It won’t surprise anyone that most advertisers are hesitant to use auto-generated creative from ad platforms. Auto-generated ads fall into the following categories:
- Customer-in-the-loop (CITL): Assets are generated based on inputs like a website URL or a user prompt. The advertiser always has a choice as to whether or not they want to include these assets in their campaigns.
- Dynamic composition: Ads are composed at serving time in different formats based on existing groups of assets, with performant winners selected and scaled (i.e., how Performance Max works). May or may not include AI-generated assets based on customer preferences.
- Auto-generated: New assets or ads are generated after a campaign is launched based on inputs like URLs, search queries, or existing videos to improve performance. These assets are not reviewed and approved by advertisers before serving, but can generally be viewed and controlled in reporting.
Even advertisers who embrace automation in bidding, targeting, and budget allocation often draw a firm line when it comes to creative.
That resistance usually comes from a few places:
- Quality concerns due to generic copy instead of product/service-specific.
- Brand compliance requirements.
- A strong desire to maintain creative ownership.
- Discomfort with the idea of ads going live without a human signing off on every variation.
Yet, auto-generated creative can sometimes perform just as well as, if not better than, human-created assets. A 2025 study found that autogenerated ads had a 19% better CTR.
These performance gains aren’t new; AI ads have been meeting or exceeding human creative as early as 2018.
That performance edge comes from two core advantages.
First, auto-generated creative is highly adaptable. It can flex across formats and placements in ways that would be time-consuming or impractical for humans to manage manually.
Second, it is bias-free in its willingness to apply the creative most likely to perform for humans searching in a profitable way, rather than the semantic syntax we think will succeed.
This article is not about declaring auto-generated creative right or wrong. There is no universal answer. Whether leaning into it makes sense will always depend on business constraints, brand rules, and personal comfort levels.
What we are going to do is walk through a practical framework you can use to decide whether auto-generated creative is worth testing for your business, and how to use platform tools to better understand how well your site and messaging are being interpreted by AI systems.
Before we get into it, an important disclosure. I am a Microsoft Advertising employee. The guidance here is intended to be platform-agnostic, but I will reference a few Microsoft-specific tools that are free to…
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