Category: AI at Work

You need to hire someone. The work is piling up, you know exactly what you need help with, and yet the job post has been sitting as an empty document for a week. Every version you start sounds either like a wish list for a superhero or like every other ad on the job board.

Here’s the short answer. To use AI to write a job description, don’t ask it to “write a job description for an office manager”. Give it a ten-minute brief first: what this person must get done in their first 90 days, the five things they truly need, the pay range, how and where they work, and how to apply. Then let ChatGPT, Claude or Gemini turn that into a clear draft, cut the wish list, and check the wording before you post it. The AI writes. You decide what the job really is.

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

Can you use AI to write a job description?

Yes, and it’s one of the most sensible things to hand to AI. A job description is structured writing with a clear goal, and most of the effort goes into getting a messy idea into clean sections. That’s exactly what language models are good at.

Two things stay with you, though. First, the AI doesn’t know your job. Ask for “a marketing assistant” and you get the average of thousands of marketing assistant ads, which is the bland text you were trying to avoid. Second, you’re responsible for what you publish. LinkedIn says it plainly about its own AI job description feature: the draft “may produce surprises or mistakes”, you’re still responsible for the final job description, and the law may require you to add things like a salary range or an applicant privacy notice (LinkedIn Help).

So the deal is simple: you bring the facts, the AI brings the structure and the words.

How to use AI to write a job description in 5 steps

Step 1: Write a ten-minute brief (no AI yet)

This is the step everyone skips, and it’s the one that makes the difference. Open a note, or record a voice memo on your walk, and answer these questions in plain words:

• Why are you hiring? What’s falling through the cracks right now?
• What does success look like after 90 days? Three concrete results, not traits. “Invoices go out by the 3rd of every month” beats “detail-oriented”.
• What does a normal week look like? The real tasks, roughly in order of time spent.
• Must-haves: the few skills or experiences they can’t do the job without. Try to stop at five.
• Nice-to-haves: things you can teach or live without.
• The facts: hours, location or remote/hybrid, start date, pay range, who they report to, how to apply.
• Why would someone good say yes? Be honest: flexible hours, a small team, real responsibility, learning.

If you already have process notes or checklists for the work, paste those in too. If you don’t, our guide on using AI to write SOPs from a voice memo uses the same trick, and the SOPs you get out of it double as onboarding material for the new hire.

Step 2: Turn the brief into a draft with one prompt

Open the AI tool you already use. The free version of ChatGPT, Claude or Gemini is fine here: this is a writing job, not a research job. Paste your brief below this prompt:

The “Missing info” line is the important part. It stops the AI from filling gaps with invented perks, and it shows you what you forgot before a candidate has to ask.

Step 3: Cut the wish list

Your first draft will probably still ask for too much. AI loves to add “excellent communication skills” and “experience with a wide range of tools”. Push back with a follow-up:

Be strict here. A long list of requirements doesn’t find you a better person, it just tells good people they’re not good enough. If a requirement is really “years of experience”, ask yourself what those years should prove, and write that instead. “You’ve run payroll for a small team on your own” says more than “3+ years of experience”.

Step 4: Check the wording before anyone sees it

This is where a quick AI pass saves you real trouble. Words in a job ad can push people away without you meaning to.

• Age and other protected traits. In the US, the EEOC says it’s illegal to publish a job ad that shows a preference for, or discourages, applicants based on things like sex, age (40 or older) or disability. Its own example: an ad asking for “recent college graduates” may discourage people over 40 (EEOC). Phrases like “young team” or “digital native” sit in the same risky corner.
• Gendered wording. A well-known set of studies by Gaucher, Friesen and Kay found that job ads with more masculine-coded words (like “competitive” and “dominant”) made those jobs seem less appealing to women, mostly because they expected to belong less (Journal of Personality and Social Psychology, 2011).
• Pay. If you hire in the EU, new pay transparency rules mean you have to tell job seekers the starting salary or pay range in the vacancy notice or before the interview, and you can no longer ask about their pay history (European Commission). The directive also asks for gender-neutral job titles and vacancy notices (Directive (EU) 2023/970). Each EU country writes its own version into national law, so check the rules where you hire.

Then ask the AI to do a review pass:

Treat the answer as a second pair of eyes, not legal advice. If you hire often, or in a regulated field, have someone who knows employment law in your country read your template once.

Step 5: Make it fit where you post it

One description, a few versions. Ask the AI for a short version (around 80 words) for social posts and a message you can send to your network, and keep the full version for the job board or your careers page.

Posting on LinkedIn? It has a built-in “Draft with AI” button when you post a job (LinkedIn Help). It drafts from your job title, company page and profile, which means it knows even less about the real job than your brief does. Paste your own reviewed text instead, or use their draft only as a starting point and fix it with your brief.

Last step: read the final text out loud once. If you’d be slightly embarrassed to say a sentence to a candidate across the table, cut it.

A quick example: from vague to clear

Say you run a small accounting practice and want a part-time office manager. Here’s a typical first line from a lazy prompt, and the version you get from a real brief.

Lazy prompt result: “We are seeking a highly motivated, detail-oriented Office Manager to join our dynamic team and drive operational excellence.”

From a brief: “You’ll keep our six-person office running so the accountants can focus on clients: sending invoices on time, booking client meetings, and making sure nothing gets lost between email and the client file. It’s 24 hours a week, mornings, in our office.”

Same AI, same five minutes. The difference is that the second one had facts to work with. A candidate reading it knows right away if this is their kind of job, and that’s the whole point of a job description.

Mistakes that make AI job descriptions worse

• Prompting with only a job title. You get the average ad. Always give the brief.
• Letting it invent perks. “Competitive salary and great culture” means nothing, and made-up benefits come back to bite you in the interview. Keep the “use only my facts” line in your prompt.
• Posting without a pay range. Beyond the legal side in some places, it saves everyone from interviews that end at the salary question.
• Pasting candidate data into the chat. For writing the ad you don’t need any personal data, so keep it that way. Screening applicants with AI is a separate, more sensitive job.
• Skipping your own read. AI text tends to sound polished and empty. Your read is what makes it sound like your company.

If the drafts keep sounding stiff, it’s worth trying the same brief in a second tool. Our comparison of ChatGPT vs Claude for writing shows where each one tends to sound more natural.

FAQ

Can I use ChatGPT to write a job description for free?

Yes. A job description is a short writing task, and the free versions of ChatGPT, Claude and Gemini all handle it well. What matters is the brief you give it, not the paid plan. New to the tool? Start with our ChatGPT tutorial for beginners.

What’s a good ChatGPT job description prompt?

One that gives the AI your real facts, a fixed structure and a rule not to invent anything. Use the Step 2 prompt above, and add the Step 3 and Step 4 follow-ups before you post.

Is it OK to use AI to write a job description?

Yes, as long as you check the result. You’re responsible for what you publish, including the accuracy of the role and any legal requirements where you hire, like pay information or a privacy notice.

Will candidates notice it was written with AI?

They notice generic text, whoever wrote it. A description built on your brief, with real tasks and a real pay range, reads like a person who knows the job. That’s what candidates respond to.

Can AI write the interview questions too?

Yes. Once your description is final, paste it in and ask for interview questions that test each must-have, plus what a strong answer would include. Same rule: you check them before you use them.

When the new hire’s first review comes around, the same brief-first approach works there too: see how to use AI to write a performance review.

Once the description is posted, the next job is the interview itself. Here is how to use AI to create interview questions that test each must-have, with a scoring guide you agree on before you meet anyone.

When the right person says yes, the next job is their first 90 days. Here’s how to use AI for employee onboarding, from the manager’s brief to the 30, 60 and 90 day check-ins.

Your next step

Take the role you’ve been putting off, spend ten minutes on the brief from Step 1, and run it through the prompt today. You’ll have a draft you can actually post before lunch. 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.

A supplier sends over a 14-page agreement. It is due back Friday, the liability clause looks odd, and you are not a lawyer. You have seen ads for AI contract review software and wonder if one of them would save you the afternoon, or just add another subscription.

Here is the short answer. AI contract review software reads a contract, flags clauses that differ from what you normally accept, and suggests edits. If you sign a few contracts a month, a general assistant like Claude or ChatGPT with a good checklist covers most of what you need. If you sign ten or more a month, or several people negotiate for the same company, a dedicated tool with playbooks starts to pay off. Either way, a person still makes the final call on anything with real money or risk attached.

Below: what these tools actually do, the four kinds on the market, six questions that decide which one fits you, and a 30-minute test you can run on your own contract before paying anything.

What AI contract review software actually does

Strip away the marketing and most tools do four jobs:

• Find and label clauses. Payment terms, liability caps, termination, auto-renewal, confidentiality, governing law.
• Compare them to a standard. That standard is called a playbook: your list of “we accept this, we push back on that, we never sign this.” The tool flags every clause that falls outside it.
• Suggest a redline. Tracked changes in Word with replacement wording, so you can accept, edit or reject each one.
• Summarize and store. A short summary for your manager, plus key dates such as renewal deadlines pulled into a list.

What it does not do is know your business. It does not know that this supplier is your only option, or that you agreed something different on the phone last week. That context is still yours.

The four kinds of AI contract review tools

1. A general AI assistant (Claude, ChatGPT, Gemini)

You upload the contract and ask questions. Claude, for example, accepts PDF and DOCX files and reads text and visuals in PDFs of up to 100 pages (Claude Help Center). There is no built-in playbook, so the quality depends on your prompt and your checklist. Cheapest option, and for many freelancers and small business owners, enough. We walk through the full method in getting the key points out of a contract PDF with Claude.

Best for: a handful of contracts a month, one person reviewing, standard agreements like NDAs, service agreements and supplier terms.

2. AI inside Word

Microsoft’s Copilot in Word can summarize a document, answer questions about it and rewrite selected passages, and on shared documents it shows suggested changes before anything is added (Microsoft Support). It needs an eligible Microsoft 365 subscription or Copilot license. It is a general writing assistant, not a contract specialist, so it will not know your negotiating positions unless you tell it.

Best for: teams that already live in Word and Microsoft 365 and want help reading and rewording, not a full review system.

3. Dedicated contract review add-ins

Tools like Spellbook and LegalOn sit inside Word and are built for this one job: review against a playbook, then redline. LegalOn advertises ready-made playbooks for common agreements such as NDAs and MSAs. Spellbook offers a 7-day free trial and prices by the number of people on the license, with the exact price given after a demo. These are built mainly for lawyers and in-house legal teams.

Best for: a legal team, or a business with a regular flow of contracts and a clear set of positions it wants applied every time.

4. Contract management platforms with AI review

Platforms like Juro and Luminance cover the whole life of a contract: templates, review, signing, storage and renewal tracking, with AI across all of it. Juro’s own pricing page says businesses signing around ten or more contracts a month are the ones that see a return (Juro pricing). Expect a demo and a sales process, not a sign-up button.

Best for: companies where sales, HR, procurement and legal all touch contracts and need one place to keep them.

How to choose: six questions that decide it

1. How many contracts a month? Under ten, start with a general assistant and a checklist. Over ten, test a dedicated tool. This is the single biggest factor.
2. Who reviews them? If it is you alone, a playbook mostly lives in your head and a written checklist does the same job. If five people negotiate for the company, a shared playbook stops each of them accepting different terms.
3. Where do your contracts live? Mostly Word files you redline back and forth? An add-in fits. Mostly signed PDFs you need to search later? A platform with a repository fits.
4. Do you have written positions? Playbook tools are only as good as the playbook. If you cannot yet write down “our liability cap is X” or “we never accept automatic renewal over 12 months,” write that list first. It makes any tool better, including a free one.
5. What happens to your data? Contracts hold names, prices and confidential terms. Read the tool’s data terms before uploading. For example, on Claude’s Free, Pro and Max plans, chats can be used for model training if you allow it in your privacy settings, while Team, Enterprise and API use fall under separate commercial terms that this setting does not cover (Anthropic). The Law Society’s guidance for solicitors makes the same point: know how a tool uses what you put in before you share client data (Law Society).
6. Which languages and countries? If you sign contracts under Dutch, German or UK law, test the tool on one of those, not on the vendor’s demo contract.

The 30-minute test before you pay for anything

Every vendor demo uses a contract that makes the tool look good. Use your own instead.

1. Pick one real contract you already negotiated and know well. You know which clauses were a problem, so you can judge the tool’s answer.
2. Write down the three to five issues you found before you upload anything.
3. Run the same contract through two options: a general assistant with the prompt below, and a free trial of one dedicated tool if your volume justifies it.
4. Score them: did each one find your issues? Did it invent problems that are not there? Did it quote the right clause numbers? Could you use its suggested wording?

If the general assistant finds your issues and the paid tool adds only formatting, you have your answer. If the paid tool catches things the assistant missed, and you review contracts every week, the subscription likely earns its place.

Here is a first-pass prompt to use with Claude or ChatGPT. Upload the contract first, then paste it:

You are helping me do a first-pass review of the attached contract. I am the [customer / supplier / freelancer] in this agreement. I am not a lawyer.

My positions:
- Liability: [e.g. capped at the fees paid in the last 12 months]
- Payment terms: [e.g. 30 days, no longer]
- Termination: [e.g. I can end it with 30 days notice]
- Renewal: [e.g. no automatic renewal longer than 12 months]
- Anything else that matters to me: [list]

1. List every clause that conflicts with my positions. For each one, quote the clause number and the exact wording, explain the risk in one plain sentence, and suggest replacement wording.
2. List any clause that is unusual for this type of agreement, even if it is not on my list.
3. List all dates and deadlines (start, renewal, notice periods).
4. If you are not sure about something, say so. Do not guess. Only quote text that is actually in the contract.

Then check every quote against the contract yourself. AI tools can produce text that sounds right and is not; the Law Society’s guidance calls this hallucination and warns against treating outputs as accurate without checking (Law Society). If a quote does not appear in the document, the answer around it is not reliable either. For contracts longer than about 100 pages, see our guide on analyzing long PDF files with Claude.

A real example of where the line sits

Take a freelance consultant who signs a client agreement every few weeks. The work is the same each time: check payment terms, liability, who owns the deliverables, and notice periods. A checklist of five positions and the prompt above catches the usual problems in about ten minutes, and a dedicated tool would cost more than the time it saves.

Now take a 40-person software company where sales, procurement and HR all send contracts to one in-house lawyer. That lawyer is the bottleneck. A shared playbook that lets sales handle standard NDAs without waiting, and only escalates the odd ones, is exactly what the dedicated tools are built for.

Most readers of this site sit closer to the first case than the second. Start there.

What AI contract review will not do for you

• It will not replace legal advice on high-stakes deals. Large sums, personal guarantees, exclusivity, intellectual property you depend on, or anything you would lose sleep over: get a lawyer to read it. The AI review makes that meeting shorter and cheaper, because you arrive with the issues already listed.
• It will not know what was agreed outside the document. Emails, calls and side letters are invisible to it unless you add them.
• It will not negotiate for you. It suggests wording. Whether to push back, and how hard, depends on the relationship.

If you are not ready to buy software yet, you can still get a plain-English read of a contract at work. Our guide to using AI for legal documents shows a safe way to do it, with copy-ready prompts and a note on when to call a lawyer.

Quick answers

Can I just use ChatGPT or Claude to review a contract?

For a first pass on everyday agreements, yes, as long as you give it your positions, ask it to quote clauses exactly, and check those quotes yourself. Check the data settings of your plan before uploading anything confidential.

What does AI contract review software cost?

General assistants have free and paid plans. Dedicated tools such as Spellbook and LegalOn price per team and ask you to book a demo for a quote, and Spellbook offers a 7-day trial. Check each vendor’s pricing page, since these change often.

Is it accurate enough to rely on?

Rely on it to find things to look at, not to decide for you. Run the 30-minute test above on a contract you know well, and you will see its accuracy on your type of agreement, not someone else’s.

Do I need a playbook to start?

You need a short list of positions, even five lines. That list is your playbook, and it improves every tool on this page.

Your next step

Pick one contract you already signed, write down its three biggest issues, and run the prompt above. In half an hour you will know whether a general assistant is enough for you or whether a dedicated tool is worth a trial. If you want more practical setups like this, from using Claude for daily work to choosing AI invoice processing software, the free Launchpad on robotshelp.me is where we start you off.

You run a small online shop. Orders come in, but so do the carts that never finish, the first-time buyers who never come back, and the newsletter you meant to send three weeks ago. You know email should be doing more of the work. You just do not have an afternoon a week to write it.

Here is the short answer. Email automation for ecommerce means setting up a few emails once, each triggered by something a shopper does (signs up, leaves a checkout, buys, goes quiet), and letting your store send them on its own. Start with five: abandoned checkout, abandoned cart, welcome, post-purchase thank you, and win-back. Use the ready-made templates in your email tool, and use AI (ChatGPT, Claude, or the assistant built into Shopify) to write the copy in your own voice. You can have the first one live today.

Below: the five flows in the order I would build them, the exact settings that stop the classic mistakes, one copy-paste prompt for the writing part, and the legal basics so your emails keep landing in the inbox.

Want one practical AI workflow like this every week?

What email automation for ecommerce actually is

Two kinds of email leave your shop. Campaigns are the ones you write and send by hand to a list: a sale, a new collection. Automations (Klaviyo calls them flows, Shopify calls them marketing automations) are written once and then sent to each shopper at the moment they trigger it.

The trigger is the whole trick. A campaign reaches people whenever you happen to send it. An automation reaches one person right after they did something, while your shop is still on their mind.

And there is a lot to catch. Baymard Institute averaged 50 studies and lands on a documented cart abandonment rate of about 70% (Baymard). Be honest with yourself about that number, though. In Baymard’s own survey, the most common reason was simply “I was just browsing / not ready to buy” (Baymard). An email will not turn every one of those into a sale. It catches the people who meant to buy and got distracted.

Which tool you need (probably the one you have)

• Shopify store: Shopify Messaging, Shopify’s built-in email app, has ready-made automations for abandoned browse, abandoned cart, abandoned checkout, welcome series, thank you, first-purchase upsell and win-back (Shopify Help Center). Every store on the Basic plan and up gets 10,000 free emails a month, then it costs $1 per 1,000 emails, and abandoned checkout emails are always free (Shopify pricing).
• Klaviyo: a dedicated email and SMS tool for shops that want more control. It has a flow library with pre-built abandoned cart, browse abandonment and post-purchase flows (Klaviyo Help Center).
• WooCommerce or another platform: Mailchimp can send abandoned cart emails once your store is connected, including through the Mailchimp for WooCommerce plugin (Mailchimp Help).

My advice: do not switch tools to start. Build the five flows in what you already pay for. Move later, when you know which flows actually earn.

The 5 flows to set up first (in this order)

1. Abandoned checkout

Trigger: someone typed in their email at checkout and left without paying. These people were almost done buying, so this flow usually comes first.

The setting that matters: make sure the flow stops the moment they buy. In Klaviyo you add the profile filter Placed Order zero times since starting this flow. Klaviyo checks it before every message, so a buyer never gets a “you forgot something” email after paying (Klaviyo: abandoned cart flow). You will then see many “skipped” profiles in the report. Klaviyo says that is normal: it means the filter works.

In Shopify the abandoned checkout automation already skips people who completed the order before the email went out (Shopify Help Center).

What to write: the product they left (your tool pulls it in with a photo), one honest line about why it is worth finishing, and a button back to the checkout. Skip the fake countdown timer.

2. Abandoned cart

Trigger: they added something to the cart but never started checkout. Lower intent than flow 1, so softer copy and fewer emails.

The setting that matters: nobody should get both the cart email and the checkout email for the same visit. Klaviyo recommends running them as two separate flows and adding Started Checkout zero times since starting this flow plus Placed Order zero times to the cart flow (Klaviyo: Added to Cart flow). On Shopify, you also need the Klaviyo setting Track behavioral events switched on, or the Added to Cart trigger never fires.

3. Welcome series

Trigger: someone joins your list through a signup form. This is the moment they are most curious about you.

Shopify’s template sends a welcome email with a discount, then two emails that tell your story, then a reminder only if they have not bought yet (Shopify Help Center). That is a sound structure to copy in any tool. You do not have to lead with a discount. A shop that sells hand-poured candles could just as well open with “how we choose our scents” and keep the discount for email three.

Watch out: run one welcome flow, not two. Shopify warns that two active welcome automations send customers twice as many emails (Shopify Help Center).

4. Post-purchase thank you (and the next step)

Trigger: an order is placed. Keep the order confirmation itself as it is, that one is a transactional email. This automation comes a day or more later and is about the relationship: how to use or care for the product, an honest request for a review, and maybe one product that genuinely goes with it.

Shopify has both a thank you automation (first and second purchase) and a first-purchase upsell. Pick one to start, not both at once.

5. Win-back

Trigger: a set amount of time has passed since their last order. You choose the time, and it should match how often people actually need your product. Coffee beans run out in weeks, a winter coat lasts years.

Keep it human: “It has been a while. Here is what is new.” If you sell something people rebuy, a simple reminder that they may be running low often fits better than a discount.

Let AI write the emails (without sounding like everyone else)

Setting up the triggers takes minutes. Writing ten good emails is the part that stalls most shop owners. That is where AI earns its place.

Inside Shopify: in Shopify Messaging, the AI assistant Sidekick can write subject lines and body text. You click the icon in the subject or text field and describe the email (Shopify: generate email text). Shopify adds a fair warning: you are responsible for the accuracy of what you publish, so read every line before it goes out.

In ChatGPT or Claude: you get more control over voice if you give the assistant real material. Paste two or three emails or product descriptions you wrote yourself, then use a prompt like this:

You are helping me write automated emails for my online shop.

About the shop: [what you sell, price range, who buys it]
My writing style: see the 3 examples below. Match the tone, sentence length and words I use. No hype, no exclamation marks in every line.

Write the [abandoned checkout / welcome series / post-purchase / win-back] emails.
For each email give me:
- 3 subject line options under 50 characters
- preview text (one line)
- the body, max 120 words, with ONE button and its label
- when it should send (time after the trigger)

Rules:
- Only use facts I gave you. If you need a fact (shipping time, return policy, discount), write [ASK ME] instead of inventing it.
- No fake urgency, no countdowns, no "only 2 left" unless I say it is true.
- [discount: none / 10% off with WELCOME10 in email 3]

My example texts:
[paste 2-3 of your own emails or product descriptions]

The [ASK ME] line matters most. Without it, an assistant happily invents a “free 30-day returns” policy you do not have. Then do one pass yourself: read each email out loud, check every price, discount and link, and send yourself a test.

Want more prompts for the campaign side? See ChatGPT prompts for marketing campaign ideas. And if replies to these emails pile up in your inbox, these customer support prompts help you answer them faster.

A simple plan for your first week

• Day 1: turn on abandoned checkout with the template text. Send yourself a test by starting a checkout with your own email.
• Day 2: rewrite that email with the prompt above, in your voice.
• Day 3: add the welcome series and check your signup form actually feeds it.
• Day 4: add post-purchase thank you.
• Day 5: add abandoned cart with the “started checkout” filter, then win-back.

After that, leave it alone for a few weeks. Check per flow: how many people entered, how many emails went out, how many orders followed. Change one thing at a time (a subject line, a delay), never everything at once, or you will not know what helped.

Stay legal and out of the spam folder

This is not legal advice, but these basics come straight from the regulators and mailbox providers.

• US (CAN-SPAM): marketing emails need an honest subject line, your valid postal address, and a clear way to opt out. Opt-outs must be honored within 10 business days (FTC compliance guide).
• UK: you may email existing customers about similar products without fresh consent only if you collected their details during a sale and gave them a simple way to opt out then and in every email (the “soft opt-in”). New prospects need consent (ICO). EU countries have similar consent rules, so check yours.
• Who gets what: Shopify automations go only to customers subscribed to marketing by default. For abandoned checkout emails you can switch the recipients to all customers (Shopify Help Center). Check your local rules before you flip that switch.
• Gmail: if you send 5,000 or more messages a day to Gmail addresses, Google requires email authentication, an unsubscribe option that works straight from the inbox on marketing mail, plus a visible unsubscribe link in the message, and a spam rate below 0.3% (Gmail sender guidelines). Most small shops are below that, but the same habits keep you out of spam at any size.

Mistakes that make ecommerce email automation backfire

• No exit filter: the customer pays and still gets “you left something behind” twice. Always stop the flow on purchase.
• Two flows fighting: cart and checkout emails, or two welcome series, landing in the same inbox on the same day.
• A discount in every email: people learn to leave carts on purpose and wait for the discount.
• Unchecked AI copy: invented policies, wrong prices, a product name spelled two ways.
• Set and forget forever: a flow that mentions last year’s product or a closed shipping option. Put a reminder in your calendar to reread every flow each quarter.

Most of these come from the same root: nobody sent themselves a test. Do that for every flow before you switch it on.

When you outgrow the templates

The built-in flows cover most small shops. When you want something custom, for example “tag VIP customers after their third order and email them personally,” Shopify points you to Shopify Flow (Shopify Help Center). For work outside your store, like a follow-up after a wholesale inquiry, a tool such as Zapier works, no programming needed. Start with automating follow-up emails with no programming, or see what the Zapier free plan can already do. For email automation ideas beyond the shop, from inbox sorting to meeting recaps, read these 8 email automation examples.

The same AI that drafts your flows can also help with the pages those emails link to. Here is how to use AI to write product descriptions that stay accurate and sound like your shop.

FAQ

How many emails should an abandoned cart flow have?

Start with the number of emails in your tool’s template. Add more only when the report shows the later emails still bring orders.

Do I need a paid tool for ecommerce email automation?

Not to start. On Shopify, the built-in automations come with 10,000 free emails a month, and abandoned checkout emails do not count toward that. Klaviyo and Mailchimp have their own plans, so check their current pricing pages before you switch.

Can AI send the emails for me?

The sending is done by your email tool, not the AI. The AI writes the copy once, you check it, and the automation sends it every time someone triggers it. That split keeps a person in control of what goes out.

Will customers notice the emails are automated?

Only if they read like a template. Write them in your own voice, sign them with a real name, and let replies reach a real inbox. Then an automated email reads like a note from the shop owner, because it is one.

Get one hands-on AI workflow every week.

Want to turn more of your shop’s busywork into automations like these? Start free on the RobotsHelp Launchpad.

Sources

• Creating and managing marketing automations in Shopify Messaging (Shopify Help Center)
• Shopify Messaging email pricing (Shopify Help Center)
• Automatically generating email subject lines and body text (Shopify Help Center)
• How to create an abandoned cart flow (Klaviyo Help Center)
• How to create an abandoned Added to Cart flow for Shopify (Klaviyo Help Center)
• Create an abandoned cart marketing automation flow (Mailchimp Help)
• Cart abandonment rate statistics (Baymard Institute)
• CAN-SPAM Act: A Compliance Guide for Business (FTC)
• Electronic mail marketing (ICO)
• Email sender guidelines (Gmail Help)

You know what the sheet needs to do. Pull the account manager in next to each order, total the North region for the quarter, flag the big deals. You just do not know the formula, and the last forum thread you opened was from 2014 and used functions your Excel does not even show.

Here is the short answer. Describe your sheet to an AI assistant (the sheet names, the column letters, what is in each column, and your Excel version), say exactly what result you want in which cell, and ask for the formula plus a one-line explanation. Then test it on three rows where you already know the answer before you fill it down. ChatGPT, Claude and Gemini all do this well in a normal chat. If you have Copilot in Excel or Gemini in Google Sheets, you can ask right inside the sheet.

Below is the prompt that gets a working formula on the first try, four real examples you can copy, and the five-minute check that stops a wrong formula from ending up in a report.

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Why the AI gives you a wrong formula (and how to stop it)

Most bad formulas from AI are not the AI being dumb. They come from a vague question. “Write a VLOOKUP for my customer list” leaves the assistant guessing your sheet names, your columns, whether you want an exact match and what should happen when a name is missing. It fills those gaps with assumptions, and one wrong assumption gives you a formula that looks fine and returns the wrong number.

Give it four things and the guessing stops:

• The layout. Sheet names, column letters and headers, where the data starts (row 2 if row 1 holds headers).
• The result. What should appear, in which cell, for one example row. “In F2, the account manager for the customer in B2.”
• The edge cases. What to show when there is no match, a blank cell or a zero.
• Your version. Excel 365, Excel 2019 or Google Sheets. This matters: Microsoft notes that XLOOKUP is not available in Excel 2016 and Excel 2019, so a modern formula can break on an older install (Microsoft Support).

The copy-paste prompt for any Excel formula

Paste this into ChatGPT, Claude or Gemini and fill in the brackets. It works for one-off formulas and for the ones you will fill down a whole column.

I need an Excel formula. I use [Excel 365 / Excel 2019 / Google Sheets].

My data:
Sheet "[name]": row 1 = headers, data starts in row 2.
Column A = [header] ([what it holds, e.g. text, dates, amounts in euros])
Column B = [header] ([...])
(add every column the formula needs)

What I want:
In cell [F2], show [the result] for that row.
Example: for row 2 I expect [the answer you know is right].
If there is no match or the cell is empty, show [blank / 0 / "Not found"].

Give me:
1. The formula for [F2], ready to fill down.
2. One plain sentence per part explaining what it does.
3. Anything in my data that could make it fail (text stored as numbers, extra spaces, merged cells).

The line “for row 2 I expect” is the one people skip, and it does the most work. It gives the assistant a target to check its own answer against, and it gives you a test you can run in ten seconds.

Four formulas people ask AI for most, with working examples

Picture a simple sales sheet. On the sheet Orders: column A Order ID, B Customer, C Region, D Order date, E Amount. On a second sheet Customers: column A Customer, B Account manager. These are the formulas a good prompt gets you.

1. Look up a value from another sheet (XLOOKUP)

Prompt: “In F2 on Orders, show the account manager for the customer in B2, taken from the Customers sheet. Show Not found if the customer is missing.”

=XLOOKUP(B2,Customers!A:A,Customers!B:B,"Not found")

XLOOKUP searches column A of Customers for the name in B2 and returns the matching value from column B. The fourth part is what shows when there is no match; without it you get #N/A (Microsoft Support: XLOOKUP). On Excel 2019 or older, ask for the INDEX and MATCH version instead:

=IFERROR(INDEX(Customers!B:B,MATCH(B2,Customers!A:A,0)),"Not found")

2. Total with conditions (SUMIFS)

Prompt: “Total the Amount column for region North with an order date in the first quarter of 2026.”

=SUMIFS(E:E,C:C,"North",D:D,">="&DATE(2026,1,1),D:D,"<"&DATE(2026,4,1))

SUMIFS adds up column E only where every condition is true: the region is North, the date is on or after 1 January and before 1 April (Microsoft Support: SUMIFS). Using “before 1 April” instead of “up to 31 March” means an order logged on 31 March with a time on it still counts.

3. Flag rows with a rule (IF)

Prompt: “In G2, show Large if the amount in E2 is 5,000 or more, otherwise Standard.”

=IF(E2>=5000,"Large","Standard")

Simple, but this is where AI saves the most time once the rules pile up (“Large over 5,000, Medium over 1,000, flag anything from the West region in red”). Describe the rules in plain words, in order, and let it build the nesting.

4. Count days since a date

Prompt: “In H2, show how many days have passed since the order date in D2.”

=TODAY()-D2

If the result shows as a date instead of a number, the cell has a date format. Set it to Number. That is exactly the kind of small snag worth asking the assistant about, in the same chat.

Check the formula before you trust it

AI formulas fail quietly. They rarely throw an error; they return a plausible number that is wrong. Microsoft says the same about its own assistant: Copilot can generate formulas that are inaccurate, so you need to review and verify them (Copilot in Excel FAQ). This five-minute check catches almost all of it:

1. Test three rows by hand. Pick rows where you know the answer: a normal one, one at an edge (a missing customer, the last day of the quarter), and one with a blank. If all three match, fill it down.
2. Cross-check totals with a filter. For a SUMIFS, filter the sheet on the same conditions and look at the sum in the status bar. Same number? Good.
3. Step through it. In Excel, Formulas > Formula Auditing > Evaluate Formula shows each part being calculated, which makes a wrong range easy to spot (Microsoft Support).
4. Ask for the explanation, then read it. If the explanation says “column C” and your region is in column D, you found the bug before it found you.

When the formula breaks: let the AI fix it

Paste the formula, the exact error and one example row. Do not just say “it doesn’t work”.

This formula in F2 returns #N/A:
=XLOOKUP(B2,Customers!A:A,Customers!B:B)
B2 contains "Jansen BV". On the Customers sheet, A14 also shows "Jansen BV".
Why does it fail, and what is the fixed formula?

The usual causes are boring and very fixable. For #N/A, Microsoft lists the main ones: the value really is not in the lookup list, or the two cells hold different data types, such as a number stored as text on one side (Microsoft Support: correct a #N/A error). Invisible extra spaces at the end of a name cause the same thing; the assistant will often suggest wrapping the lookup in TRIM.

Explain a formula you inherited

The other big use: a colleague left, and their workbook is full of formulas three lines long. Paste one in and ask:

Explain this Excel formula step by step, in plain English, for someone who knows basic Excel.
Then tell me what would make it return a wrong result.
[paste the formula]
Column A holds [...], column B holds [...].

The second question is the useful one. It tells you where the old sheet is fragile before you build next month’s report on it. Copilot in Excel can do the same from inside the cell: select it and ask Copilot to explain the formula (Microsoft Support: Copilot in Excel).

Chat assistant or the AI inside your spreadsheet?

Both write formulas. The difference is what they can see and what you need to pay for.

• A chat assistant (ChatGPT, Claude, Gemini) works with any spreadsheet and any version, including the free plans. It only knows what you describe, so the prompt above matters. If you are new to these tools, start with our ChatGPT tutorial for beginners or the Claude tutorial for beginners.
• Copilot in Excel sees your actual columns, suggests formula columns and explains existing formulas. It needs a Microsoft 365 plan that includes Copilot, and Microsoft says it works on files saved to OneDrive or SharePoint with AutoSave on, with your data set up as a table or a clean range (Copilot in Excel FAQ).
• Gemini in Google Sheets lets you type = in a cell and press Ctrl + Alt + G (Cmd + Ctrl + G on a Mac) to describe the formula you want, and offers a Fix button on cells that show an error. It requires an eligible Google Workspace or Google AI plan (Google Docs Editors Help). Our Gemini tutorial for beginners covers the basics.

If you have the built-in option, use it for formulas on the sheet in front of you. Keep the chat assistant for planning a whole workbook, or when you are on a version or plan without it.

Keep company data out of the chat

A formula never needs your real customer names or revenue. Send the headers and two or three made-up rows with the same shape. The formula works the same on the real data.

If you do paste real data into ChatGPT on a personal Free, Plus or Pro plan, know that sharing data for model training is on by default there, and you can switch off “Improve the model for everyone” under Settings > Data controls. OpenAI says content from Business, Enterprise and Edu workspaces is not used for training by default (OpenAI Help Center: data controls). Your company’s own AI policy comes first either way.

Where this goes next

Once writing formulas stops being the bottleneck, the next step is asking AI what the numbers actually say. Our guide on how to use ChatGPT to analyze a spreadsheet for work picks up right there. And if your sheet is fed by copying numbers out of emails or invoices every week, that part can be automated too: see the n8n workflow for automatic invoice processing.

FAQ

Can ChatGPT write Excel formulas for free?

Yes. Writing and explaining formulas is plain text work, and the free plans of ChatGPT, Claude and Gemini handle it. You only need a paid plan for the in-sheet assistants like Copilot in Excel or Gemini in Sheets.

Does the same formula work in Google Sheets?

Often, but not always. Common functions like SUMIFS, IF and XLOOKUP exist in both, while some functions and date handling differ. Say which one you use in the prompt and you get the right version.

Why does the AI formula work on row 2 but not further down?

Usually a reference that should stay fixed moves when you fill down. Ask the assistant: “Which references in this formula need $ signs so it fills down correctly?”

Is it cheating to use AI for formulas?

No more than looking it up in a forum. The difference is speed. Read the explanation each time and you will find yourself writing the simple ones without help after a few weeks.

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Want to go from one formula to a whole week of saved hours? Start free on the RobotsHelp Launchpad.

Sources

• XLOOKUP function (Microsoft Support)
• SUMIFS function (Microsoft Support)
• How to correct a #N/A error (Microsoft Support)
• Get data insights with Copilot in Excel (Microsoft Support)
• Frequently asked questions about Copilot in Excel (Microsoft Support)
• Collaborate with Gemini in Google Sheets (Google Docs Editors Help)
• Data controls in ChatGPT (OpenAI Help Center)

You have a hunch. A new service, a new customer group, maybe a new country. Before you spend money on it, you want to know if the market is real, who else is already there, and what customers complain about. And you’d like that answer this week, not after a consultant’s invoice.

Here’s the short answer. To use AI for market research, turn your hunch into one decision question, let a deep research tool (ChatGPT deep research, Gemini Deep Research, Claude Research or Perplexity Research) read the web and write a cited report, then add what customers say in their own words, check every number against its source, and squeeze it all into a one-page brief. The AI does hours of reading in minutes. You do the judging, and you still talk to a few real customers.

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What AI is good at in market research, and where it fails

AI research tools are very good at the boring half of desk research: finding pages, reading them, comparing them and writing it up with links. OpenAI describes its deep research tool as “agentic”: it plans the search, evaluates sources, refines its queries and then writes a report with citations (OpenAI Academy).

It is not a crystal ball. OpenAI itself writes that deep research “can sometimes hallucinate facts” or make incorrect inferences, and may struggle to tell authoritative information from rumors (OpenAI, Introducing deep research). So treat every report as a well-read first draft. Useful. Not proof.

And it can’t do the one thing that matters most: tell you whether your future customers will pay you. That still comes from conversations, a test offer, or a small ad budget.

How to use AI for market research in 5 steps

Step 1: Turn your hunch into one decision question (10 minutes)

“Research the coaching market” gets you a generic essay. A decision question gets you something you can act on. Write down three things before you open any tool:

• The decision: launch it or not, which customer group first, what price range.
• The scope: country or region, type of customer, time frame (for example the last two years).
• The output you want: a table of competitors, a list of customer problems, a short recommendation.

Bad: “Tell me about the bookkeeping market.”
Good: “Should I offer a fixed-price monthly bookkeeping package to freelance designers in the Netherlands, and at roughly what price do competitors sell something similar?”

Step 2: Let a deep research tool do the reading (5 to 30 minutes, mostly waiting)

Normal chat answers from what the model already knows plus a quick search. A deep research mode runs many searches that build on each other and hands you a longer, cited report. All four big assistants have one now:

• ChatGPT deep research: pick Deep research from the + tools menu. ChatGPT proposes a research plan you can edit, you can limit which websites it uses (Sites > Manage sites), and you can download the report as Markdown, Word or PDF (OpenAI Help Center). OpenAI says a run may take 5 to 30 minutes.
• Gemini Deep Research: choose Deep Research in the Gemini text box, check the plan (click Edit plan to change it), then Start research. Google Search is a source by default and you can add Gmail, Drive or uploaded files. Google says a report usually takes about 5 to 10 minutes (Gemini Apps Help).
• Claude Research: on a paid Claude plan, click + and then Research, with web search turned on. Claude runs several searches that build on each other and can also look in connected tools like Google Docs (Claude Help Center).
• Perplexity Research: select Research in the mode selector of the search box. Free users get limited access, Pro gets more, and Perplexity says most tasks finish in under 3 minutes. You can export the report to PDF or a document (Perplexity Help Center).

Not sure which one you already have, or which one fits the rest of your work? Our ChatGPT vs Claude vs Perplexity comparison walks through that. Then paste this prompt in and fill the brackets:

I'm deciding: [your decision question].
Market: [country/region], customers: [who exactly], time frame: [e.g. last 2 years].

Write a report for a busy owner, max 2 pages, with:
1. The 5 to 8 most relevant competitors or alternatives, in a table:
   name, what they sell, who it's for, price if public, source link.
2. The main customer problems and buying reasons you can find,
   with a link for each one.
3. Signs of demand: growing or shrinking, and the evidence.
4. Risks and reasons NOT to do this.
5. Three questions I should ask real customers before deciding.

Rules: link a source for every number. If you can't find a
number, write "not found" instead of estimating. Mark anything
that is your own inference with [INFERENCE].

That last block of rules matters more than the rest. It makes the gaps visible instead of letting the AI paper over them.

When the plan appears, read it before you press start. If it wanders into a topic you don’t care about, edit it out. Two minutes there saves you a report full of the wrong thing.

How to use Perplexity AI for market research

Perplexity is handy when you want quick, source-heavy answers to lots of small questions, because every answer shows its sources up front. A good rhythm: run one Research query for the big picture, then use normal searches for follow-ups like “What does [competitor] charge for [service]?” or “Which [industry] forums discuss [problem]?” Open the source behind every price before you copy it into your notes.

Step 3: Map the competitors yourself, with AI as your assistant (20 minutes)

The report gives you names. Now go one level deeper on the three or four that matter most. Open their websites, copy the text of their pricing and “about” pages, and paste it into ChatGPT or Claude with:

Here is the text from the pricing and about pages of [competitor 1],
[competitor 2] and [competitor 3].
Make a table: target customer, main promise, price and what's included,
what they DON'T offer. Only use the text I pasted. If something
isn't in the text, write "not stated".
Then name one gap none of them covers well.

Because you pasted the source yourself, the table is built on what’s really on their sites today, not on what a model remembers from last year.

Step 4: Hear the customer in their own words (20 minutes)

Competitor pages tell you what sellers promise. Reviews, forum threads and support questions tell you what buyers actually feel. Collect 30 to 100 real comments: public reviews of competitors, threads from industry forums or Reddit, or your own customer emails and survey answers. Then ask:

Below are customer comments about [type of product/service].
Group them into the 5 most common complaints and the 5 most common
reasons people buy. For each group: how many comments fit it, and
2 short quotes in the customer's exact words.
Don't add anything that isn't in the comments.

Those exact quotes are gold later, for your offer, your landing page and your ads. If you have a big survey export, our guide to analyzing a spreadsheet with ChatGPT shows how to handle the file, and for long reports there’s summarizing long documents with ChatGPT.

Before you paste anything from your own customers, check what your company allows. Client emails and survey answers with names in them are personal data. Strip the names, or use the business plan your workplace has approved.

No survey answers to work with yet? Our guide on how to use AI to create a survey helps you write a short one that people actually finish. Once the answers are in, here is how to use AI to analyze survey data without losing what people actually said.

Step 5: Check demand and every number (15 minutes)

This is the step most people skip, and it’s the one that keeps you from building a plan on a made-up statistic.

• Click every source behind a number. Does the page really say that? Is it from this year or from 2019? Is it about your country? If the source is missing or says something else, the number goes.
• Be careful with market-size figures. Big “the market is worth X billion” numbers are often from paid reports the AI can’t read, quoted second-hand. Ask for the method instead: “Estimate how many [customers] exist in [region], show your calculation, and link a source for each input.” A rough count you can check beats a big number you can’t.
• Check search demand with Google Trends. Compare your main term with a couple of alternatives over the same time range and location (Trends Help). Remember the numbers are relative, scaled from 0 to 100, and Google says Trends is not a scientific poll, so use it as one data point among others (Google Trends FAQ).

Turn it into a one-page brief you can decide on

A 15-page report you never reread is not research. It’s homework. Paste your checked notes back into the chat and ask:

From my notes below, write a one-page decision brief:
- The decision in one line
- What we know (only checked facts, with links)
- What we still don't know
- My 3 options, with the main risk of each
- What I would test first, in under 2 weeks and with a small budget
Plain language. No buzzwords.

Need to present it to a partner or your team? Our guide on how to use AI to make a presentation takes that brief to slides.

Before you pick one of those 3 options, it helps to see them side by side. Our guide to a SWOT analysis with AI shows how to sort your checked notes into strengths, weaknesses, opportunities and threats, and turn them into a short list of moves.

Ready to turn that research into a full plan for a lender, a partner or yourself? Here is how to use AI to write a business plan, section by section.

Market research vs market analysis: same workflow?

Mostly, yes. Market research is collecting the facts: who the competitors are, what customers want, how big the demand is. Market analysis is what you do with them: comparing options, spotting a gap, choosing a price. Steps 2 to 4 above are the research. Step 5 and the brief are the analysis. AI helps with both, but the analysis is where your own judgment has to lead, because you know your costs, your skills and your clients.

One thing this guide is not about: stock market research. Picking investments is a different job with different risks, and we don’t cover it here.

An example: from hunch to test in one afternoon

Say you’re a freelance bookkeeper and you keep getting questions from designers. Here’s how the five steps could look:

1. Question: “Should I offer a fixed-price monthly package for freelance designers in my country, and at what price?”
2. Deep research: one report on who already serves freelancers this way, their public prices and what freelancers say about bookkeeping.
3. Competitors: you paste the pricing pages of the three closest offers and get a clean table, plus one gap (for example, nobody explains the package in plain language for creative people).
4. Customer voice: 50 forum comments from freelancers about bookkeeping, grouped into complaints like “I never know what I’ll pay” and “I don’t understand what my bookkeeper sends me”.
5. Check: you click every price, drop the two that don’t match the source, and look at search interest in Google Trends.

The brief ends with a small test: message ten designers you know, offer the package at the price range you found, and see how many say yes. That test is the real market research. AI just got you there with a lot less reading.

Not sure which assistant to run these steps in? Our ChatGPT vs Gemini for research comparison runs the same research task through both so you can pick one.

FAQ

Can I use ChatGPT for market research for free?

You can do a lot in a normal free chat: brainstorm questions, group customer comments you paste in, build competitor tables from page text. Deep research usage varies by plan and ChatGPT shows your remaining tasks in a counter (OpenAI Help Center). Perplexity also gives free users limited access to its Research mode.

Is AI market research accurate?

It’s as accurate as the sources it finds and your check afterwards. The tools give you citations precisely so you can verify them. Use the “not found” and [INFERENCE] rules from the prompt, and click before you trust.

Which AI tool is best for market research?

The one you already pay for is usually good enough. If you live in Google Workspace, Gemini can pull in your Gmail and Drive. If you want fast answers with sources visible up front, Perplexity is quick. ChatGPT and Claude are both strong for the report and the follow-up analysis. The workflow matters more than the brand.

Can AI replace talking to customers?

No. It can tell you what people say in public. It can’t tell you whether the people you can reach will pay your price. Use the AI work to ask much better questions in those conversations.

Your next step

Pick the one business question that has been sitting in your head the longest, write it as a decision, and run it through the Step 2 prompt today. You’ll know in half an hour whether it deserves a real test. For more workflows like this, from campaign ideas with ChatGPT to small automations, start with the free Launchpad on our home page.

The meeting is tomorrow at ten. You have the notes, the numbers and a rough idea of what you want to say. What you don’t have is the two hours it takes to turn all of that into slides that don’t look thrown together.

Here’s the short answer. To use AI to make a presentation, don’t start by asking for “a deck about X”. Give ChatGPT, Claude or Gemini your real material first (notes, a report, a spreadsheet), ask for a storyline of 6 to 10 slides with one message per slide, fix that outline, and only then let a slide tool build it: Copilot in PowerPoint, Gemini in Google Slides, Canva, or Claude, which can hand you a finished .pptx file. Then you check every number and cut the text by half. The AI does the structure and the first draft. You keep the judgment.

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Why “make me a presentation” gives you a generic deck

If you type one line into an AI slide maker, it has nothing to work with except the topic. So it fills the gaps with safe, general statements and stock photos. The slides look tidy and say very little.

The fix is simple. A presentation is a story first and a design second. Get the story right in plain text, where it’s fast to change, and the design step becomes almost automatic. That’s also how the AI tools themselves are built: Canva’s AI shows you an outline you can edit before it generates anything (Canva Help Center), and Copilot in PowerPoint may ask who the audience is and how long the deck should be before it starts (Microsoft Support).

How to use AI to make a presentation in 5 steps

Step 1: Feed it your real material (5 minutes)

Collect what you already have: meeting notes, the report the deck is based on, a few rows of data, last quarter’s deck. Paste it in or upload the file. Then add three facts the AI can’t guess:

• Who is watching: your manager, a client, the whole team.
• What you want them to do afterwards: approve a budget, pick an option, stop worrying about the project.
• How long you have: 10 minutes is a very different deck than 45.

That last line in your prompt does more for the result than any clever wording.

Step 2: Ask for the storyline, not the slides

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

I need to give a [10]-minute presentation to [my manager and two team leads].
After it, I want them to [approve moving the launch by two weeks].
Below are my notes and data.

Make an outline of 6 to 10 slides. For each slide give:
1. A headline that states the point as a full sentence (not a topic label)
2. Max 3 short bullets
3. One suggestion for a chart, table or image, if it helps
4. 2 to 3 sentences of speaker notes

Use only facts from my notes. If something is missing, write
"[CHECK: ...]" instead of making it up. End with a list of
questions my audience is likely to ask.

[paste notes / data here]

Two things in that prompt matter most. “Headline as a full sentence” turns “Q3 numbers” into “Q3 sales are up, but returns doubled”, which is what people remember. And the “[CHECK]” line stops the AI from quietly inventing a figure to fill a gap.

Step 3: Fix the outline before anything gets designed

Read the headlines only, top to bottom. Do they tell the story on their own? If you’d skip a slide while presenting, delete it. If a slide makes two points, split it. Ask the AI for changes in plain words: “merge slides 3 and 4”, “the client doesn’t care about our internal process, cut it”, “start with the decision we need”.

This is the step most people skip, and it’s the one that makes the deck sound like you.

Step 4: Turn the outline into slides with the tool you already use

Pick the route that matches where you work. You don’t need all of them.

• PowerPoint with Copilot: start a new presentation (or open your company template first), open Copilot and paste your outline as the prompt. Copilot builds the deck with your template, and on work licences it can also start from a Word or PDF file (Copilot in PowerPoint FAQ). It needs a Microsoft 365 plan that includes Copilot.
• Claude: in the same chat, say “Now turn this outline into a PowerPoint file.” Claude can create .pptx files you download or save to Google Drive, and that works on the Free plan too (Claude Help Center). If you don’t name a file format, it may build the deck as an artifact instead, so say “PowerPoint file” out loud.
• Google Slides with Gemini: open your presentation, click Ask Gemini and describe the slide. You can point it at a Drive file with @, for example “Create a slide that summarizes @Project notes”. It generates one slide at a time in your current theme (Google Docs Editors Help), so paste one outline slide per prompt. It needs an eligible Workspace or Google AI plan.
• Canva: on the homepage choose Canva AI, then Design, then Presentation, paste your outline as the prompt, adjust the outline Canva shows you and click Generate presentation (Canva Help Center). Good when looks matter more than your company template. It counts toward your monthly Canva AI usage.

If you’re new to the chat tools themselves, our Claude tutorial for beginners and Gemini tutorial for beginners get you set up in a few minutes.

Step 5: Do the human pass (10 minutes)

Now open the deck and go through it slide by slide:

• Check every number against your source. Search the deck for “[CHECK” and fill those in yourself.
• Cut text. Microsoft’s own advice is short bullets of one line each and no font smaller than 18 pt, because you want people listening to you, not reading the screen (Microsoft Support). AI drafts almost always carry too many words.
• Swap generic images for your own screenshot, chart or photo where you can. A real screenshot of your dashboard beats a stock photo of a handshake.
• Read the speaker notes out loud once. Change anything you’d never actually say.

Which AI tool is best for presentations?

Honestly, the one you already pay for and work in. The quality of the story comes from steps 1 to 3, and every tool above does those well enough. The difference is in the last mile:

• Your company has a strict template: PowerPoint with Copilot, or the Claude for PowerPoint add-in on paid Claude plans, which builds slides from your existing template’s layouts (Claude docs).
• Your team lives in Google Workspace: Gemini in Slides, because it can pull straight from your Drive files.
• You want it to look designed with little effort: Canva.
• You want a file fast and you’re on a free plan: Claude’s file creation, then open the .pptx in PowerPoint, Keynote or Google Slides.

How to use AI to make a PowerPoint presentation for free

You can do the whole thing without a paid plan. Use the free version of ChatGPT, Claude or Gemini for steps 1 to 3 (the storyline is the valuable part anyway). Then either ask Claude for the .pptx file, or copy the headlines and bullets into a blank PowerPoint or Google Slides deck yourself. With a clean outline, building 8 simple slides by hand is a short job, and you’ll know every line on them.

Free plans have usage limits, so do your outline in one focused chat instead of ten scattered ones.

An example: from messy project notes to an 8-slide update

Say you run a small website project and you need a 10-minute update for a client. Your input is a page of notes from the last three status calls plus a short list of open tasks.

With the prompt above, a typical outline comes back like this: one slide with the decision you need (“We recommend moving launch to 14 March”), one with what’s done, one with what’s blocking, one with two options and their trade-offs, one with the new timeline, and a closing slide with the next step. Plus speaker notes and a list of likely client questions, such as “Does this change the budget?”

The bits where your notes were vague come back as “[CHECK: confirm hosting migration date]”. Those are exactly the places where an AI would otherwise have guessed. You fill them in, cut the bullets, and paste the outline into your tool of choice. The structure is done before you open a slide.

If your source is a long report rather than notes, summarize it first with ChatGPT for long documents. If it’s a pile of meeting notes, turn them into a report and build the deck from that.

A deck usually needs a clean logo on the title slide too. If you do not have one, see the best AI tool for logo design for options that fit a work budget.

Mistakes that make AI slides look like AI slides

• Letting it invent numbers. If a figure isn’t in your source, it shouldn’t be on a slide. Your audience will ask where it came from.
• Topic headlines. “Market overview” says nothing. “Two competitors cut prices this quarter” says something.
• Too many slides. AI is happy to give you 20. For a 10-minute slot, 6 to 10 is plenty.
• Pasting confidential data into a personal account. Use the work account or tool your company has approved for client and financial data, or strip names and figures first.
• Presenting a deck you haven’t rehearsed. The slides were fast. Spend part of the time you saved saying them out loud once.

Need to show a process on a slide, like an approval flow or a customer journey? Skip drawing boxes by hand. Our guide on how to make a flowchart with AI shows how to get a clean diagram you can export as an image and drop into your deck.

Questions people ask

Can Claude make a PowerPoint presentation?

Yes. Ask it to create a PowerPoint file and it gives you a .pptx to download or save to Google Drive. On paid plans there’s also an add-in that works inside PowerPoint itself.

Can AI make a Google Slides presentation?

Gemini in Google Slides generates and edits slides inside your deck, one slide per prompt, if your Workspace or Google AI plan includes it. Without it, you can open a Claude-made .pptx in Google Slides or paste an AI outline in yourself.

How long does it take?

Depends on your material. Most of the time goes into steps 3 and 5, fixing the story and checking facts, and that’s the time well spent. The typing and layout are what the AI takes off your plate.

Is it OK to use an AI-made deck at work?

Treat it like a draft from a fast junior colleague: useful, but you sign off on it. Check your company’s policy on which AI tools may see work data, check every fact, and make sure the opinions on the slides are yours.

Your next step

Take the next presentation on your calendar, paste your notes into the prompt above, and only look at the headlines it gives you. If those tell the story, you are most of the way there. For more workflows like this, from using Claude for everyday work to small automations, start with the free Launchpad on our home page.

You’re the one everybody asks. How do I issue a refund, where’s the client onboarding checklist, what’s the login for the supplier portal. It all lives in your head, and you know you should write it down. You just never get two quiet hours to do it.

Here’s the short answer. You can use AI to write SOPs in about 20 minutes of your own time for a simple process: do the task once while you talk it through out loud, turn that recording into a transcript, paste the transcript into ChatGPT or Claude with a fixed SOP prompt, then have someone else follow the draft and fix what trips them up. The AI does the formatting and the tidying. You still supply the knowledge and the final check.

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Why AI is good at SOPs (and where it isn’t)

A standard operating procedure is mostly structure: a purpose, who it’s for, what you need, numbered steps, what can go wrong. The US Environmental Protection Agency’s guide on writing SOPs puts the style in one line: write them “in a concise, step-by-step, easy-to-read format”, in active voice and present tense, and keep them short (EPA QA/G-6, Guidance for Preparing SOPs).

That is exactly the kind of rewriting ChatGPT and Claude do well. Give them a rambling explanation and they hand back clean numbered steps.

What they can’t do is know your process. If you ask “write an SOP for processing refunds” with nothing else, you get a generic document that sounds right and matches nobody’s real work. The same EPA guide says SOPs should be written by the people who actually do the work. So the trick is simple: you bring the raw knowledge, AI brings the shape.

Step 1: Capture the process while you do it (5 minutes)

Don’t sit down to “write”. Do the task for real and narrate it, like you’re showing a new colleague over your shoulder. Say what you click, why you click it, and what you check before moving on. Mention the annoying bits too: “if the invoice is in dollars, stop and ask finance first.”

Ways to capture it:

• Phone voice memo. On an iPhone 12 or later, the Voice Memos app transcribes speech for you, and you can copy the whole transcript with one tap (Apple Support: Voice Memos transcription).
• Screen recording with your voice. Many video call and screen recording tools can produce a transcript. Grab that text.
• Screenshots plus notes. For a click-heavy process, take a screenshot at each key screen and type one line per screenshot.
• An existing mess. An old email where you explained it to someone, a Slack thread, a half-finished doc. That’s raw material too.

Messy is fine. “Uhm, then you go to, no wait, first you check the order number” is perfect input. Cleaning that up is the AI’s job.

Step 2: Turn the transcript into an SOP with one prompt

Paste your transcript into ChatGPT or Claude together with this prompt. Fill in the brackets.

You are helping me write a standard operating procedure (SOP).
Below is a transcript of me doing the task "[task name]" and explaining it out loud.

Turn it into an SOP with these sections:
1. Purpose (one sentence)
2. Who does this and when (trigger)
3. What you need before starting (access, tools, files)
4. Steps: numbered, one action per step, active voice, present tense
5. Checks: what to verify before the task counts as done
6. Common problems and what to do
7. Who to ask if stuck

Rules:
- Use ONLY what is in the transcript. Do not invent steps, tools or names.
- If something is unclear or missing, do not guess. List it under
  "Open questions for the author" at the end.
- Write for someone with basic computer skills who has never done this task.
- Keep it short. No intro, no conclusion.

Transcript:
[paste here]

Two lines in that prompt do most of the work. “Use only what is in the transcript” stops the model from filling gaps with plausible fiction. “Open questions for the author” turns those gaps into a short to-do list for you, instead of hidden mistakes for your colleague.

If your transcript is long, ChatGPT and Claude both handle it fine. For really long material, like a 40-page manual you want to split into several SOPs, see our guide to getting ChatGPT to summarize long documents for work.

Step 3: Answer the open questions, then fix the draft

Read the “open questions” list first. Typical ones: “Which folder are signed contracts saved in?” or “What is the refund limit before approval is needed?” Answer them in the same chat in plain words and ask for an updated version.

Then read the steps yourself, once, slowly. Look for three things:

• Merged steps. “Log in and create the invoice” is two steps. Split them.
• Missing decisions. Every “if this, then that” you said out loud should be in there.
• Invented details. A button name or menu path you never mentioned. Delete it or correct it.

Step 4: Let someone else test it

This is the step people skip, and it’s the one that makes an SOP actually work. The EPA guidance recommends that draft SOPs be tested by someone other than the writer before they’re finalized. Hand the draft to a colleague, a freelancer, or your future self in three months, and watch where they get stuck. Every question they ask is a missing line.

A good test: could someone with basic computer skills follow it alone, without phoning you? If yes, it’s done.

Some processes are easier to follow as a picture, especially when there are a few yes or no decisions in them. You can turn the same steps into a diagram: here is how to make a flowchart with AI from a process you have already written down.

Step 5: Keep your SOPs in one place AI can reuse

Once you have five or ten SOPs, two things help.

One home. A shared folder or wiki with one SOP per process and a clear name (“SOP: Issue a customer refund”). Add a “last checked” date at the top. Processes change, and an outdated SOP is worse than none.

One AI workspace. In Claude you can create a Project, upload your SOP template and a couple of finished SOPs as project knowledge, and add instructions like “always use this format”. Every new chat in that project then follows your house style without re-pasting the prompt. Projects are available on free Claude accounts too, with a limit of five projects (Claude Help Center: What are projects?). ChatGPT has a similar Projects feature. New to either tool? Our Claude tutorial for beginners covers the setup in your first 30 minutes.

An example: from voice memo to SOP

Say you run a small agency and onboarding a new client is always “ask Sanne, she knows”. Sanne records herself once while setting up a real client: creating the folder, sending the welcome email, adding them to the invoicing tool, booking the kickoff call. That’s maybe six minutes of talking.

Run through the prompt above, that turns into a one-page SOP: a dozen or so numbered steps, a “before you start” list (access to the drive, the email template, the calendar link) and three open questions Sanne answers in two minutes. The next time a client signs, a junior colleague does it from the SOP. And once the steps are written down and stable, you can see which ones a tool could do for you. That’s how you get from “documented” to “automated”, like in our guide to automating client onboarding with Make.com.

Hiring rather than signing a client? The SOPs you write this way are exactly what a new starter needs in their first weeks. Our guide on how to use AI for employee onboarding shows how to fold them into a 30-60-90 day plan and a new-hire FAQ.

AI SOP generators: do you need one?

Search for “AI SOP generator” and you’ll find dedicated tools, some of which record your screen and build a step-by-step guide with screenshots automatically. They’re handy for click-heavy software processes where a picture of every screen saves explaining.

For most small teams, though, ChatGPT or Claude plus the prompt above is enough. You already pay for it or use the free tier, there’s nothing new to learn, and the SOP lands in whatever doc tool you already use. Try the free route on three processes first. If you find yourself pasting screenshots all day, then a dedicated tool is worth a look.

Quick answers

Can ChatGPT write SOPs on its own?

It can write a generic SOP template from a one-line request. It can’t write your SOP, because it doesn’t know your systems, limits and exceptions. Give it a transcript or notes of the real process and it does a good job.

Is it safe to paste internal processes into AI?

Leave out passwords, personal customer data and anything confidential. Use placeholders like [CUSTOMER NAME] or [ADMIN LOGIN]. If your company has a policy on AI tools, follow it, and check whether your plan uses chats for training in the tool’s data settings.

What’s the best format for an SOP?

Short and scannable: purpose, trigger, what you need, numbered steps with one action each, checks, problems, contact. For a process with many branches, a simple flow chart helps, and the EPA guide recommends one too. You can ask the AI to draft the chart as a list of decisions first.

How often should I update SOPs?

Whenever the process changes, and otherwise on a fixed rhythm. The EPA guide suggests a periodic review, for example every one to two years. For fast-moving software processes, a quick check every few months is more realistic.

Can I turn meeting notes into an SOP?

Yes, if the meeting was someone explaining a process. Use the same prompt. For regular meeting notes, our guide on using ChatGPT to summarize meeting notes is the better fit.

Hiring someone to take over a process? The same interview approach works for the role itself: see how to use AI to write a job description.

Turning a bigger piece of work into steps, owners and dates instead of a single procedure? See how to use AI to create a project plan.

Interviewing for that role next? See how to use AI to create interview questions that check whether a candidate can really do the work, with a simple scoring guide.

Need to announce a new process in a team meeting? Turn the SOP into spoken talking points with how to write a speech with AI, so the rollout still sounds like you.

Your next step

Pick the one task people ask you about most this week. Record yourself doing it, run the prompt, answer the open questions, and hand it to someone to test. That’s one less interruption, every week, from now on. If you’d like a new hands-on AI workflow for your work every week, join the free Launchpad on our home page, or open robotshelp.me to see what’s inside.

It’s the last week of the month. There are 30 supplier invoices spread across your inbox, two are phone photos of paper bills, one is in German, and you’re typing totals into a spreadsheet again. You’ve seen “AI invoice processing” everywhere, but the tool lists all look the same.

Here’s the short answer. AI invoice processing software reads an invoice (a PDF, a scan or a photo), pulls out the supplier, invoice number, dates, VAT and total, often the line items too, and sends that to your accounting software or a sheet so you only check and approve. For most small businesses the right pick is a capture app that plugs straight into the accounting software you already use. Build your own in n8n only when you need custom routing, and use a raw document AI API only if a developer is involved. One check comes before all of that: if your suppliers are switching to structured e-invoices, part of the problem disappears on its own.

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What AI invoice processing software actually does

Strip the marketing away and every tool in this category does the same three jobs.

1. Capture. Invoices come in by email forward, upload, phone photo or a shared inbox.
2. Extract. An AI model reads the document and fills fixed fields. Microsoft’s invoice model, for example, returns fields like vendor name, invoice ID, invoice date, due date, subtotal, total tax, amount due, IBAN and line items, and it handles phone photos, scans and digital PDFs (Microsoft Learn: invoice model). Google’s Invoice Parser can pull up to 46 fields, including VAT amounts and supplier tax IDs (Google Cloud: Document AI processors).
3. Hand off. The fields go into Xero, QuickBooks, your ERP or a Google Sheet, ideally with the original PDF attached, so you approve instead of type.

The difference between tools is almost never “can it read an invoice”. They all can. The difference is where the data ends up, how you correct mistakes, and what it costs per document once you’re past the free trial.

The four kinds of tools (and who each one is for)

1. Bookkeeping capture apps

These sit next to your accounting software. You snap or forward an invoice, the app reads it and creates the bill for you. Hubdoc, for example, extracts supplier names, amounts, invoice numbers and due dates and creates transactions in Xero and QuickBooks Online with the source document attached (Hubdoc). Dext does the same job and accepts documents by mobile, email, WhatsApp or desktop (Dext).

Good for: freelancers and small teams that already use a cloud accounting package. Less good for: anything outside bookkeeping, like routing an invoice to a project manager for sign-off.

2. Accounts payable automation platforms

One step up. These add approval flows, purchase order matching, supplier onboarding and payment runs. Nanonets is one example; it positions itself around AI agents for accounts payable and reconciliation (Nanonets).

Good for: a finance team handling hundreds of invoices a month with several approvers. Less good for: a one-person business. You’ll pay for features you never open.

3. Build your own workflow (n8n, Make, Zapier plus an AI model)

You connect your inbox to an AI model and a sheet yourself. n8n’s Extract From File node pulls the text out of a PDF (n8n docs), a model turns it into fields, and the result lands wherever you want. We walk through that exact build in our n8n workflow for automatic invoice processing.

Good for: people who want invoices routed by project, client or cost centre, or posted into a tool no capture app supports. Less good for: anyone who doesn’t want to maintain a workflow when a supplier changes their layout.

4. Document AI APIs

Microsoft Document Intelligence and Google Document AI are cloud services you call from your own code. You get raw fields plus a confidence score per field, and you build everything around it.

Good for: a company with a developer and a high, steady volume. Less good for: everyone else. There’s no inbox, no approval screen and no accounting sync out of the box.

How to choose: six questions that decide it

1. Where must the data end up? If the answer is Xero or QuickBooks, start with a capture app that syncs with it natively. Everything else is extra plumbing.
2. How many invoices a month? Twenty is a capture app or a small DIY flow. Several hundred with approvals is AP automation territory.
3. Do you need line items or just totals? Totals and VAT are enough for bookkeeping. Line items matter when you rebill clients or match purchase orders, and that is where tools differ most.
4. Which languages and countries? Check the vendor’s supported language list against your real suppliers. Microsoft, for instance, publishes its list and even extracts the Dutch KVK number as its own field (invoice model schema).
5. Where is the data stored? Invoices carry names, addresses and bank details. If you’re in the EU, ask where documents are processed and kept, and whether the vendor signs a data processing agreement.
6. What does a correction cost you? No tool is right every time. The best one for you is the one where fixing a wrong field takes two seconds, not a support ticket.

Test it on your own invoices before you pay

Vendors quote accuracy figures (Dext’s homepage says over 99%). Treat any number like that as their test, not yours. The only test that counts is your own messy pile. It takes about 30 minutes:

Run the same 10 through two tools and the choice usually makes itself. If you want a free baseline first, you can ask Claude to pull the same fields from a PDF into a table; here’s how to extract data from a PDF with Claude. It won’t replace a tool for monthly volume, but it shows you what “good extraction” looks like on your own documents.

Check this first: are your invoices becoming e-invoices?

A lot of invoice software exists to read PDFs. Structured e-invoices don’t need reading: the data already arrives as fields. And in parts of Europe they’re becoming the rule.

• Belgium: since 1 January 2026, invoices between Belgian VAT-registered businesses must be structured e-invoices; a PDF by email no longer counts (Belgian government e-invoice FAQ).
• Germany: since 1 January 2025, businesses must be able to receive e-invoices (German Federal Ministry of Finance FAQ).
• The wider EU: the Commission tracks each country’s rules on its eInvoicing pages (European Commission: eInvoicing).

What that means for your choice: pick software that can both receive structured e-invoices and read the PDFs and photos that will keep coming from smaller or foreign suppliers. Paying only for PDF reading could leave you with half a solution in a year or two.

What it won’t do for you

• Decide what gets paid. Keep approval with a person, at least for anything above an amount you pick.
• Spot every odd invoice. A changed bank account on a familiar supplier’s invoice should always get a phone call to a number you already have, whatever the software says.
• Fix a messy inbox. If invoices arrive in five places, set up one forwarding address first. That alone saves more time than most features.

Choosing a tool for contracts instead of invoices? The same test-it-on-your-own-files approach works there too: see our guide to AI contract review software.

Quick answers

Can I just use ChatGPT or Claude to process invoices?

For a handful a month, yes: upload the PDF and ask for the fields in a table. For a steady flow you want something that runs on its own, which is why people end up with a capture app or a workflow like the ones in our email automation examples.

What does it cost?

Capture apps usually charge a monthly plan with a document limit; APIs charge per page. Prices change often, so compare the vendors’ own pricing pages against your real monthly volume, not their headline plan.

Do I need to code?

No for capture apps and AP platforms. No for n8n, Make or Zapier either, though you’ll spend an afternoon setting it up. If you’ve never built a workflow, start with our n8n tutorial for beginners.

Your next step

Pick the kind of tool that matches where your data must end up, run the 10-invoice test on two options, and keep a person on the approve button. That’s the whole decision. If you’d like a new hands-on AI workflow for your work every week, join the free Launchpad on our home page.

You have seen the photos: a little Mac mini on a shelf, running an AI agent all day. Now you are on Apple’s order page, looking at 16GB, 24GB, 32GB and a Pro chip, and wondering how much of that you actually need. Fair question. The price gap between the cheapest and the most expensive Mac mini is bigger than the cost of a year of most AI subscriptions.

Here is the short answer. If your OpenClaw agent uses a cloud model like Claude, ChatGPT or Gemini, the base Mac mini is enough: Apple M6, 16GB memory, 256GB storage, $899 in Apple’s US store. OpenClaw itself only needs a recent Node version, and the OpenClaw Mac app needs macOS 26.2 or later. The heavy thinking happens on the AI company’s servers, not on your desk. Pay for more memory only if you want to run the AI model on the Mac mini itself. Then memory is the one spec that decides everything, and 32GB is where it starts to feel usable. This guide to OpenClaw Mac mini specs shows you which box fits which job, so you don’t overspend or come up short.

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What OpenClaw itself needs (it’s less than you think)

OpenClaw’s own install docs keep the list short: Node 24.16 or newer, or Node 26.1 or newer, and the installer sets up Node for you if it’s missing (OpenClaw docs: Install). There is no minimum chip and no minimum memory in that list.

Two macOS details matter before you buy, especially a used Mac mini:

• The OpenClaw Mac app (the menu bar app with the dashboard and chat window) needs macOS 26.2 (Tahoe) or later.
• The Terminal install runs on Node, whose Mac builds are made for macOS 13.5 or later. Older versions may still run it, but they are not supported (OpenClaw docs: macOS app).

Why so little? The part of OpenClaw that runs on your Mac mini is the Gateway. It keeps your settings, your chats and your connections to apps like Telegram or Slack, and it passes each job to the AI model. With a cloud model, the model does the hard work somewhere else and sends back the answer. Your Mac mini is mostly waiting, routing and running a browser now and then.

The current Mac mini line-up, in one table

Apple sells two chips in the Mac mini right now: the M6 and the M5 Pro. These are the numbers from Apple’s own spec page (Apple: Mac mini technical specifications). Prices are from Apple’s US store on 26 October 2026 and change by country.

Every model has Ethernet (2.5Gb, 10Gb as an option), Wi-Fi 7 and the same small 12.7 cm square box. The M5 Pro adds Thunderbolt 5 ports. For an OpenClaw box, the rows that matter are memory and storage. The rest is nice to have.

One thing to know before you order: you choose the memory when you buy. Apple only offers it as an option at checkout, so there is no adding more later. Storage you can always extend with an external drive. Memory you can’t.

Memory: the one OpenClaw Mac mini spec that decides it

Everything comes down to one question: where does the AI model run?

Cloud model (Claude, ChatGPT, Gemini): 16GB is fine

This is how most people start, and it’s what OpenClaw’s own setup steers you to first. The Mac mini runs the Gateway, maybe a browser for web tasks, and a few connected apps. 16GB covers that comfortably. If you also plan to run Docker, several browser sessions at once, or a second user account that stays logged in, 24GB gives you breathing room.

The real cost of a cloud setup is not the hardware. It’s the AI plan or API usage behind it. If that part is new to you, our guide on what happens when you hit ChatGPT and Claude usage limits shows where the caps are.

Local model (the AI runs on the Mac mini): memory first, then speed

Running the model yourself means nothing leaves your desk, and there is no per-message bill. The trade is hardware. On Apple silicon the chip and the graphics share one pool of memory, so the whole model has to fit in it, next to macOS and OpenClaw.

OpenClaw is honest about this. Its managed local setup checks your memory, graphics memory and free disk before it downloads anything. The smallest model recipe has an 8GiB memory floor, larger ones need more, and the docs add that these floors “do not guarantee fit or speed” (OpenClaw docs: Local models). The same page warns that a model that answers a short test prompt can still fail a real agent task, because the agent sends a long prompt with tools and history.

A simple rule of thumb: take the model’s download size, then leave plenty of room on top for macOS, OpenClaw and the conversation. Here are real download sizes from the Ollama library, a popular way to run models locally:

• Llama 3.1 8B: 4.9GB (Ollama: llama3.1)
• Qwen3 14B: 9.3GB, and Qwen3 32B: 20GB (Ollama: qwen3)
• gpt-oss 20B: 14GB (Ollama: gpt-oss)
• Llama 3.1 70B: 43GB

Read that list next to the memory options and the picture gets clear. A 16GB Mac mini can hold a small 8B model, but that leaves little room for anything else. 32GB fits the 14B and 20B class with space to work. A 70B model at 43GB is only realistic on an M5 Pro with 64GB. Small local models are fine for simple jobs like sorting or short summaries. For an agent that plans, browses and uses tools, most people still get better results from a cloud model.

Speed is the second half. When a local model writes its answer, it reads through its memory again and again, so memory bandwidth matters more than the number of CPU cores. That is why the M5 Pro’s 307GB/s, about double the base M6, is the real reason to pay for it. Hands-on buyer guides for OpenClaw land on the same advice: buy the Pro for local models, not for cloud ones (Bitdoze: Best Mac mini for OpenClaw).

Storage: 256GB or 512GB?

For a cloud-model agent, 256GB is enough. OpenClaw, its logs and a browser profile are small next to that.

Go for 512GB or more when any of these apply:

• You run local models. Each one is several GB, and most people try three or four before they settle.
• You want a macOS virtual machine to keep the agent apart from your own Mac. OpenClaw’s docs count about 60GB of free disk per VM (OpenClaw docs: macOS VMs).
• You use Docker or keep big project folders on the machine.

If you are on a budget, the base 256GB plus an external SSD over Thunderbolt is a fair middle way. Keep the operating system and OpenClaw on the internal drive, and store model files and archives on the external one.

Which Mac mini should you buy? Three honest picks

This is what I tell friends who ask me which one to get.

1. “My agent uses Claude or ChatGPT, and I just want it always on.”
Base Mac mini M6, 16GB, 256GB. Don’t let anyone talk you into more. You get an agent that answers your messages day and night, reads your inbox for you and runs your weekly jobs, and the box itself is the cheapest part of the setup.

2. “I’ll run browser jobs, maybe Docker, and I want to try a small local model.”
Mac mini M6 with 24GB or 32GB and 512GB. This is the safe middle. It gives OpenClaw room to run next to other tools, and a small model for simple background work fits.

3. “The model has to run here. Client data stays in the office.”
Mac mini M5 Pro with 48GB or 64GB and at least 1TB. This is where local models start to do real agent work at a speed you’ll accept. Before you spend this much, test the exact model you plan to use on a real task from your week, as OpenClaw’s own docs advise.

Already have an older Mac mini? Try it first. An Apple silicon Mac mini with an M1 or newer can run the OpenClaw Gateway with a cloud model. Check which macOS it runs: below macOS 26.2 you use the Terminal install instead of the menu bar app. Our guide to installing OpenClaw on a Mac covers both routes.

Before you buy: a one-week test that costs nothing

The cheapest way to pick the right specs is to find out what you actually use. Install OpenClaw on the Mac or Windows laptop you already have (here is the Windows guide), connect a cloud model, and give it three real jobs for a week. A morning summary of your inbox, a weekly report, a research task.

At the end of that week you know two things. Whether you want it running when your laptop is closed (then a Mac mini makes sense), and whether a cloud model does the job (then the base model is all you need). Not sure OpenClaw is the right agent at all? Compare it first in OpenClaw vs Claude Code and OpenClaw vs Claude Cowork.

Once the Mac mini is on your desk, follow our OpenClaw Mac mini setup guide: a separate user account for the agent, no sleep, automatic login and remote access, step by step.

Quick answers

Is a Mac mini with 8GB enough for OpenClaw?

For a cloud model, it can work, because OpenClaw lists no memory minimum and the model runs elsewhere. It gets tight once a browser and other apps are open, and it leaves no room for a local model. The current Mac mini starts at 16GB anyway.

Do I need the M5 Pro for OpenClaw?

Only if you want to run large AI models on the machine itself. For a cloud-model agent, the extra power mostly sits idle.

Can I add more memory later?

No. You choose the memory when you order, so decide based on whether you’ll want local models in the next few years. Storage you can extend with an external drive.

Mac mini or a cheap server (VPS)?

OpenClaw’s docs list both as good options. A VPS is cheaper to start with. A Mac mini gives you iMessage, a home internet address that websites block less often for browser jobs, and hardware you own (OpenClaw docs: macOS VMs).

Do I need a monitor?

Only for the first setup. After that you reach the Mac mini from your laptop or phone. The setup guide linked above shows how.

Pick the specs for the jobs you have today, not for the agent you might build in three years. If you want help building those jobs step by step, the free RobotsHelp Launchpad on our home page is where we start.

Get one hands-on AI workflow every week.

Sources

• Install: system requirements (OpenClaw docs)
• macOS app: requirements (OpenClaw docs)
• Local models: hardware floor (OpenClaw docs)
• macOS VMs: always-on options and disk space (OpenClaw docs)
• Mac mini technical specifications (Apple)
• Buy Mac mini: prices and configurations (Apple US store)
• Model download sizes (Ollama library)
• Best Mac mini for OpenClaw (Bitdoze)

Your inbox is in Gmail, your files are in Drive, and everyone keeps telling you to “just use Gemini”. You open it, type “help me with my work”, and get three friendly paragraphs that help with nothing. Sound familiar?

Here is the short answer. To start with Gemini, go to gemini.google.com and sign in with your Google account. Then give it one real task from today, with four things in the message: who you are, what you need, the background, and what the result should look like. Add your own file with Add files, or type @ to let it read your Gmail or Drive. Correct the first answer in the same chat instead of starting over. When a task comes back every week, save your instructions as a skill. That is the whole beginner loop. This Gemini tutorial for beginners walks you through it step by step, with prompts you can copy.

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Step 1: Sign in with the right Google account

Gemini is Google’s AI assistant. It runs in any normal browser at gemini.google.com, and there is a Gemini app for phones too. You can try a few things without signing in, but file uploads, saved chats and the connection to Gmail and Drive only work once you are signed in (Gemini Apps Help: Use Gemini Apps).

Which account you pick matters more than with most AI tools, because Gemini can read your Google data:

• Personal Google account (Gmail address): works straight away and is free to start.
• Work account on Google Workspace: works only if your company’s edition includes it and your admin allows it. You also have to be 18 or over (Gemini Apps Help: What you need to sign in).

My advice: if your employer gives you Gemini on your work account, use that one for work. Your files are already there, and the company has decided what is allowed. If not, learn on your personal account with practice material, and keep client documents out of it until you have checked the privacy setting in Step 6.

Step 2: Write your first work prompt (four parts)

A prompt is simply your message. Google’s own guide for writing instructions names four parts: the persona (what role to play), the task (what to do), the context (the background) and the format (how the result should look). You do not need all four every time, but a few of them make a big difference (Gemini Apps Help: Tips for writing instructions).

Here it is with a real task. Swap in your own details:

You are an experienced office manager who writes short, friendly emails.

Task: write an email to the whole team about the office move.

Context: we move to the new building on Monday 9 November.
Everyone packs their own desk on Friday 6 November before 3pm.
Boxes and labels are in the kitchen from Wednesday.
IT moves the screens; people only take laptops home.

Format: under 150 words, a clear subject line,
the three dates as a short list, one friendly line at the end.

Now compare that with “write an email about the move”. The long version gives Gemini the dates, the rules and the tone. The short one makes it guess all three, and guesses read like a template you would never send.

Once the draft is close, a second prompt can polish it. The ones that work best are in make this email sound more professional, and they work the same in Gemini.

Step 3: Give Gemini your own material

This is where it gets useful. An answer from your document beats an answer from general knowledge every time. There are two ways in.

Upload a file

Click Add files in the text box, then Upload files, and pick a document, spreadsheet or image. According to Google’s help page you can add up to 10 files in one prompt, each up to 100 MB (videos can be bigger), and you can ask Gemini to make a chart from an uploaded spreadsheet (Gemini Apps Help: Upload and analyze files).

A good first test: upload a report you already know well, so you can judge the answer.

Read the attached report.
1. Give me the 5 most important points in plain English, one line each.
2. For each point, say which section it comes from.
3. List anything that needs a decision from me, with the deadline if there is one.

Asking where each point comes from is the best beginner habit. You can check it in seconds, and you quickly learn how far you can trust it on your kind of documents.

Let it read Gmail and Drive with @

This is the part that makes Gemini different from ChatGPT or Claude for a Google user. Type @ in the text box and pick Gmail or Drive. The first time, Gemini asks your permission to connect. After that it can find and summarize emails and documents for you (Gemini Apps Help: Connect Google Workspace).

Try one of these:

@Gmail Summarize the emails from Sarah about the Henderson project
from the last two weeks. What did we agree, and what is still open?

@Drive Find my notes from the Q3 planning meeting and list
every action item with the person who owns it.

Three things Google’s help page warns about, and they match what beginners run into:

• Use keywords, not links. Don’t paste the URL of an email or document. Describe it with words from the content, like a name or project.
• Check the sources. Gemini can pick an older email when a newer one exists. Open the sources listed under the answer before you act on it.
• It can’t connect? Keep Activity has to be on, and in Gmail the setting “Smart features in other Google products” has to be switched on. On a work account, your admin decides.

For long PDFs and reports, our guides go deeper. They use Claude and ChatGPT, but the prompts carry over to Gemini: summarize long documents for work and summarize meeting notes.

Step 4: Correct it, don’t start over

The first answer is a draft. Most beginners either take it as it is, or open a new chat and start again from zero. Both throw away the work Gemini already did.

Reply in the same chat, short and direct, the way you would to a colleague:

• “Shorter. Cut the second paragraph.”
• “Warmer. This client has been with us for five years.”
• “The deadline is the 14th, not the 12th. Fix it everywhere.”
• “Put this in a table: task, owner, deadline.”

Gemini can also turn a finished answer into a file. Ask “put this in a Google Doc” or “make this a spreadsheet”, and it creates a Doc, Sheet, PDF or Word file you can download or save to Drive (Gemini Apps Help: Generate files from your chats). That saves the copy and paste at the end.

Step 5: Save repeat work as a skill (not a Gem)

If you paste the same background into Gemini every Monday, save it once. Until now that was called a Gem. Google is replacing Gems with skills: on personal accounts Gems go away from November 2026 and are turned into skills automatically, and work accounts follow in 2027 (Gemini Apps Help: The move from Gems to skills). So if you are starting now, start with skills.

A skill is a set of saved instructions. You call it by typing / and its name in any chat, and Gemini can also use it by itself when your request fits. Skills work without a paid plan, but you need to be 18 or over and have Keep Activity on (Gemini Apps Help: Create and manage skills).

The easiest way to make one is to ask for it in a chat:

Create a skill called weekly-client-update based on these instructions:

When I paste my rough notes, turn them into a client update with
three headings: Done this week / Next week / Needs your input.
Max 150 words. Plain English, no jargon.
Use the client's first name, never "Dear client".
If my notes mention a risk or a delay, put it first under "Needs your input".

Next Friday you type /weekly-client-update, paste your notes, and the update comes back in your format. You can find, edit or switch off your skills under Customize, then Skills, in the sidebar. If your updates come from a Google Sheet, our guide to Gemini for automated status updates shows the whole Friday routine.

Step 6: Check one privacy setting before real work

On a personal account, while Keep Activity is on, Google can use your chats to improve its services, and some chats are read by human reviewers (Gemini Apps Privacy Hub). The catch for beginners: the Gmail and Drive connection and skills need Keep Activity on.

So here is the simple rule I use:

• For something sensitive: use a Temporary chat (next to New chat). It doesn’t show up in your history, but it also can’t use skills or connected apps (Gemini Apps Help).
• For everyday work: leave names, salaries and client numbers out of the prompt, or use the work account your employer has approved.

Five beginner tasks to try in Gemini this week

It sticks when you use it on Tuesday’s real work, not on test questions. Pick two:

1. Catch up after a day off. “@Gmail What came in from my manager and my clients since Friday? List what needs an answer from me.”
2. The email you keep postponing. Paste the email you got, say in one sentence what you want to answer, ask for a reply under 100 words.
3. Meeting notes into actions. Upload or paste your notes and ask for decisions, action items with owners, and open questions.
4. A spreadsheet you don’t understand. Upload it and ask: “What does this sheet track, what stands out, and make one chart of the most important trend.”
5. Prep for a call. “@Drive Find the last proposal we sent to [client]. Give me the three points they are most likely to ask about.”

Free or paid: what a beginner actually needs

The free plan is enough for everything in this tutorial: chat, file uploads, the @ connection to your Google apps and skills. Google lists the paid plans (Google AI Plus, Pro and Ultra) with higher usage limits, stronger models and Gemini built into Gmail and Docs themselves (Gemini subscriptions).

Pay only after you have hit the free limits several times on real work. Not because a new model launched. If you are torn between paid plans, read ChatGPT vs Gemini Pro or Claude vs Gemini Pro first.

Once you are comfortable with text, try images too: how to use Gemini to edit photos walks through prompts that work.

Beginner mistakes that cost the most time

• Vague first prompts. “Help me with this report” gets you a lecture. Say who it is for and what you need from it.
• Trusting a summary of the wrong email. With @Gmail, always open the source once. It takes five seconds.
• A new chat for every correction. Stay in the same chat, so Gemini keeps your context.
• Building ten skills on day one. Make one for the task you really repeat. Add the next one when you catch yourself retyping again.
• Sending without reading. Google itself says Gemini can make mistakes. You are still the one who hits send.

Most of your work lives in email? Here is how to use Gemini in Gmail to summarize long threads and draft replies right inside your inbox.

Gemini, ChatGPT or Claude for a beginner?

If your day already runs on Gmail, Docs and Drive, Gemini is the easiest place to start, because your material is one @ away. If your files come from everywhere, ChatGPT or Claude may feel smoother. The basics are the same in all three, so nothing you learn here is wasted. Our ChatGPT tutorial for beginners and Claude tutorial for beginners follow the same steps, so you can compare for yourself.

If your main job is learning from notes and PDFs, not inbox triage, start with Claude vs Gemini for studying before you lock in a daily tool.

Pick one tool, use it for the same three jobs every week for a month, and the hours come back. If you want a place to build that habit step by step, the free RobotsHelp Launchpad on our home page is where we start.

If you are enrolled in higher education, you may also qualify to get Gemini for students free for a year instead of starting on the paid plan.

Once those six steps feel natural, you can run the same habits inside Gmail, Docs, Sheets and Meet. Our guide on how to use Gemini for work shows a desk system for the full workday, including prompts you can save and reuse.

FAQ

Is Gemini free?

Yes, there is a free plan that covers chat, file uploads and the connection to Gmail and Drive. Paid Google AI plans add higher limits and stronger models (Gemini subscriptions).

Can I use Gemini with my work Google account?

Only if your company’s Google Workspace edition includes it and your admin allows it. If it doesn’t work, ask your IT team before you move work files to a personal account.

What happened to Gems?

Google is turning Gems into skills. On personal accounts that starts in November 2026, and your existing Gems are converted automatically. New users can simply start with skills.

Can Gemini read my emails?

Only when you connect it. Type @ and pick Gmail, and Gemini asks for your permission first. You can disconnect it again in the Connected Apps settings.

Get one hands-on AI workflow every week.

Sources

• Use Gemini Apps (Gemini Apps Help)
• What you need to sign in to Gemini Apps (Gemini Apps Help)
• Tips for writing Gem instructions (Gemini Apps Help)
• Upload and analyze files in Gemini Apps (Gemini Apps Help)
• Connect the Google Workspace app to Gemini Apps (Gemini Apps Help)
• Create and manage skills (Gemini Apps Help)
• About the transition from Gems to skills (Gemini Apps Help)
• Gemini Apps Privacy Hub (Google)
• Gemini subscriptions (Google)