Google’s AI Ad Labels Put Marketers On Notice

Google’s AI ad labels are not just a transparency feature for users. They are becoming a compliance problem for marketers, agencies and brands that now rely on generative AI to produce campaign assets.

Google announced the change in July through its Ads and Commerce Blog, saying users can access a new “How this ad was made” section in My Ad Centre across Search, YouTube and Discover. The panel indicates whether an ad was created or edited using AI.

The company says ads made with Google’s own generative AI advertising tools can be labelled automatically. For ads created elsewhere, Google is giving advertisers a control to indicate whether generative AI was used. Depending on local requirements, the label may also appear directly on the ad creative itself.

That is where the operational headache begins. A brand may use an in-house designer, an agency, a freelance editor, a third-party AI creative platform and Google’s own ad tools in the same campaign. If nobody tracks which asset was generated, edited or only lightly touched by AI, the campaign team may not know how to label it correctly.

Google’s Advertising Policies Help page says AI regulations in the European Union, India and New York require disclosures or labels for certain AI-generated or edited ad assets. It also warns that using Google’s label setting does not guarantee legal compliance. Advertisers still need to understand their local obligations.

That warning matters. Google can provide a tool, but it will not take legal responsibility for every campaign. Brands will need internal rules for AI creative: what counts as generated, what counts as edited, who records the tool used, who approves the disclosure and what evidence is kept if a regulator asks questions later.

This fits the wider shift around AI provenance. We recently wrote about Google allowing some visible AI watermarks to be removed while keeping SynthID signals. Ad labels are another version of the same problem: people need to know when AI has shaped what they are seeing, but the mechanism has to work at scale.

For marketers, the practical issue is workflow. AI is already being used for product backgrounds, video edits, copy variations, synthetic voice, image touch-ups and localized creative. If those assets move quickly through approval systems, disclosure can easily become an afterthought.

For users, the label could make ads more transparent, but it will not solve deceptive advertising by itself. An AI-made ad can be truthful, and a human-made ad can be misleading. Google says its existing ad policies still prohibit misleading and deceptive ads whether AI is involved or not.

The bigger point is that AI advertising is moving from experimentation to regulated practice. The companies that treat labelling as a small checkbox may run into compliance and trust problems. The ones that build AI disclosure into their creative workflow now will be better prepared as more jurisdictions demand transparency.