AI ads: how to use AI to make better ads

What people mean by AI ads

The phrase covers several different jobs, and it helps to separate them before choosing any tool. Some tools write text: headlines, primary text, scripts and email subject lines. Some generate or edit images, such as new backgrounds behind a product photo. Some assemble short videos from images and a script. Others sit in the middle and suggest concepts, which is the job Madly focuses on. A few features inside ad platforms also automate parts of delivery or asset generation, and those change over time, so check each platform's own documentation rather than relying on a blog summary, including this one.

For an ecommerce founder the useful question is not whether AI can make an ad. It plainly can. The useful question is which part of your current process is slow, expensive or stuck, and whether AI shortens that part without lowering the quality of your decisions. A founder who struggles to think of fresh angles has a different problem from one who has plenty of angles but no time to produce variations.

Where AI genuinely helps

AI is strongest wherever the work is combinatorial. If you have one product, five customer motivations and four formats, that is twenty possible ads. Drafting all of them by hand is tedious, and the tedium usually means founders ship one or two and call it a day. A model can produce rough versions of all twenty in minutes, which lets you pick the five worth polishing.

It also helps as a thinking partner. Pasting in a set of anonymised customer review themes and asking for ten different ways to frame the benefit often surfaces an angle you had stopped noticing because you were too close to the product. The same applies to objections. Asking what a sceptical buyer might worry about before purchasing is a quick way to build a list of things your ad or landing page should address.

Finally, AI is useful for adaptation. Turning a long-form description into a short caption, rewriting for a different tone, or producing a version for a different placement are mechanical tasks that a model handles well, leaving your attention for the parts that need taste.

Where AI does not help

AI does not know your numbers. It cannot tell you that your contribution margin leaves room for only a small acquisition cost, or that your repeat purchase rate makes a first order worth less than it looks. Those inputs come from you, and tools such as the break-even ROAS calculator exist to turn them into a target.

It does not know what is true about your product. Language models can write fluent and confident claims that are simply wrong, or that you cannot substantiate. In regulated categories such as supplements, skincare and finance, an invented benefit is not just embarrassing, it can breach advertising rules and platform policies. Treat every factual statement in generated copy as unverified until you have checked it against something you can point to.

It does not remove the need for a point of view. When many sellers use similar tools with similar prompts, the output converges on similar phrases. The ads that stand out tend to carry something specific that only the founder knows: a detail about how the product is made, an unusual use case, a real constraint, a customer question that arrives every week.

A five-step workflow that holds up

Step 1: Write the brief first

Before opening any AI tool, write a short brief. Name the product, the one customer you are speaking to, the problem they have, the result you can honestly promise, the proof you actually hold, and the offer. The first ad creative brief guide walks through this. A good brief is the single biggest influence on output quality, because the model can only work with what you give it.

Step 2: Generate angles, not finished ads

Ask for a spread of angles rather than polished ads. An angle is the reason someone would care: saving time, avoiding a bad outcome, feeling a certain way, belonging to a group. Aim for eight to fifteen angles, then discard the ones that are generic, untrue or off brand. Keep three to five.

Step 3: Draft variations within each angle

For each surviving angle, draft a few hooks, a body and a call to action. The ad hooks guide lists thirty hypothetical examples across angles that you can adapt, and writing ad copy with AI covers how to keep the voice human.

Step 4: Edit with a checklist

Edit every draft against a fixed checklist: Is each claim true and supportable? Does it match the landing page? Does it fit the character limits of the placement? Does it sound like your brand? The ad copy grader and ad character counter help with the mechanical checks, though neither replaces your own reading.

Step 5: Test and read the result honestly

Launch a small set of clearly different concepts and measure against profit. The AI ad creative testing guide explains how to structure that, and the ROAS calculator turns spend and revenue into a comparable number.

The AI ads cluster at a glance

This pillar guide links to a set of deeper guides. Use the table to find the one that matches your current question.

A worked example with hypothetical numbers

Imagine a small store selling refillable ceramic candles. Average order value is 42 pounds, product and shipping costs take 22 pounds, and payment fees take another 1.50. That leaves roughly 18.50 pounds of contribution per order before advertising. Break-even ROAS is the order value divided by that contribution, so 42 divided by 18.50, which is about 2.27. Any campaign returning less than that on first orders loses money, unless repeat purchases make up the difference, which is a separate assumption you should state and not hide.

Now the founder uses AI to generate twelve angles. Five are discarded as generic. Of the remaining seven, three are kept: the refill saving, the calm evening routine, and gifting. Each gets two hooks and one body, giving six ads. They launch with a modest daily budget, and after a sensible window the founder compares ROAS by concept against 2.27, not against a vague sense that one ad looks better. In this invented scenario the gifting concept clears the line and the others do not. The lesson is the process, not the outcome: AI produced the volume, the brief and the break-even maths produced the discipline.

Scope and attribution cautions

Be careful about what you conclude. Platform-reported conversions are the platform's own attribution, and different windows and methods produce different numbers. A creative that looks strong in one dashboard may look average once you compare with store revenue. The MER versus ROAS guide explains why it helps to look at both.

Also be careful about small samples. If each concept received only a handful of orders, differences between them may be noise. Avoid declaring a winner on very little data, and avoid generalising from one product or one month to your whole catalogue. Finally, any statistic you read about AI ad performance from a vendor describes that vendor's own data and context. It is not a promise about your store.

Practical guardrails for responsible use

Keep a short log of what you generated, what you changed and what you published. If a claim is ever questioned, you want to show what supports it. Do not upload customer personal data into tools without checking the tool's terms and your privacy obligations. Avoid generating realistic images of people using your product if that implies an experience that did not happen, and never present synthetic content as a real customer testimonial. Where a platform asks you to label AI-generated or altered content, follow its current policy.

Disclose sensibly. Even when no rule requires it, be careful with imagery that could mislead about size, texture, results or who is using the product. A generated lifestyle background behind a real product photograph is a very different thing from a generated person apparently endorsing it.

When to start small

If you are new to paid ads, begin with one product, one audience and three concepts. Use AI to speed up the writing and the variations, but keep the budget modest and the measurement simple. The first month ad budget guide helps size that first spend. Once you understand your own numbers, add complexity gradually. AI does not change the fundamentals of advertising: a clear offer, an honest message to the right person, and a price that leaves room for profit.

Jobs-to-tools: one end-to-end mug example

Illustrative worked example, not a measured customer result. Replace assumptions with checked facts.

Common questions

Can AI replace a designer or copywriter for a small store?

It can replace some of the first-draft work, and for a very small store that may be enough to get started. It does not replace taste, brand consistency or the judgement about what is truthful. Many founders use AI for volume and a human for final polish.

Are AI-generated ads allowed on Meta, Google and TikTok?

Platforms generally allow them, but they also publish policies on misleading content, restricted categories and, in some cases, labelling of altered or synthetic media. Policies change, so read the current advertising policies on each platform before publishing.

How many AI-generated concepts should I test at once?

Fewer than you can generate. Three to five clearly different concepts is a sensible start for a small budget, because each needs enough spend to show a meaningful difference. Generating many does not oblige you to test many.

Will AI ads perform better than ads I write myself?

There is no reliable general answer. Performance depends on the offer, the audience, the product and the execution. AI can help you test more ideas, which may improve your odds, but it does not guarantee better results.

What should I give an AI tool to get useful output?

A written brief: the product facts, the audience, the problem, the promise you can support, the proof you hold and the offer. Add examples of your brand voice and a list of phrases or claims to avoid.

Is it safe to use customer reviews as input?

Quote or paraphrase themes carefully and anonymise them. Do not present generated text as a real review, and check the privacy terms of any tool before pasting in personal data.