Automated ad copy from AI Max is changing how campaigns are managed. Tests across ecommerce, B2B, and B2C accounts reveal where AI-generated assets boost performance-and where human oversight still outperforms automation.
AI Max’s automated asset creation promises to ease the workload for PPC teams by generating ad copy tailored to each ad group. To measure its real-world impact, a software provider partnered with three companies-spanning ecommerce, B2B, and B2C-to test how well AI-driven text customization performs compared to human-managed campaigns.
The experiment began with a careful setup. Each company enabled AI Max and its text customization feature, then established messaging restrictions to prevent the AI from producing off-brand or misleading ads. This process involved using Gemini prompts to generate both desirable and undesirable ad copy, then refining restrictions until all outputs aligned with brand guidelines. Messaging restrictions proved essential, as AI sometimes created assets promoting products or offers the companies didn’t provide.
Campaign selection was deliberate. The teams chose only campaigns without brand keywords, with monthly spends above $20,000, and at least 100 ad groups. Both highly optimized and less-attended long-tail campaigns were included, but those relying heavily on pinning or final URL expansion were excluded to isolate the effect of AI-generated assets.
Asset Oversight
Throughout the tests, companies closely monitored auto-created assets, removing those that didn’t fit their messaging before they could accumulate impressions. On average, about 19% of AI-generated assets were discarded-excluding the B2B case, which saw even more aggressive filtering due to poor fit.
Reviewing these assets required adjusting default filters in Google Ads to ensure all AI-generated ads were visible for evaluation. This hands-on oversight was crucial to maintaining brand integrity and campaign effectiveness.
Performance Across Campaign Types
In the ecommerce test, the company managed over 100,000 SKUs. Initially, AI Max and text customization appeared to drive strong results. However, deeper analysis revealed that AI-generated ads cannibalized impressions and conversions from other campaigns, leading to an overall revenue decline. The team responded by adding more targeted keywords, negative keywords, and audience lists to reduce overlap, then reran the tests. Ultimately, AI-generated assets performed well in long-tail campaigns but fell short in highly optimized ones where human-crafted copy remained superior.
The B2B lead generation test highlighted a key limitation. Without pinning, AI-generated ads attracted a surge in clicks but failed to prequalify leads, resulting in a sharp drop in conversion rates as B2C users clicked through. Despite messaging restrictions, the AI struggled to consistently target the intended B2B audience. After three weeks of poor results, the company reverted to manual pinning and asset creation, quickly restoring previous performance levels.
For B2C lead generation, the company used geographic ad copy and insertion to localize ads. While top campaigns already featured highly tailored human-written copy, long-tail campaigns relied on more generic assets. Here, AI Max’s auto-created assets delivered solid improvements, outperforming the formulaic ads in lower-priority campaigns, though still not matching the results of the most optimized human-managed campaigns.
When to Trust AI Max
AI Max can be a valuable tool for generating ad copy when time or resources are limited, especially in campaigns that don’t receive intensive manual optimization. However, for campaigns requiring precise messaging-such as those targeting specific audiences or promoting time-sensitive offers-human oversight remains essential. Regular review and strong messaging restrictions are necessary to prevent off-brand or ineffective ads from slipping through.
While AI Max offers efficiency gains, it is not yet a set-and-forget solution. Ongoing supervision and intervention are required to ensure campaign quality and brand safety. For organizations seeking to maximize automation without sacrificing results, combining AI-driven asset creation with disciplined human review is currently the most effective approach.
For a deeper look at how intentional governance and feedback loops can further improve automated paid search outcomes, see this analysis of how smart governance shapes Google Ads automation.
Google Ads, launched in 2000, remains the dominant paid search platform globally, serving millions of advertisers and generating over $200 billion in annual ad revenue for Google as of 2025. The introduction of AI Max reflects Google’s ongoing push to automate campaign management, but adoption rates vary widely depending on advertiser size, industry, and willingness to cede creative control to machine learning systems.
