Should You Use Auto-Generated Creative? – Ask A PPC via @sejournal, @navahf

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.

Image from author, April 2026

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.

Three text ads: one made by a human, the others autogenerated (Image from author, April 2026) Results of three ads from a logistics company over 30 days (Image from author, April 2026)

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 use and particularly helpful for understanding how your site is being interpreted by machines and humans alike.

The Case For Using Auto-Generated Creative

The number one reason to consider auto-generated creative is simple: time savings.

At its core, auto-generated creative takes your existing assets and adapts them to meet the formatting and placement needs of different inventory. Instead of building bespoke creative for every surface, you allow the system to reassemble what you already have in ways that let you reach more people with less manual effort.

The inputs for auto-generated creative typically come from your website, your existing ads, and, in some cases, proven concepts that are broadly applicable across advertisers. You can also apply brand style guides to ensure fonts, colors, and creative (including tone of voice) are compliant with brand standards.

Image from author, April 2026

Advertisers who are able to say yes to auto-generated creative often see faster campaign ramp-up. Eligibility for more placements means more opportunities to enter auctions, and fewer bottlenecks make it easier for the system to test and learn which creative works best in which contexts.

Because auto-generated creative allows advertisers to be eligible for more placements (with Ad Rank determining the ad shown), it naturally has access to more impressions. More impressions create more opportunities to win auctions, which can translate into incremental volume that would have been difficult to capture using tightly controlled, manually built assets alone.

Auto-generated creative does not have to be all-or-nothing. There is also a hybrid approach where humans partner with AI systems. That can mean using in-platform tools from Google or Microsoft, or external AI tools, to help generate ideas, headlines, or variations that are then reviewed, approved, and manually uploaded.

Some advertisers draw a distinction between AI-assisted ideation and auto-generated creative. In practice, if you are using AI at any point to help create or shape ad messaging, there is already an element of automation in the process.

The Case Against Using Auto-Generated Creative

There are absolutely valid reasons to opt out.

The most pressing is brand compliance. If your organization requires explicit approval for every piece of creative before spend can occur, allowing systems to dynamically generate variations may simply not be permissible.

That said, many platforms provide preview tools that show examples of how creative may appear.

Image from author, April 2026

If you are willing to explore those previews and lean into tools like brand kits that enforce fonts, colors, and tone, it may be possible to secure internal approval where it previously felt impossible.

Another reason advertisers shy away from auto-generated creative is reliance on proven assets with no tolerance for variation. Sometimes budget approval is contingent on using specific creative that has already demonstrated performance, and there is no room to test alternatives.

Image from author, April 2026

It is worth noting, however, that auto-generated creative already relies heavily on your existing assets. If the primary concern is avoiding untested messaging, allowing your site content and proven ads to inform the system can help mitigate that risk.

Bonus Tip: Using Auto-Generated Creative To Understand How AI Sees You

One of the most underrated benefits of campaigns like Performance Max, Dynamic Search Ads, and other feed or keywordless-based formats is that they reveal how well platforms understand your site and landing pages.

Image from author, April 2026

If you strongly disagree with the creative shown in previews for AI Max, Performance Max, or similar formats, that is a warning sign. Running budget to those pages risks confusing users if the system’s interpretation does not align with your intended messaging.

These tools can function as diagnostic instruments, not just delivery mechanisms.

Image from author, April 2026

You can go a step further by pairing them with behavioral analysis tools like Microsoft Clarity, which shows how users actually interact with your site. When creative interpretation and user behavior do not line up, the issue is often not the ads, but the underlying content.

Another advantage of modern campaign creation tools is their built-in AI editing capabilities. Even if you never allow auto-generated creative to go live, you can still use these tools to explore tone shifts, rewrites, and messaging ideas that inform your manual creative work.

Image from author, April 2026

There are many use cases for these systems beyond automation alone. Insight generation is one of the most valuable.

Final Takeaways

At its core, the decision to lean into auto-generated creative comes down to whether your brand is allowed to test.

If the answer is yes, there is little downside to experimenting. Auto-generated creative is largely built from your existing assets, and poor results are often a signal that your landing pages or messaging need refinement anyway.

If the answer is no, whether due to brand compliance, limited testing bandwidth, or the need to lock spend behind proven creative, it is entirely reasonable to opt out.

Used thoughtfully, it can save time, unlock scale, and surface insights about how your brand is understood by machines and users alike. Used blindly, it can create risk. The goal is not blind trust, but informed experimentation.

Hope you found this helpful, and I’ll see you next month for another edition of Ask the PPC.

More Resources:

Should Advertisers Be Worried About AI In PPC? When Advertising Shifts To Prompts, What Should Advertisers Do? What Google’s 2025 Year in Review Tells Us About the Future of PPC

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Featured Image: Paulo Bobita/Search Engine Journal