AI Prompts for Business: What to Ask, by Function

Most "100 AI prompts for business" lists fail for the same reason: a prompt without your context is just a topic sentence. "Write a marketing email" produces a generic marketing email no matter how cleverly it's worded, because the model doesn't know your product, your customer, or what you've already tried.

The prompts below are written the way business prompts actually need to be written — with the context slot made explicit, so you can see what you have to supply. What the model brings is speed and structure. What you bring is the specifics, and there's no prompt that substitutes for them.

• The rule: every useful business prompt contains a task, your real context, a constraint, and a format. Drop any one and the output gets generic.
• The highest-value uses are drafting, restructuring, and summarizing — work where a fast first version saves real time and you'll review it anyway.
• The lowest-value uses are anything where being confidently wrong costs money: legal interpretation, tax treatment, real financial figures, and decisions about people.
• The thing that compounds: saving the prompts that worked. Most people rewrite the same prompt monthly from memory.

The shape of a business prompt that works

Before the function-specific ones, the pattern they all follow:

A worked example. The weak version:

Write a sales email for our product.

The version that produces something usable:

Draft a follow-up email to a hospital IT director who demoed our scheduling software three weeks ago and went quiet. We're a 12-person company; our differentiator is that we integrate with their existing EHR rather than replacing it. Their stated concern was implementation time. Under 120 words, no exclamation marks, one clear ask. Don't claim savings figures.

Same task. The second one works because four slots are filled, not because the wording is clever. Anthropic's prompt engineering guidance puts being clear and direct at the top of its list for exactly this reason, ahead of every advanced technique.

If you're supplying the same context repeatedly, stop pasting it — that's what a master prompt is for, and it's the single biggest time saving available here.

Prompts by function

Sales and customer-facing work

• Objection prep. "Here are the three objections we heard in our last five lost deals: [paste]. For each, draft a two-sentence response that acknowledges the concern honestly rather than deflecting, and flag which ones point at a real product gap."
• Call-notes triage. "Turn these raw notes into: the customer's stated problem, their unstated concern, the agreed next step and owner, and anything I promised. Quote their exact words for the problem."
• Pre-call research structuring. "Here's a prospect's public job description and their careers page: [paste]. What can I reasonably infer about their priorities this quarter, and what would be a guess?"

That last constraint — separating inference from guess — is worth adding to most analysis prompts. It's a direct way to make a model mark its own uncertainty rather than present everything at the same confidence.

Marketing and content

• Positioning critique. "Here's our homepage copy: [paste]. Argue the case that a first-time visitor still wouldn't know what we sell. Be specific about which sentence loses them."
• Variant generation. "Ten subject lines for this email: [paste]. Five direct and specific, five curiosity-led. No emoji, no 'unlock', no questions."
• Repurposing. "Turn this case study into a 200-word LinkedIn post that leads with the customer's problem, not our product. Keep every number exactly as written."

One hard rule for marketing output: AI-drafted claims are regulated like any other claim. The FTC's Operation AI Comply sweep targeted companies making unsupported claims about what AI could do for customers. If a draft produces a statistic or a results claim you can't source, cut it — the model didn't verify it and neither did you.

Finance and operations

Use AI for structure here, not for numbers.

• Model scaffolding. "List the line items a subscription business needs to forecast 12 months of cash flow, and the assumption behind each. Don't invent values — leave them blank."
• Process documentation. "I'll describe how we currently handle refunds: [describe]. Write it as a numbered SOP, and list every step where the process depends on one specific person knowing something undocumented."
• Contract and policy reading. "Summarize this vendor agreement's termination, renewal, and data-handling clauses. Quote the exact wording for each, and list anything that seems unusual for this kind of agreement."

That last one is a summary prompt, not a legal opinion. It tells you where to look; a lawyer tells you what it means.

HR and internal communication

Lowest-risk uses are drafting and restructuring; highest-risk is anything that evaluates a person.

• Job description tightening. "Rewrite this job description to describe what the person will actually do in their first 90 days. Cut every adjective that would appear in any company's version."
• Difficult message drafting. "Draft an announcement that we're pausing a project the team has worked on for four months. Direct, no corporate euphemism, and it should acknowledge the work without over-promising about what happens next."
• Meeting synthesis. "From these notes, list decisions made, decisions deferred and why, and open questions with owners."

Don't use AI to screen, rank, or evaluate candidates or employees. Beyond the fairness problem, automated decisions about people carry legal exposure that varies by jurisdiction. NIST's AI Risk Management Framework is a sensible free structure for deciding which of your use cases need governance and which genuinely don't.

The three failure modes to plan for

Confident invention. Models state false things fluently, and business contexts are exactly where that's expensive. Two habits from Anthropic's guidance on reducing hallucinations help: explicitly permit "I don't know," and ask for a source per claim so you can check it. Any number that reaches a document with your name on it needs to be traceable.

Confidential data. Before pasting customer data, contracts, or financials into a consumer chat tool, know where it's stored and whether it's used for training. This is a settings question and an account-tier question, and it's worth answering once for your whole team rather than per person.

Average output. A model trained on everything produces the average of everything. For anything competitive — positioning, a pitch, a point of view — AI is good for a first draft to react against and bad as a final answer. Use it to get to the version you disagree with faster.

Keep the prompts that work

The real cost isn't writing prompts. It's rewriting the same prompt every month because nobody saved it.

A shared document of working prompts, each with a note on what it's for, outperforms any list you'll find online — including this one — because yours contains your context. Best ChatGPT prompts covers the patterns underneath, and if your work is technical, AI prompts for web development covers that side.

When the thing you're repeating is a whole sequence rather than a single ask, a saved prompt stops being enough. Taku is an AI-native desktop workspace for that case: you mirror an AI app or workflow someone already got working, run it on your own machine, and keep it as something you re-run rather than a chat you scroll back through. Taku is in Beta, and the Mac app is available now.

Key points

• A business prompt needs four slots filled: task, your real context, a constraint, and a format. The context is the part no prompt list can supply.
• Drafting, restructuring, and summarizing are the high-value uses. Legal interpretation, tax treatment, real figures, and decisions about people are not.
• Ask models to separate inference from guess, and to permit "I don't know" — both reduce confident invention.
• Marketing claims drafted by AI carry the same regulatory weight as any other claim, so cut anything you can't source.
• Save the prompts that worked. Rewriting them monthly from memory is where most of the time actually goes.

FAQ

What are the best AI prompts for business?

The ones containing your own context. A prompt that names your product, your customer, the specific situation, and the output format will beat any generic prompt from a list, because the generic version leaves the model to guess the details that matter.

Which business tasks should AI not be used for?

Anything where a confident error is expensive or unfair: legal and tax interpretation, financial figures presented as fact, and decisions that evaluate or rank people. Use it to summarize and structure those things, then have a qualified person decide.

Is it safe to paste company data into an AI tool?

It depends on the tool, the plan, and the settings. Check whether inputs are retained or used for training before pasting customer data, contracts, or financials, and decide it once as a policy rather than leaving each person to guess.

How do I stop AI from inventing numbers in business documents?

Tell it explicitly not to invent values and to leave unknowns blank, ask for a source with each factual claim, and give it permission to say it doesn't know. Then check anything that ends up in a document you sign.

Do I need to learn prompt engineering to use AI at work?

No. Filling in the four slots — task, context, constraint, format — covers most of the benefit. The advanced techniques matter when you're building something repeatable, not when you're drafting an email.