, a partner or your own sceptical brain keeps asking for. You open a blank page, type “Executive Summary”, and stare at it for twenty minutes.

Here’s the short answer. To use AI to write a business plan, don’t ask it to “write a business plan for my coffee shop”. Give it a short brief with the facts only you know (who pays you, what for, what it costs you, what you need), let it interview you about the gaps, then have it draft one section at a time in a format you picked: a one-page lean plan or a full traditional plan. You do the numbers yourself, and you finish by asking the AI to attack the plan like a lender would. ChatGPT, Claude or Gemini can get you to a solid first draft in an afternoon. The thinking stays yours. The typing gets a lot lighter.

Want one practical AI workflow like this every week, free?

What AI is good at in a business plan (and where it will fool you)

AI is very good at three jobs here: turning your messy notes into clear sections, asking the questions you forgot, and spotting where your story doesn’t hang together. That is most of the pain of writing a plan.

It is bad at one thing that matters a lot: facts about your market. OpenAI says it plainly in its own help article “Does ChatGPT tell the truth?”: the model can produce incorrect facts and even fabricated studies or citations, and it can sound confident while doing it. Their advice is to use it as a first draft, not a final source, and to check data and references yourself.

So a market size figure that shows up in your draft without a link you clicked yourself doesn’t go in the plan. Treat every number the AI offers as a question (“where would I check this?”), never as an answer.

There’s a second trap. Harvard professor William Sahlman wrote in Harvard Business Review that detailed financial projections for a new company are an act of imagination, and that most business plans spend far too much ink on the numbers. AI makes that worse if you let it, because it can produce five years of tidy spreadsheets in seconds. Tidy is not the same as true. Spend your effort on who the customer is, why they buy and what could go wrong.

Step 1: Pick your format before you prompt

The U.S. Small Business Administration describes two common formats in its guide “Write your business plan”:

• Lean startup plan. Usually one page, built from a handful of blocks: key partnerships, key activities, key resources, value proposition, customer relationships, customer segments, channels, cost structure and revenue streams. The SBA says it can take as little as an hour.
• Traditional plan. Detailed and often dozens of pages: executive summary, company description, market analysis, organization and management, service or product line, marketing and sales, funding request and financial projections. The SBA notes lenders and investors commonly ask for this one.

Rule of thumb: if you’re asking a bank or investor for money, write the traditional plan. If the plan is for you and a partner to get clear on the business, start lean. You can always grow the lean version into the full one later, and AI is great at that expansion step.

Telling the AI which format you want is the single biggest upgrade to your prompt. Without it you get a generic mix of both.

Step 2: Write a 10-minute founder brief

This is the part nobody can do for you, and it is why AI drafts usually sound empty. The model knows what a business plan looks like. It doesn’t know your business. Open a note and answer these in plain sentences. Bullet fragments are fine.

The last line matters more than it looks. A plan for a bank loan officer and a plan for a co-founder are different documents, and the AI can only write for the reader you name.

Step 3: Let the AI interview you first

Paste your brief and ask for questions, not a draft. This is where AI saves you the most time, because it is good at noticing what is missing.

Answer honestly, including “I don’t know yet”. Those “don’t know” answers become your to-do list. Some of them, like how big your local market is or what competitors charge, need real research. Our guide on how to use AI for market research shows how to do that with sources you can check, and the SBA’s guide lists free public data such as the Census Business Builder.

Step 4: Draft one section at a time

Asking for the whole plan in one go gives you a long, smooth, shallow document. Section by section gives you something you can actually defend. Start with the middle (market, customers, offer) and leave the executive summary for last, because it summarizes everything else.

Then repeat for each section you need. The [NEEDS DATA] tags are the trick. They stop the model from filling holes with plausible fiction, and they show you exactly what to look up.

A quick tool note. ChatGPT, Claude and Gemini all handle this well. Claude is pleasant for long documents if you paste the whole draft back in later, and it is what we use in how to use Claude for work. Pick the one you already pay for. The brief matters far more than the brand.

Step 5: Do the numbers yourself, with AI as a checker

This is where most AI business plans go wrong. Don’t ask the model to “create financial projections”. Give it your numbers and ask it to lay them out and check the math.

The SBA’s guide includes a simple break-even formula every plan should show: fixed costs divided by (price per unit minus variable cost per unit) gives your break-even point in units. Here is a made-up example to show the idea. Say your fixed costs are 3,000 a month, you sell a service at 500, and each sale costs you 100 to deliver. 3,000 divided by 400 is 7.5, so you need 8 sales a month before you make a cent.

Then check the math in a spreadsheet. Chatbots still slip on arithmetic now and then, and a lender will check. If you’d rather work from a sheet you already have, our guide to analyzing a spreadsheet with ChatGPT walks through uploading it and asking good questions.

Honest projections with your reasons written next to them beat confident five-year curves. That’s Sahlman’s point too: readers care about the people, the opportunity and the risks you see, not about how many cells you filled.

Step 6: Ask the AI to attack your plan

Once the draft is done, switch roles. This is the step that turns an AI draft into a plan you trust.

You will not like every answer. Good. It is much cheaper to hear it from a chatbot at your kitchen table than from a loan officer across the desk.

Want a second angle on the same plan? Run a quick SWOT analysis with AI on your business before you send it out. It shows where your strengths line up with real opportunities, and which threats your plan still has no answer for.

A worked example: a freelance bookkeeper’s lean plan

To make this concrete, here is an illustrative example (not a real client). Sam is a freelance bookkeeper who wants to stop taking every job and focus on small hair and beauty salons.

Her prompt without a brief: “Write a business plan for a bookkeeping business.” The result: a generic page about “offering high-quality financial services to businesses of all sizes”, a competitor section with no names, and growth figures nobody can check.

Her prompt with a brief: She told the AI she has six salon clients, charges a fixed monthly fee, gets most new clients through referrals from one supplier, and has room for about ten more clients on her own. She asked for a lean plan for herself and a possible part-time hire.

The draft came back with a clear value proposition (bookkeeping that understands booth rental and tips), a customer segment narrow enough to market to, and three [NEEDS DATA] tags: how many salons are within her area, what other bookkeepers charge them, and how many referrals the supplier sent last year. The attack step then pointed out that the whole plan leans on one referral source. That became the first risk in her plan, with a fix: test a second channel before hiring.

Same tools, same afternoon. The difference was the brief.

Free AI business plan generators vs a normal chatbot

If you search for an AI business plan generator, you’ll find many tools, free and paid. Some are useful, especially ones that give you a good template and a finance sheet that adds up. Under the hood, most of them do what you just did: ask you questions and fill sections.

So the honest test for any tool is simple. Does it ask you for your real facts before writing? Does it let you edit every section? Does it show you where its numbers come from? If yes, use whatever you like. If it writes ten pages from one sentence about your idea, you are back to a generic plan with a nicer cover.

A general chatbot plus the prompts on this page gets you the same result without a new subscription. If you’ve built a plan before, you’ll notice the work looks a lot like using AI to create a project plan: brief first, structure second, your judgement last.

What not to paste into a chatbot

A business plan holds sensitive things: client names, bank details, your salary, a partner’s personal finances. Before you paste, check your settings. OpenAI’s data controls page explains that on personal ChatGPT plans, data sharing for model training is on by default and can be turned off under Settings, Data controls, “Improve the model for everyone”. It also says business and enterprise workspaces aren’t used for training by default.

Simple habit: replace client names with “Client A”, round personal figures, and leave out account numbers completely. The AI doesn’t need them to write a good plan.

Applying for funding instead of a loan or investor? The same facts-first method works for grants too. Here is how to use AI to write a grant proposal section by section, including what funders say about AI.

Common mistakes

• No brief. One sentence in, ten generic pages out.
• Letting AI invent the market. Every number needs a source you opened yourself.
• Writing the executive summary first. Write it last, from the finished sections.
• Five-year projections with no reasons. Twelve honest months with your assumptions written down are more convincing.
• Skipping the attack step. The weak points are still there. You just find out later.
• Sending the AI’s wording as is. Read it out loud. If it doesn’t sound like you, a reader who meets you will notice.

FAQ

Can AI write a business plan for me?

It can write the draft, and it can save you hours of typing and structuring. It can’t know your customers, your costs or your goals unless you tell it, and it can get facts wrong. Think of it as a fast co-writer who needs a good brief and a careful editor.

What is the best AI to use to write a business plan?

ChatGPT, Claude and Gemini all do this well. Use the one you already know. A clear brief, a chosen format and the section-by-section method matter far more than which model you pick.

Can I use an AI-written business plan for a bank loan?

Yes, as long as everything in it is true and you can explain every number. The lender reads the plan, not the tool you used. Check the figures yourself, add real sources, and make sure you could answer the questions from Step 6 in a meeting.

How long does it take?

The SBA says a lean plan can take as little as an hour. With AI doing the drafting, a lean plan is realistic in one sitting. A traditional plan usually takes a few sessions, mostly because of the research and the numbers, which is time well spent.

What should a business plan include?

For a traditional plan, the SBA lists executive summary, company description, market analysis, organization and management, service or product line, marketing and sales, funding request and financial projections. Use only the sections your reader needs.

Stuck choosing between two business ideas, markets or pricing models before you write the plan? Make a decision matrix with AI first, so the plan starts from a choice you can defend.

Your next step

Open a note now and fill in the founder brief from Step 2. Ten minutes. Then paste it into the chatbot you already use with the interview prompt from Step 3. By tonight you’ll have a list of honest questions about your business, and that list is worth more than any polished template.

If you want more workflows like this, built for people who use a computer all day and want AI to take the boring parts, start on our home page or grab the free Launchpad right here.

Writing client proposals as well as plans? See AI proposal writing software for how to pick the right stack for your deals.

Still testing an idea before you write the plan? Here is how to use ChatGPT to make money and get your first paying customer.

You need feedback by Friday. Maybe it’s the team after a messy tool rollout, maybe it’s clients after a project. You open a blank form, type “Survey” as the title, and stare at it. Writing ten good questions feels like it should take ten minutes. It never does.

Here’s the short answer. To use AI to create a survey, don’t ask for “a customer feedback survey”. Tell it what decision the answers will feed, who will fill it in, and how many minutes they will give you. Ask for one idea per question, neutral wording and answer options that don’t overlap. Then let the AI check its own draft for leading and double-barreled questions, build it in Google Forms or Microsoft Forms, and test it on two people before you send it. ChatGPT, Claude, Gemini and Copilot can all do the drafting in about a minute. The thinking about what you actually need to know stays with you.

Want one practical AI workflow like this every week, free?

Why most AI-made surveys get weak answers

Ask any chatbot for “an employee satisfaction survey” and you will usually get a long list of agree/disagree statements that could belong to any company on earth. It looks finished. The answers you get back are hard to act on.

Survey researchers have known the reasons for decades. The Pew Research Center’s guide to writing survey questions lists the classic traps:

• Double-barreled questions. One question that asks about two things, like “How happy are you with our speed and quality?” Nobody knows which half the answer is about.
• Agree/disagree statements. Pew notes that some people tend to agree with whatever statement you put in front of them (acquiescence bias). Offering a choice between two alternatives gives cleaner answers.
• Answer options that overlap or leave people out. Closed questions should cover all reasonable answers, and the options shouldn’t overlap.
• Jargon and double negatives. Simple, concrete words get understood the same way by everyone.
• Question order. Earlier questions can colour how people answer later ones.

A chatbot knows all of this. It just doesn’t apply it unless you ask. So the trick is not a better tool. It is a better brief, and a second pass where the AI checks itself.

Step 1: Write a 60-second brief

Before you open any AI tool, answer four questions in plain words. This is the part only you can do.

1. What decision will these answers feed? “Decide whether we keep the new shared inbox tool or go back to email” is a decision. “Get feedback” is not.
2. Who fills it in? 25 support agents, 40 clients, your newsletter readers. Their context changes the words you use.
3. How much time will they give you? Be honest. A busy client gives you three minutes, not fifteen.
4. What will you do with each answer? If you can’t say what you’d do differently based on a question, that question goes.

That last one is the filter that keeps a survey short. Most bloated surveys are full of “nice to know” questions nobody ever looks at again.

Step 2: Generate the survey with one prompt

Paste your brief into ChatGPT, Claude or Gemini with this prompt. It works the same in all three.

The last line matters more than it looks. When the AI has to say which part of the decision each question serves, the filler questions show themselves. If it writes “general sentiment” next to a question, cut it.

Step 3: Let the AI check its own draft

First drafts still slip. Open a new message in the same chat and run a review pass:

Asking for “the one question I could drop” is a small habit that pays off. It forces a ranking, and you’ll often agree with the cut.

Step 4: Build it in Google Forms or Microsoft Forms

You now have a clean list of questions. Getting them into a real form is the boring part, and both big form tools have AI built in for it.

Google Forms with Gemini

Open a new form and use Help me create a form. Paste your final survey as the prompt and Gemini builds a draft form you can edit before you click Create form. According to Google’s help page for this feature, it needs an eligible Google Workspace or Google AI plan, works on desktop, and can’t yet build forms with multiple sections or edit a form you already have (it replaces the content). So for a longer survey with sections, generate the questions here and add the sections by hand.

Microsoft Forms with Copilot

In Microsoft Forms, start a new form and describe what you want in the Copilot box, or paste your finished questions. Microsoft’s Copilot in Forms guide says Copilot drafts a title, description, questions and answer options, can suggest fixes for leading or double-barreled questions, and needs a Microsoft 365 account and a Copilot license. You pick Keep to move the draft onto the form.

No AI plan in your form tool?

Then the free version of any chatbot plus a normal form builder is plenty. Copy the questions from Step 3 and paste them into Google Forms, Microsoft Forms, Typeform or whatever your company uses. It takes about five minutes for a ten-question survey, and you get to look at every question once more on the way in.

Step 5: Test it on two people before you send it

This is the step almost everyone skips. Pew calls pretesting “an essential step” in designing a questionnaire, and it doesn’t need a research budget. Send the form to two people who look like your real audience and ask them to fill it in while thinking out loud, or to tell you afterwards:

• Which question made you pause?
• Was there a question where none of the answers fit you?
• How long did it take?

Paste their comments back into the chat and ask the AI to fix exactly those spots. Ten minutes of testing saves you from fifty answers to a question everyone read differently.

A before and after example

Say you rolled out a shared inbox tool to a 25-person support team six weeks ago, and you need to decide whether to keep it. Here is what a lazy prompt tends to produce, next to what the brief-based version gives you.

Before (generic prompt):

Question 1 asks about two things in an agree/disagree format. Question 2 is double-barreled. Question 3 leads. Question 4 has overlapping options (is 10 in the first or second group?) and no option for more than 30.

After (brief + review pass):

Five questions, about three minutes, and every answer points at the keep-or-drop decision. That is the whole difference: the AI didn’t get smarter, the brief did.

How long should your survey be?

Shorter than you think. SurveyMonkey analysed roughly 100,000 surveys and found that people spend about 5 minutes on a 10-question survey, and that they spend less time per question the longer a survey gets. In their write-up on survey length they also report that abandon rates rose for surveys taking more than 7 to 8 minutes, and that people tolerated longer surveys for work or school than for customer surveys.

A practical rule from that: for clients or customers, aim for 5 to 8 questions. For your own team, 10 to 12 is usually fine if every question earns its place. Put the time in the intro (“takes about 3 minutes”) and make sure it is true.

After the answers come in: let AI do the first read

The open text answers are where the useful surprises hide, and also where most people give up reading. AI helps here too.

• In Google Forms, Gemini can summarize answers to short-answer and paragraph questions in the Responses tab once a question has 3 to 200 responses, on eligible plans (Google’s help page on summarizing responses).
• In Microsoft Forms, Copilot can summarize results into key findings from the responses view, per the Microsoft guide linked above.
• Anywhere else, export the responses as a CSV and give it to ChatGPT or Claude. Our guide to analyzing a spreadsheet with ChatGPT walks through how to do that and check the numbers.

One prompt that works well for open answers: “Group these answers into the 5 most common themes. For each theme, give the count and two quotes in the respondent’s exact words. Don’t add anything that isn’t in the answers.” Then read the quotes yourself. A summary is a starting point, not the finding.

For the full process, from cleaning the export to a one-page summary you can share, see our guide on how to use AI to analyze survey data.

What not to paste into a chatbot

Drafting questions is safe: there’s nothing private in “what do we ask our clients”. The answers are a different story. Responses can contain names, email addresses, and honest opinions people gave you in trust. Before you paste them anywhere, remove names and contact details, check what your company allows, and use the business version of the tool your workplace has approved. If you promised the survey was anonymous, keep it that way all the way through.

Common mistakes when you create a survey with AI

• Skipping the brief. Without the decision and the audience, you get a generic list of questions.
• Keeping every question the AI suggests. More questions mean less careful answers. Cut hard.
• Only agree/disagree scales. Mix in balanced choices and one or two open questions.
• No “Not sure” or “Other” option. People forced into a wrong box give you wrong data.
• Not testing. Two testers catch the confusing question before fifty people do.
• Trusting the AI summary without reading quotes. Always check the themes against real answers.

FAQ

Can ChatGPT create survey questions?

Yes, and it does it well when you give it the decision, the audience and the time limit. The prompts in Steps 2 and 3 work in ChatGPT, Claude and Gemini without changes. If you’re new to it, our ChatGPT tutorial for beginners gets you set up.

Is there a free AI survey generator?

The free versions of ChatGPT, Claude and Gemini can draft a full survey from a good prompt, and you can paste the result into the free version of Google Forms. The AI features built into Google Forms and Microsoft Forms need a paid plan or license, according to their help pages. Dedicated survey generators mostly wrap the same idea in a template. The quality comes from your brief.

How many questions should a survey have?

As few as your decision needs. For customers, 5 to 8 questions is a good target. SurveyMonkey’s data shows people take about 5 minutes for 10 questions and start dropping off past 7 to 8 minutes.

Can AI analyze survey results too?

Yes. Gemini in Google Forms and Copilot in Microsoft Forms can summarize responses, and any chatbot can group open answers into themes from a CSV export. Check counts and quotes yourself before you share conclusions.

Should I use Gemini or ChatGPT for this?

If your team already lives in Google Workspace, Gemini inside Google Forms saves you the copy and paste. If not, use whichever chatbot you already know. Our Gemini tutorial for beginners shows the basics if you want to try it.

Need right-and-wrong answers instead of opinions? A short scored quiz fits better than a survey when you are checking knowledge. Here is how to make a quiz with AI, with copy-paste prompts for ChatGPT or Claude.

Your next step

Think of the one decision you’ve been putting off because you “need input first”. Write the four-line brief from Step 1, run it through the two prompts, and send the form to two testers today. By tomorrow you can have it out to the people whose answers you need. For more small workflows like this, the kind that take an annoying task off your plate, start with the free Launchpad on our home page.

The candidate is booked for Thursday at two. You have their CV open, a job description you wrote last month, and a blank page where your interview questions should be. So you reach for the same five you always ask: tell me about yourself, your biggest weakness, where you see yourself in five years.

Here’s the short answer. To use AI to create interview questions, don’t ask ChatGPT or Claude for “good interview questions for a project manager”. Paste in the job description, name the three to five skills that really decide success in the role, and ask for one behavioral question and one situational question per skill, each with follow-up probes and a short note on what a strong answer sounds like. Then ask for a simple 1 to 5 scoring guide and a check for anything you shouldn’t ask. That takes about ten minutes. You end up with a question set you can use for every candidate, so you compare people on the same things instead of on gut feeling.

Want one practical AI workflow like this every week, free?

Why the usual interview questions tell you so little

Most interviews are a friendly chat. You follow whatever sounds interesting, you like some people more than others, and afterwards you go with the feeling. It feels thorough. It isn’t.

Iris Bohnet, a behavioral economist at Harvard Kennedy School, put it bluntly in Harvard Business Review: unstructured interviews get the highest ratings from hiring managers for how useful they feel, yet dozens of studies found them among the worst predictors of how someone will actually do the job (HBR, How to Take the Bias Out of Interviews).

The fix is not more clever questions. It’s structure. The US Office of Personnel Management, the federal government’s HR agency, sums up the research: interviews that ask every applicant the same predefined questions and follow-ups, and score answers against set benchmarks, show higher validity, better agreement between interviewers and less adverse impact than loose conversations. Questions built on the specific skills the job needs do best (OPM, Structured Interviews).

That is exactly the boring, careful work AI is good at. It won’t decide who to hire. It will do the drafting that most of us skip because it takes an hour.

Step 1: Start from the job, not from a list of “top 50 questions”

Generic question lists are where most AI interview question generators start, and that’s why their output feels generic. Your input decides the quality.

Before you open ChatGPT, write down three things. It takes five minutes:

• The job description. If you don’t have a good one yet, our guide on how to use AI to write a job description gets you there first.
• Three to five must-have skills. Not twelve. The few things that, if missing, mean this hire fails. For a customer support team lead that might be calming angry customers, coaching a struggling agent, and prioritising a queue on a bad day.
• What good looks like in month three. One or two sentences per skill. “Handles escalations without passing them up” is useful. “Great communicator” is not.

That last point is the one people skip, and it’s the one that makes the AI’s scoring guide sharp later.

Step 2: The prompt that writes your interview questions

There are two proven question types, and OPM describes both. Behavioral questions ask what someone did in a real past situation (“Tell me about a time you…”). Situational questions ask what they would do in a realistic scenario from the job. Both work; behavioral ones hold up especially well for complex professional and managerial roles (OPM). Ask the AI for one of each per skill.

Copy this into ChatGPT, Claude or Gemini and fill in the brackets:

The “Missing info” line matters more than it looks. Without it, the AI fills gaps with invented details about your team, and you end up asking a candidate about a tool you don’t even use.

Step 3: Ask for a scoring guide before you meet anyone

Questions alone are half the structure. The other half is deciding, in advance, what a 1, a 3 and a 5 sound like. Otherwise the candidate who was charming at the start gets a 5 on everything.

If several people interview, OPM’s description of how structured panels work is a good model: each interviewer scores on their own first, then the panel talks through the big differences. Doing it in that order stops the most senior voice in the room from setting everyone’s score.

Step 4: Check the questions for bias and anything you shouldn’t ask

AI drafts can slip in questions that sound harmless and aren’t. “Where did you grow up?” or “Do you have kids?” have no place in an interview. In the US, the EEOC says pre-employment questions should stick to what’s needed to judge if someone is qualified, and that questions which reveal protected characteristics, such as age, religion, disability or family status, should generally be avoided (EEOC, Prohibited Employment Policies/Practices). Most other countries have similar rules, so check your own.

Run one more pass:

Treat this as a second pair of eyes, not legal advice. If you’re unsure about a rule where you hire, ask your HR person or an employment lawyer.

A before and after example

Say you’re hiring that customer support team lead. Here’s a question most of us would write on the spot:

Before: “How do you handle difficult customers?”

Every candidate answers that one the same way: “I stay calm, I listen, I find a solution.” You learn nothing.

Here’s the kind of question set the prompt above gives you for the skill “calming angry customers”, after one quick round of edits:

After (behavioral): “Tell me about the last time a customer was angry with you or your team. What had gone wrong, what did you say first, and how did it end?”

Probes: “What would you do differently now?” and “What did you tell your team afterwards?”

After (situational): “It’s Friday at 4pm. A customer emails the CEO directly, saying their order is three weeks late and they’re cancelling. The agent who owns the ticket is out sick. Walk me through your next hour.”

Strong answer signs: names a concrete first action, owns the problem without blaming the agent, mentions following up after the fix. Weak answer sign: stays general and never says what they’d actually write or say.

Same ten minutes of your time. A completely different conversation.

How to generate interview questions from a job description

Many people search for an AI interview questions generator based on a job description. You don’t need a special tool for this. The prompt in Step 2 already does it: the job description is the main input, and the “use details from the description” rule makes the situational questions specific to your role.

Two tips make it work better:

• Cut the fluff out of the description first. Company history and benefits don’t help the AI write questions. Paste the responsibilities and requirements only.
• Tell it which requirements matter most. A job description lists ten things. If you don’t rank them, the AI gives every line equal weight and your interview becomes a checklist.

Free versions of ChatGPT, Claude and Gemini all handle this well. If you’re new to these tools, our ChatGPT tutorial for beginners covers the basics in a few minutes, and how to use Claude for work shows the same idea in Claude.

Tailoring questions to one candidate’s CV (carefully)

A fair interview asks everyone the same core questions. You can still add two or three follow-ups about a specific CV, as long as the core set stays the same for all candidates. Ask the AI something like: “Here are my core questions and this candidate’s work history. Suggest three follow-up questions about gaps or claims I should explore. Don’t change the core questions.”

Before you paste a CV anywhere, remove the name, contact details, photo and date of birth. You only need the work history. Also check your settings. In ChatGPT’s personal plans, the “Improve the model for everyone” setting is on by default, which means your chats can be used for training unless you turn it off under Settings, Data controls. Temporary chats aren’t used for training, and business workspaces aren’t used for training by default (OpenAI Help, Data controls in ChatGPT). If your company has rules about candidate data, they win.

Common mistakes to avoid

• Asking for “the best interview questions”. You get the same list as everyone else. Always paste your role and your must-haves.
• Too many questions. In a 45 minute interview, eight to ten questions with probes is plenty. A candidate rushing through twenty gives you twenty shallow answers.
• Skipping the scoring guide. Without it, you’re back to gut feeling with nicer questions.
• Letting AI change the set between candidates. Generate once, edit once, then freeze it for this hiring round.
• Using the output without reading it. Read every question out loud once. If it sounds odd when you say it, rewrite it.
• Letting AI judge the answers. Your notes and your scores decide. AI helps you prepare, not decide who gets the job.

Questions people ask about this

Can I use ChatGPT to create interview questions for free?

Yes. The free versions of ChatGPT, Claude and Gemini can all write a full question set and scoring guide with the prompts above. Paid plans mostly help with longer documents and higher limits.

How many interview questions should I prepare?

Plan two questions per must-have skill, so six to ten for three to five skills, plus probes. For a 45 minute slot that leaves room for introductions and the candidate’s own questions.

Should I use behavioral or situational questions?

Both. Behavioral questions show what someone has actually done. Situational ones help with candidates who haven’t faced that exact situation yet, like a first-time team lead. If you want candidates to give fuller answers, many career services teach the STAR method (situation, task, action, result), and MIT’s career office has a clear guide on it (MIT CAPD, The STAR method). Your probes can gently steer someone through those four parts.

Can AI write the answers I should expect?

It can describe the signs of a strong answer, which is what the scoring guide needs. Don’t use it to write a “perfect answer” you compare word for word. Good candidates answer in their own words, from their own experience.

What about performance reviews and internal promotions?

The same structure works for internal interviews. For the review side of things, see how to use AI to write a performance review.

After the hire, a short new-starter survey tells you whether your interview process worked. Here is how to use AI to create a survey people actually finish.

Once you’ve made the hire, the same approach helps with their first months. See how to use AI for employee onboarding for a 30-60-90 day plan, a first-week checklist and a welcome email.

Your next interview, ten minutes from now

Pick the next role you’re hiring for. Write down the three skills that matter most and what good looks like in month three. Paste them into the Step 2 prompt, then run the scoring and bias checks. You’ll walk into Thursday’s interview with questions that actually tell candidates apart, and a sheet that helps you defend your choice afterwards.

The AI writes the drafts. You decide what the job really needs, and who fits it.

We share one practical workflow like this every week inside Launchpad, our free starting point for using AI at work. You can join from our home page or right here:

The meeting is tomorrow at ten. You booked it, six people accepted, and the invite still says nothing but the title. You know roughly what needs to happen. Writing it down in a way that keeps the hour on track is the part that keeps sliding.

Here’s the short answer. To use AI to create a meeting agenda, don’t ask for “an agenda for our project meeting”. Give it the goal of the meeting, who is coming, how long you have and the decisions you need, then ask it to turn each topic into a question the group has to answer, with a time box and an owner next to every item. ChatGPT, Claude, Gemini or Copilot can do this in under a minute. You spend two more minutes cutting what doesn’t belong. The AI writes the structure. You decide what the meeting is for.

Want one practical AI workflow like this every week, free?

Why most agendas don’t help (and what AI should fix)

An agenda on its own doesn’t make a meeting better. Meeting researcher Steven Rogelberg writes in Harvard Business Review that research has found little to no relationship between having an agenda and how attendees rate the meeting. What matters is whether the items are relevant and how the discussion is run. On his own site he adds that an estimated half of agendas are simply recycled from the last meeting.

That’s exactly the trap with AI. Ask a chatbot for “a team meeting agenda” and you get the generic one: welcome, updates, discussion, any other business, next steps. It looks tidy and changes nothing.

So the job you give the AI is different. You want it to do three things a tired organizer skips:

• Turn topics into questions. Rogelberg’s advice is to frame items as questions to be answered, not topics to discuss. “Budget” becomes “Where do we cut 5,000 from Q1 without delaying the launch?”
• Put the important item first. In the same essay he notes that research found early agenda items get a disproportionate share of time and attention, whatever their importance.
• Say what each item is for. Roger Schwarz suggests in Harvard Business Review that every item states whether it’s for sharing information, gathering input or making a decision, with a realistic time estimate and a clear note on how people should prepare.

A model is good at all three. It’s fast at rephrasing, it doesn’t get bored ordering things, and it will happily add time boxes that add up to your slot.

How to use AI to create a meeting agenda in 4 steps

Step 1: Write a 60-second brief

Before you open any AI tool, jot down five lines. This is the part only you can do:

• Goal: what must be true when the meeting ends? (“We’ve picked a supplier.”)
• People: who is coming and what they bring. (“Sara, finance. Tom, ops. Two people from the supplier.”)
• Time: how long, and whether it’s in person or a video call.
• Open questions: the two or three things nobody has answered yet.
• Input you have: an email thread, last meeting’s notes, a short report.

If you can’t fill in the goal line, stop there. Rogelberg’s point is blunt: if you can’t come up with questions to answer, you may not need the meeting at all. Sometimes the best agenda is a short email instead.

Step 2: Paste the brief into this prompt

Open ChatGPT, Claude or Gemini and use this. Replace the brackets with your brief.

The “Missing info” line matters. Without it, a model will often fill gaps with plausible guesses, like an owner who isn’t coming or a deadline you never set. With it, you get a list of what to check instead.

Step 3: Cut and sharpen

Read the draft like an attendee who has three other meetings that day. Then ask the AI for one round of changes:

This is usually where a seven-item draft drops to four, and the meeting gets shorter.

Step 4: Send it with the invite

Put the agenda in the calendar invite, not in a separate document people won’t open. Send it at least a day ahead if anyone needs to prepare. Add the “send before” items as a short note above the agenda so people read them first.

A before and after example

Here’s an example from a small agency planning a client website relaunch. The organizer’s first version, typed in two minutes:

After the brief and the prompt above:

Same meeting, 15 minutes shorter, and every item ends in something you can write down. “Updates” disappeared because they went into the status sheet. “AOB” disappeared too: anything that matters now has its own question and owner.

Using the AI already built into your calendar

If your company runs on Microsoft 365 or Google Workspace, you may not need a separate chatbot.

• Outlook with Copilot: Microsoft’s support page explains that in new Outlook you create the meeting, add a title and attendees, open Copilot in the description (Alt+I) and choose “Auto draft an agenda”, or type your own prompt with the goal and talking points. With a Microsoft 365 Copilot license, “Schedule with Copilot” can also turn an email thread into an invite with a title and draft agenda.
• Google Docs with Gemini: Google’s Workspace Learning Center shows how to draft an agenda with “Help me write” in Docs, and how to type “@” and pick Meeting notes to link a doc to a Calendar event. Availability depends on your Workspace plan and admin settings.

These built-in tools are handy because they already know the title and attendees. Their weakness is the same as any chatbot: if you don’t give them the goal and the open questions, you get the generic agenda. Paste the rules from Step 2 into their prompt box and you get the better version.

A reusable agenda template prompt for recurring meetings

Weekly team meetings are where recycled agendas live. Instead of reusing last week’s list, keep this prompt in a note and run it the afternoon before:

That last line is a small gift to your team. Some weeks the honest answer is that a status message is enough.

If you also want the agenda to start from the previous meeting’s outcome, our guide on summarizing meeting notes with ChatGPT shows how to get clean decisions and actions out of a messy transcript. Paste that summary into the prompt above and the loop closes itself. Only have a recording of the last meeting? Here is how to transcribe audio with AI so you have text to work from.

What to keep out of the chatbot

Agendas often touch sensitive things: a reorganization, a client dispute, salaries. Before you paste background into a tool, check what your company allows. On personal ChatGPT plans, OpenAI’s data controls page says conversations can be used to improve its models unless you switch off “Improve the model for everyone”, and Temporary Chats are not used for training. It also says content from ChatGPT Business and Enterprise workspaces is not used for training by default. When in doubt, describe the situation in general terms (“a budget overrun with a supplier”) instead of pasting names and numbers.

Common mistakes

• Asking for an agenda without a goal. You’ll get a pretty list that steers nowhere.
• Keeping every item the AI suggests. Models like to be thorough. Your attendees don’t. Cut to what needs the group.
• Time boxes that don’t add up. Check the total yourself. A 60-minute plan in a 45-minute slot means the last item, often the decision, gets skipped.
• No owner per item. An item without a lead tends to become a general chat.
• Sending it an hour before. If people need to read something, they need the agenda the day before.

FAQ

Can ChatGPT make a meeting agenda?

Yes. It’s one of the easiest work tasks to hand over, as long as you give it the goal, the people, the length and the open questions. The prompt in Step 2 works in ChatGPT, Claude and Gemini without changes. New to ChatGPT? Start with our ChatGPT tutorial for beginners.

Is there a free AI meeting agenda generator?

The free versions of ChatGPT, Claude and Gemini all handle this task well with a good prompt, so you don’t need a dedicated generator. Dedicated tools mostly add a template around the same idea. The quality comes from your brief, not the tool.

What should a good meeting agenda include?

The goal of the meeting, each item written as a question, its purpose (inform, input or decide), a time box, an owner, and what to read or bring. End with a few minutes to confirm decisions and who does what.

Can AI turn the agenda into a project plan afterwards?

Yes. Once the meeting has made its decisions, paste the agenda plus the outcomes into a chatbot and ask for tasks, owners and dates. Our walkthrough on using AI to create a project plan takes it from there.

Your next step

Open your calendar, find the next meeting you’re running, and spend 60 seconds on the brief from Step 1. Run it through the prompt and send the agenda with the invite today. Your attendees will notice the difference before the meeting even starts. To find room for that prep in a busy day, see how to use AI to plan your day. Once the meeting is under way, an AI note taker for meetings can capture decisions so you stay present instead of typing. For more small workflows like this, the kind that take an annoying task off your plate, start with the free Launchpad on our home page.

Your manager just said “can you put a plan together for this by Friday?” and you nodded. Now you’re staring at a blank spreadsheet, the project lives in five email threads and your head, and you’re not sure where it even starts.

Here’s the short answer. To use AI to create a project plan, don’t type “make me a project plan for a website relaunch”. Give ChatGPT, Claude or Gemini a five-minute brain dump of the goal, the deadline, the people and the limits. Let it ask you questions first. Then have it break the work into deliverables, turn those into a dated task list with owners, and poke holes in it before anyone sees it. The AI does the structuring. You keep the dates honest.

Want one practical AI workflow like this every week, free?

Can ChatGPT create a project plan?

Yes, and it’s good at it. A project plan is mostly structure: what has to be delivered, which tasks get you there, in what order, by whom, by when. Turning a messy description into that kind of structure is exactly what language models do well.

What it can’t do is know your project. It doesn’t know that the designer is on holiday in week three, that legal takes ten days to sign anything, or that the client always changes their mind after the first draft. Ask for a plan without that context and you get a neat, confident, generic plan with made-up durations. OpenAI itself explains that language models produce “plausible but false statements” partly because standard training rewards guessing over admitting uncertainty (OpenAI, Why language models hallucinate). A guessed task duration is exactly that: a guess that looks like a fact.

So the deal is the same as with any work task you hand to AI. You bring the facts and the judgment. The AI brings the structure and the speed.

How to use AI to create a project plan in 6 steps

This works with the free version of ChatGPT, Claude or Gemini. Keep all six steps in one chat so the AI remembers what you’ve already agreed on.

Step 1: Brain-dump the project (5 minutes, no AI yet)

Open a note or record a voice memo and answer these in plain words. Messy is fine.

• The goal: what is different when this project is done? “New CRM live and the sales team using it” beats “CRM project”.
• The deadline, and whether it’s fixed (a trade show) or soft (someone’s wish).
• Done means: the two or three things that must be true to call it finished.
• People: who’s involved, how many hours a week each one really has, and any holidays you know about.
• Limits: budget, tools you must use, approvals you need, things that are out of scope.
• What worries you: the part you suspect will go wrong. You usually know.

Paste in anything you already have: the client email, meeting notes, a rough budget. If your notes are a wall of text from a kickoff call, our guide on turning meeting notes into a report with ChatGPT cleans them up first.

Step 2: Let the AI ask you questions before it plans

This is the step that separates a useful plan from a generic one. Paste your brain dump below this prompt:

Answer each question in a line or two. This is usually where the plan gets real: “who signs off on the design?” is a question you’d rather answer now than in week four.

Step 3: Break the work into deliverables

Project managers call this a work breakdown structure. It sounds formal, but it’s simply the full list of things the project has to produce, split into smaller pieces. The Project Management Institute describes a good one as deliverable-oriented and complete: the pieces together should add up to 100% of the work in scope, including the project management itself, and nothing outside it (PMI, Developing and elaborating effective work breakdown structures). That 100% idea is your best check on what the AI gives you.

Read the list slowly. Cross out what doesn’t belong, add what’s missing. This is your scope now, and it’s the thing you’ll point at when someone asks for “just one more small thing” in week five.

Step 4: Turn it into a timeline with owners

Now the plan gets dates. The trick is to make the AI ask for durations instead of inventing them, and to put the result in a table you can paste straight into Excel or Google Sheets.

Those brackets matter. They turn every AI guess into a visible question for you, instead of a quiet assumption buried in row 23. Go through each one and replace it with a real estimate, ideally from the person who’ll do the work. If you want to sort, filter or chart the table afterwards, our guide to analysing a spreadsheet with ChatGPT picks up from here.

Step 5: Stress-test the plan (risks and buffer)

Almost every first plan is too optimistic, and it’s not because you’re bad at planning. In a well-known study, psychology students predicted they’d hand in their thesis in about 34 days. They took about 55 on average, and fewer than half finished even by their own “if everything goes wrong” date (Buehler, Griffin and Ross, 1994, Journal of Personality and Social Psychology). People plan for how the work should go, not how it usually goes.

AI is a useful outsider here because it has no stake in your plan looking good:

You don’t have to accept every point. But if it flags that your designer has 60 hours of work in a 20-hour week, believe it.

Step 6: Make it visible and keep it alive

A plan nobody looks at is a document, not a plan. Two easy ways to share it:

• A spreadsheet: ask for the final schedule “as CSV” and paste it into Excel or Google Sheets. Add a status column people update each week.
• A Gantt chart: ask “Turn this schedule into a Mermaid Gantt chart.” Mermaid is a free text-to-diagram tool, and its Gantt chart syntax is simple enough that AI writes it well. Paste the result into the free Mermaid Live Editor and you get a timeline image you can drop into a slide or an email.
• A flowchart: for the steps, decisions and handoffs inside the plan, see how to make a flowchart with AI. It works in the same free Mermaid editor.

To keep the plan alive, put it in a project space inside your AI tool. ChatGPT Projects keep related chats, files and instructions together so ChatGPT can use the same context each time (OpenAI Help Center), and Claude has Projects too, including on free accounts, with a limit of five (Claude Help Center). Upload the plan once, and every Friday you can paste in what happened and ask “what’s slipping, and what should I tell the team?”

Example: a 6-week CRM switch for a small team

Here’s what this looks like on a real kind of project. Say you run a five-person agency and you’re moving from spreadsheets to a CRM in six weeks. Your brain dump is ten lines: the goal (all leads and clients in the CRM, the team using it daily), the deadline (before the busy season starts), who’s involved (you, an assistant with 10 hours a week, a freelancer for the data import), and your worry (the old spreadsheet is a mess).

In Step 2, the AI asks things like: Who decides which CRM? Is the data clean-up part of this project? Does anyone need training? Do you need to connect email or a website form? Each answer changes the plan.

After Steps 3 and 4, a slice of the schedule looks like this:

The “(5?)” next to the clean-up is the AI telling you it guessed. Your assistant looks at the spreadsheet and says it’s more like eight days, which pushes the import back. Step 5 then flags that the website form has no owner and that the whole plan hangs on the clean-up. That’s two real problems found in week zero instead of week five. And if the CRM is meant to automate follow-ups later, our list of email automation examples is the natural next project.

And the Mermaid version of the same plan starts like this, readable even before you render it:

More ChatGPT prompts for project planning

Once the plan exists, the same chat can take care of the admin around it. A few prompts worth saving:

• Kickoff email: “Write a short kickoff email to the team: the goal, the deadline, who owns what in the first two weeks, and what I need from each person by Friday.”
• Kickoff meeting agenda: “Turn this plan into a 45-minute kickoff agenda with a goal, time boxes and the decisions we need to make.” Our guide on how to use AI to create a meeting agenda walks through it step by step.
• Weekly status update: “Here’s what got done this week [paste]. Update the schedule, mark what’s late, and write a five-line status update for my manager.” For a fully automated version, see our guide to automated status updates with Gemini.
• Scope change: “The client wants to add [request]. Show me what it does to the timeline and draft a polite reply that explains the trade-off.”
• One-page summary: “Summarise this plan on one page for someone who has two minutes: goal, deadline, three biggest risks, and what I need from them.”

Planning a whole new business or side venture rather than a single project? Our guide on how to use AI to write a business plan covers the market, the numbers and the pitch.

Mistakes to avoid

• Trusting dates you didn’t check. Every duration the AI made up is a risk with a nice font. Keep the brackets until a person confirms the number.
• Planning people at 100%. Someone with “40 hours” also has email, meetings and other projects. Tell the AI their real project hours.
• Too much detail too far ahead. Plan the next two or three weeks in detail and keep later phases at the deliverable level. PMI’s guidance on the WBS makes the same point: it can be more detailed on near-term work and more summary on future work, filling in as things become clear (PMI, The WBS: basic principles).
• Pasting things you shouldn’t. Client names, contracts and salaries may be confidential. Check your company’s AI rules, or replace names with roles (“Client A”, “Developer”).
• Skipping the “done means” line. Without it, the AI and your team will each assume a different finish line.

If you’d rather build this habit with Claude in particular, our guide on how to use Claude for work covers the basics, including how to set up a project space.

FAQ

Can ChatGPT create project plans for free?

Yes. The free versions of ChatGPT, Claude and Gemini can all build a work breakdown, a schedule table and a risk list from your notes. What makes the plan good is the brief and the questions in Step 2, not a paid plan.

Can AI make a Gantt chart?

Yes. Ask it to turn your schedule into a Mermaid Gantt chart and paste the result into the Mermaid Live Editor, or ask for a CSV and build the chart in your spreadsheet or project tool.

Should I use AI instead of project management software?

Use them together. AI is great at turning a vague idea into a structured plan and at writing the updates around it. A tool like a shared spreadsheet, Trello or Asana is better at tracking who ticked off what. Many people draft the plan with AI, then import the table into the tool the team already uses.

What’s the best prompt for project planning?

One that makes the AI ask questions first, forbids invented facts, and asks for a fixed table format. The Step 2 and Step 4 prompts above do exactly that.

How detailed should an AI project plan be?

Detailed enough that every task has one owner and fits in a few days. If a task says “build website” and takes 20 days, ask the AI to split it.

If the project starts with a choice, like which vendor, tool or approach to go with, settle it first with a decision matrix made with AI, then plan around the winner.

Your next step

Take the project that’s been sitting in your head all week, spend five minutes on the brain dump from Step 1, and run it through the Step 2 prompt today. You’ll have a first plan, with its weak spots marked, before your next meeting. Then, to turn this week’s tasks into a realistic schedule, here’s how to use AI to plan your day. For more small workflows like this, the kind that take a dreaded task off your plate, start with the free Launchpad on our home page.

Once the plan exists, the daily work starts: status updates, risk checks, stakeholder emails. These ChatGPT prompts for project management cover that part.

Once the plan exists, here is how to use AI for project management day to day, from status updates to risk logs.

Planning a building project? Read project management software for architects for the tools that fit studios.

A new review lands on your Google profile. Two stars. “Waited 40 minutes, nobody told us anything.” Your stomach drops, you start typing a reply, delete it, start again, and twenty minutes later you still have nothing you would want a future customer to read.

Here’s the short answer. To use AI to respond to Google reviews, don’t ask it to “reply to this review”. Give it three things first: the review itself, the facts only you know (what actually happened, what you can offer), and how your business talks. Then let ChatGPT, Claude or Gemini write a short draft, check it against a five-point list, and post it yourself. The AI finds the calm words. You bring the truth and press the button.

Want one practical AI workflow like this every week, free?

Can AI respond to Google reviews?

Yes, in two ways. The simple way works for everyone: you copy a review into ChatGPT, Claude or Gemini, get a draft, and paste your final reply into your Business Profile. The second way is newer. Google now lets you connect your Business Profile to the Gemini web app, and Gemini can then fetch your reviews and draft replies for you. Google announced that connection on its official blog in June 2026.

Google has also been testing a “Reply to reviews with AI” button inside Business Profile itself. Search Engine Land reported in March 2026 that the test was limited, showed up unevenly across accounts, and was seen in the U.S., Brazil and India but not widely in Europe. So if you don’t see that button, nothing is wrong with your account.

Whichever route you take, one thing doesn’t change. According to Google’s own help page on managing reviews, your reply is public, it shows as coming from your business, the reviewer gets notified, and Google checks replies against its content policies before they go live. That check usually takes up to 10 minutes, but it can take up to 30 days. A reply is a small public statement from your business. Treat the AI draft like a first draft from a new colleague: useful, never final.

What a good review reply actually needs

Before you write a prompt, know what you’re asking for. A guide by a Google Business Profile Product Expert in Google’s own community boils it down well:

• Positive reviews: short and sincere. Thank them, mention what they liked, no hard sell.
• Negative reviews: no generic copy-paste. Understand what went wrong, apologise if it’s warranted, stay professional, and never get defensive or personal.
• Timing: that guide suggests aiming to reply within 24 to 72 hours.

Notice what’s missing from that list: long paragraphs, marketing slogans, and the phrase “we value your feedback” three times. That’s exactly what AI writes when you give it nothing to work with. So the trick is not a clever prompt. It’s giving the AI the facts it can’t guess.

Step 1: Write a five-line “reply brief” once

This takes about ten minutes and you reuse it for every review. Open a note and fill in:

Business: [name, what you do, city]
Voice: [e.g. friendly and direct, first names, no exclamation marks]
Sign-off: [e.g. "Sanne, owner" or "The team at ..."]
How unhappy customers can reach us: [business email or phone]
Never say: [e.g. promises about refunds, staff names, anything about health]

The sign-off matters more than it looks. Google shows every reply as coming from the business, so a human name at the end makes it feel like a person read the review. The same community guide suggests that when a review mentions a specific employee, that person can reply and add their name or initials.

The “never say” line is your safety rail. AI likes to promise things (“we’ll refund you in full”) because it sounds kind. Only you know what you can actually offer.

Step 2: The prompt for positive reviews

Positive reviews are where AI saves you the most time, because they’re easy to answer and easy to put off. Paste your brief, then this:

You help me reply to Google reviews for my business. Use the brief above for voice and sign-off.

Write a reply to this review:
"[paste the review]"

Rules:
- 2 to 3 sentences, max 60 words.
- Thank them and mention ONE specific thing they wrote about.
- No marketing slogans, no discounts, no links.
- Don't repeat the business name more than once.
- Don't invent details that are not in the review or the brief.
Give me 2 versions: one warm, one shorter.

Asking for two versions is the small move that makes this work. You pick the one that sounds like you, change a word, done. If you have ten unanswered five-star reviews, paste them all in one go and ask for one reply per review, each mentioning something different. Then read every single one before it goes out.

Step 3: The prompt for negative reviews

This is where people get burned, so slow down. Write the facts down first, in your own words, even if they’re messy. Then:

Help me reply to a negative Google review. Use the brief above.

The review:
"[paste the review]"

What actually happened (my notes, not for publishing as-is):
[e.g. Saturday 7pm, two staff out sick, kitchen was 30 min behind, nobody went to the tables to explain]

What I can honestly offer:
[e.g. invite them to email me directly / we now tell tables when the kitchen is behind]

Rules:
- Max 80 words, calm and human, no excuses.
- Acknowledge their experience in plain words.
- Apologise only for what we actually got wrong.
- Mention the one concrete change or offer from my notes, nothing more.
- Invite them to contact us using the channel in the brief.
- Never share any personal details about the customer or our staff.
- Never argue about facts in public.
Then list anything in your draft that I should double-check.

That last line is my favourite part. It makes the AI point at its own weak spots (“you mentioned a change in process; confirm this is true”) instead of hiding them in nice wording.

A habit worth building: if a review makes you angry, write your notes, run the prompt, and don’t post until later that day. The AI reply will be calm either way. You want to be calm too when you read it.

Step 4: Check the draft before you post (the five-point list)

Read the AI’s reply once, slowly, against these five questions:

1. Is every fact true? If the draft says “we’ve retrained the team”, did you? Delete anything you can’t back up.
2. Is anything private in it? Google’s Maps content policy doesn’t allow posting other people’s personal information without consent, such as a full name, last name, or financial or medical details. Your own business email or phone number is allowed. Booking details, order numbers and staff surnames stay out.
3. Does it offer anything in exchange for changing the review? The same policy forbids offering payment, discounts or free goods for posting a review or for revising or removing a negative one. “Email me and I’ll give you 20% off if you update your review” breaks that rule. “Email me so I can make this right” doesn’t.
4. Does it sound like you? Read it out loud. If you’d never say “we sincerely apologise for any inconvenience caused” across the counter, change it.
5. Is it short? Most good replies fit in two to four sentences. A wall of text under a two-star review reads as defensive, even when it isn’t.

This check takes about a minute. It’s the minute that keeps a time-saver from turning into a public mistake.

Step 5: Post it, then keep an eye on it

Posting is the same as always: go to your Business Profile, select Read reviews, then Reply next to the review, paste your final text and confirm. Google’s help page explains you can also edit or delete your reply later from the same place.

Two things people miss. First, Google reviews your reply before it shows, so if it doesn’t appear right away, give it time. If it’s rejected, you’ll be asked to edit it. Second, customers can change their review after reading your reply, and the review date updates when they do. The community guide adds that owners aren’t notified about those edits, and an old reply can then look like it came before the new review. It’s worth a quick look at your recent reviews once a week.

Using Gemini connected to your Business Profile

If you have one business location, the Gemini connection can cut out the copy-paste. Per Google’s help page, here’s what you need:

• You’re the owner or manager of only one verified Business Profile. If you manage several, it isn’t available.
• You’re signed in to the Gemini web app with a personal Google Account linked to that profile. Work or school accounts don’t work for this yet.
• Keep Activity is switched on in Gemini.
• You’re 18 or over, and you use it at gemini.google.com.

Then you go to gemini.google.com, ask something about your Business Profile, and follow the steps to connect it. If Gemini doesn’t pick it up, Google suggests adding @Google Business Profile to your prompt. Once connected, Gemini can fetch your star ratings and reviews, draft replies, and summarise themes in your feedback.

That last one is underrated. Ask it something like:

@Google Business Profile Look at my reviews from the last 3 months. What are the 3 things customers praise most and the 3 things they complain about most? Quote one short example review for each.

Now your reviews aren’t just something to answer. They’re a to-do list for the business. And because Gemini can also post and delete replies through that connection, keep the same habit as above: you read every draft before anything goes live.

New to Gemini? Our Gemini tutorial for beginners walks you through the basics first.

A before-and-after example

Here’s an illustration, a made-up café, to show the difference a brief makes.

The review: “Coffee was great but we waited 40 minutes for two sandwiches and nobody said a word.”

What AI writes with no brief:

Dear valued customer, thank you for taking the time to share your feedback! We sincerely apologise for any inconvenience you may have experienced. At [Café Name], customer satisfaction is our top priority and we strive to provide excellent service at all times. We hope to see you again soon!

Polite. Empty. It could sit under any review of any business, and readers can tell.

What AI writes with the brief and the notes:

You're right, and I'm sorry. Forty minutes for two sandwiches is too long, and someone should have come to your table to explain. We were short two people that Saturday. That's on us, not on you. We now tell every table when the kitchen is running behind. Glad the coffee hit the spot. If you'd like to tell me more, email me at hello@[yourcafe].com. Sanne, owner

Same AI, same two minutes. The difference is the facts you gave it.

What AI should never do with your reviews

Using AI to reply is fine. Using it to fake reviews is a different story, and it’s worth saying plainly because AI makes it so easy.

• Google: its Maps policy says reviews must reflect a genuine experience. Fake engagement, paid reviews and reviews from conflicts of interest (like staff or family) aren’t allowed and get removed.
• U.S. law: the FTC rule on consumer reviews, 16 CFR 465.2, makes it a violation for a business to write or create a review that misrepresents that the reviewer exists, used the product, or what their experience was. The final rule in the Federal Register took effect on October 21, 2024, and it names AI tools as something that makes fake reviews easier to write.

Outside the U.S., check the rules where you do business. This isn’t legal advice, but the safe line is simple: AI helps you answer real customers. It never pretends to be one.

Common mistakes when you use AI for review replies

• Same reply under every review. Google’s policy also lists repetitive content as not allowed on Maps, and to a reader ten identical “Thanks for the kind words!” replies look like nobody’s home. Ask the AI to mention something specific each time.
• Letting it apologise for things you didn’t do. An apology for a mistake you never made reads as an admission. Only apologise for what’s real.
• Pasting customer data into the chat. The review text is public, so that’s fine. Booking systems, phone numbers and order histories don’t belong in your prompt.
• Arguing in the reply. If a review is false or breaks Google’s rules, Google lets you flag it for review. Do that instead of debating it in public.
• Answering only the bad ones. The community guide recommends replying to positive reviews too. With AI drafting, that’s a two-minute job.

If you write a lot of customer messages beyond reviews, the same “brief first, draft second” approach works for email too. See how to use ChatGPT to draft reply emails faster and our ChatGPT client communication templates. And when a reply comes out stiff, the tips in make this email sound more professional work just as well the other way round, to make it sound more human.

Reviews only come from the customers who choose to write one. To hear from the quiet majority too, see how to use AI to create a survey people actually finish.

FAQ

Can AI respond to Google reviews automatically?

Partly. Gemini connected to your Business Profile can draft replies, and Google has tested an AI reply button inside Business Profile. Search Engine Land noted conflicting reports on whether the test’s bulk replies still needed review. My advice: even if a tool can post on its own, read each reply first. It’s public, and it’s your name.

Does Google penalise AI-written review replies?

Google’s help pages don’t say AI replies are a problem, and Google itself offers AI drafting. What it does check is whether your reply follows its content policies. A reply that’s accurate, polite and free of personal data is fine however you drafted it.

Should I reply to every review?

The Google community guide recommends replying to all reviews, positive ones included. With a reply brief and the prompts above, most replies take a couple of minutes.

Which AI is best for review replies?

For drafting, ChatGPT, Claude and Gemini all do a good job once you give them a brief. Gemini has the extra option of connecting to your Business Profile if you manage a single location. If you’re choosing between them, our ChatGPT vs Claude for writing comparison helps.

How fast should I reply?

The Google community guide suggests aiming for 24 to 72 hours. For a negative review, a calm reply the same day beats a perfect one next week.

Your next ten minutes

Open your Business Profile and find the oldest review you never answered. Write the five-line reply brief, run the prompt from Step 2 or Step 3, check it against the five points, and post it. That’s one review done, and a system for every review after it.

If you’d like more workflows like this, small things that give you back real hours at work, start on our home page and join Launchpad. It’s free.

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.

Want one practical AI workflow like this every week, free?

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.