An Indian real-estate company creates an attractive image of a future apartment using generative AI. A jewellery business places its product on an AI-generated model. A coaching company uses an artificial voice in a video advertisement.
All three businesses can technically launch these assets much faster than they could have a few years ago. But they now need to answer an important question before publishing:
Does the advertisement need to disclose that its image, video or audio was created or meaningfully edited using AI?
Google has introduced new controls to help advertisers answer that question more consistently.
On 9 July 2026, Google announced expanded AI-transparency features for advertising. These include a “How this ad was made” section for users and AI-content label settings for advertisers. Google also identifies India as one of the locations where certain AI-created or AI-edited advertising assets may be subject to disclosure requirements.
For Indian small businesses, this is not simply a policy update to forward to an advertising agency. It affects how campaign images and videos are created, approved, documented and uploaded.
What Has Changed in Google Ads?
Google is introducing a clearer way for people to identify advertisements containing labelled AI-generated or AI-edited assets.
Users can open the three-dot menu or information icon attached to an advertisement on Google Search, YouTube or Discover. Where applicable, a section titled “How this ad was made” can indicate that AI was used to create or edit the advertisement.
Google’s system handles disclosures in two main ways:
- Google-generated assets: When an advertiser uses Google’s own generative-AI advertising tools, Google can automatically add the relevant disclosure.
- Externally generated assets: When an asset is created using another AI tool, the advertiser can use Google’s AI-label control to declare that the asset was created or edited with AI.
The controls were introduced gradually during July 2026 across Google Ads, Display & Video 360, Campaign Manager 360, Merchant Center and Google Ads Editor.
Google also says that local requirements can affect how the disclosure appears. For campaigns targeting India, an AI disclosure may appear as a visible label directly on the advertisement in addition to information available through My Ad Center.
Why This Matters to Indian Advertisers
Generative AI is no longer limited to specialist creative teams. Small businesses routinely use AI-enabled design, writing and video tools to produce:
- Product backgrounds
- Lifestyle images
- Virtual models
- Real-estate visualisations
- Voice-overs
- Short promotional videos
- Image extensions
- Multiple creative variations
This can reduce production time, but it also makes the source of an asset less obvious. A business owner may send an image to an agency without explaining that an AI tool generated part of it. The agency may then upload the asset without reviewing whether a disclosure is appropriate.
That gap creates three practical risks:
- The asset may be published without an appropriate AI label.
- The creative may unintentionally misrepresent a product, property, person or result.
- The business may have no record of how the asset was produced if a customer, platform or regulator questions it later.
Applying an AI label does not make misleading advertising acceptable. Google continues to prohibit deceptive advertisements regardless of how they were created.
Does Every AI-Assisted Advertisement Need a Label?
No. Google explains that not every use of AI necessarily requires an AI-content label. Requirements can depend on the location, the type of content and the extent to which AI changed the asset.
There is an important difference between a routine production adjustment and a substantive synthetic creation.
Routine or assistive changes
Examples may include:
- Cropping an existing photograph
- Resizing an image for a different placement
- Correcting brightness or colour balance
- Removing minor background distractions
- Applying normal compression or formatting
These changes generally do not alter the central meaning of the advertisement. However, advertisers should still review current platform guidance and applicable requirements instead of assuming every minor edit is automatically exempt.
Substantive AI creation or editing
An asset needs closer review when AI creates or materially changes something that appears real. Examples include:
- Generating a realistic person who does not exist
- Placing a real person in a situation that did not occur
- Creating a synthetic customer testimonial
- Generating or cloning a person’s voice
- Changing the appearance or capabilities of a product
- Showing a property feature that has not been constructed
- Generating a realistic event or location
- Making a treatment result appear better than the actual outcome
These assets should not be treated as ordinary photo editing. They require documented review before the campaign goes live.
Practical Examples for Indian Businesses
| Advertising asset | Main concern | Practical action |
|---|---|---|
| AI-generated rendering of an upcoming housing project | The image could be mistaken for a completed property | Apply the appropriate AI label and clearly identify the image as an artistic or proposed representation. |
| AI-generated model wearing a real jewellery product | The product’s size, fit or appearance may be altered | Check the product against the original photograph, disclose AI use where appropriate and avoid inaccurate representations. |
| Synthetic patient image in a clinic advertisement | The image may imply a genuine treatment result | Do not present it as a real patient outcome. Review healthcare advertising requirements and label substantive AI creation. |
| AI voice presenting a coaching-course testimonial | Customers may believe the speaker is a genuine student | Do not frame synthetic speech as an authentic customer statement. Add appropriate disclosure and rewrite the claim. |
| Restaurant photograph with a small object removed from the background | The edit may be purely presentational | Retain the original file and assess whether the edit materially changes the food, premises or customer expectation. |
| AI-generated festival background behind an actual product | The product may remain accurate while the setting is synthetic | Confirm that the composition does not alter the product and review whether the final asset should be labelled. |
How to Apply an AI Label During Campaign Creation
The exact interface can vary by campaign type, but Google’s documented workflow follows these steps:
- Create or edit the Google Ads campaign.
- Upload or select the required image or video assets.
- Open the Review assets stage.
- Select the assets that need to be reviewed.
- Choose Manage AI label.
- Select Label this asset as created or edited with AI where applicable.
- Select Don’t label this asset only after confirming that the declaration is not required.
- Save the selection and complete the campaign review.
Do not leave this decision until the final minutes before launch. The person approving the creative should know how it was produced and what the final advertisement represents.
How to Review Existing Assets
Businesses should also audit images and videos already stored in their accounts.
- Open Google Ads.
- Go to Tools.
- Open Asset Studio and then Asset library.
- Select the relevant image or video asset.
- Open the AI-label option.
- Choose whether the asset should be labelled.
- Save the change.
Google provides an AI-label status column and related filters in the Asset library and reporting interface. This allows an advertiser or agency to identify assets that have been labelled and find items that still require review.
If Google automatically applies a label to an asset, Google says the advertiser cannot overwrite that automatic designation.
What If the Creative Was Made Outside Google?
An image does not have to be created inside Google Ads for the disclosure process to matter.
External sources can include:
- AI image generators
- Design platforms with generative features
- AI video-production services
- Voice-generation tools
- Agency production systems
- Freelancers using AI-assisted editing
Google’s own tools can automatically pass the relevant disclosure information into the advertising system. Assets produced elsewhere may require the advertiser to use the manual control.
This is why every creative brief should contain a simple question:
Was generative AI used to create or substantially alter any realistic image, video, person, voice, place, product or event in this asset?
A clear answer is more useful than the vague statement that a design was “AI assisted.”
A Practical AI-Creative Review Process
1. Record the source of every asset
Maintain a basic register containing:
- Asset filename
- Campaign name
- Original source
- AI tool used, if any
- Description of the AI-generated or edited element
- Approval owner
- AI-label decision
- Date reviewed
This can be managed in a spreadsheet for a small account. The important point is that the information exists before the asset is uploaded.
2. Compare the advertisement with reality
Check the creative against the actual product, service, property or result. Ask:
- Does the product look materially different?
- Could a customer believe an imagined scene is real?
- Does the asset imply a customer endorsement that never occurred?
- Does it create a result the business cannot substantiate?
- Would a reasonable viewer make a different buying decision after learning how the image was created?
An AI label should support transparency. It should not be used to excuse an inaccurate claim.
3. Separate minor edits from material changes
Document what the tool changed. “Edited in an AI design tool” is too broad. A useful note would be:
Original product photograph retained. Background replaced with a generated Diwali setting. Product shape, dimensions and colour were not changed.
This makes the approval decision easier and creates a usable audit trail.
4. Apply the platform label
Use Google’s AI-label setting where the asset requires disclosure. If the creative contains its own disclosure, make sure it remains readable across placements.
Google advises advertisers not to place their own labels too close to the corners or edges because automated resizing or cropping may remove them. If the disclosure is built into an image, review image-enhancement and cropping settings carefully.
5. Review the complete customer journey
The advertisement and landing page must tell a consistent story. If the advertisement uses a conceptual rendering, the landing page should not describe it as a photograph of a completed project.
Also review:
- Headlines and descriptions
- Product claims
- Before-and-after comparisons
- Customer testimonials
- Pricing statements
- Landing-page imagery
- Lead forms and disclaimers
6. Preview every major placement
Check how the asset appears on Search, YouTube, Discover and other selected inventory. A disclosure that works in one aspect ratio may be cropped or difficult to read in another.
7. Recheck reusable assets
An image may be appropriate for one campaign but unsuitable for another. For example, a clearly described architectural concept image may become misleading if reused with a headline such as “Book your visit to our completed homes.”
Common Mistakes to Avoid
Assuming external AI assets will always be detected automatically
Google may automatically identify and label some assets, but advertisers should not depend on detection as their entire process. External AI-generated creative still requires an internal review and an accurate declaration.
Treating the label as permission to exaggerate
Disclosure does not make an unsubstantiated product claim acceptable. An artificial testimonial, false treatment result or misleading property image can remain problematic even when it carries an AI label.
Labelling everything without examining it
Applying a label to every resized or lightly corrected photograph may create unnecessary confusion. Classify the actual change and make a documented decision.
Placing a custom disclosure at the edge
Responsive placements can crop creative assets. Keep essential disclosure text inside a safe area and inspect every major variation.
Forgetting YouTube uploads
When a video is uploaded to YouTube through Google Ads, the advertiser may be asked whether AI was used. The person uploading it should have the correct production information rather than guessing.
Leaving the decision entirely to the agency
An agency cannot accurately classify an asset if the client does not reveal how it was created. Responsibility should be shared through a documented handover and approval process.
Will an AI Label Reduce Advertising Performance?
Google’s announcement presents AI labelling as a transparency feature, not as a campaign-optimisation tactic. Advertisers should not assume that applying a label will automatically improve or reduce conversion rates.
The more useful question is whether the creative remains clear, accurate and persuasive after the disclosure is applied.
A strong advertisement should still communicate:
- What the business offers
- Who the offer is for
- Why the offer is relevant
- What evidence supports the claim
- What action the customer should take
AI can accelerate production, but it does not replace truthful positioning, good design or a relevant landing page.
Google Ads AI-Creative Checklist
Before launching an AI-assisted advertisement in India, confirm the following:
- The original source of every asset is recorded.
- The team knows which parts were generated or altered with AI.
- The creative does not misrepresent a product, property, person or outcome.
- Testimonials and endorsements come from genuine, authorised sources.
- The appropriate Google Ads AI-label setting has been reviewed.
- Any custom disclosure remains visible after cropping and resizing.
- The advertisement and landing page communicate consistent facts.
- The final asset has been approved by an accountable person.
- High-risk or uncertain campaigns have received appropriate legal review.
- The label status is periodically checked in the Asset library.
Frequently Asked Questions
Do all AI-generated Google Ads need a label in India?
Not every routine use of AI necessarily requires the same disclosure. The requirement can depend on the type of asset, the extent of the change and applicable rules. Realistic content that was created or materially altered using generative AI deserves particularly careful review.
Does Google automatically label assets created with Google AI?
Google says disclosures are added automatically when advertisers use its generative-AI advertising tools. Advertisers should still review the final output for accuracy and compliance.
What if an asset was created using an external AI tool?
Google provides a manual control that allows advertisers to indicate that an externally produced asset was created or edited with AI. Record the production method before uploading the asset.
Where can I change the AI-label status of an existing asset?
Open Tools, Asset Studio and the Asset library in Google Ads. Select the asset and use the available AI-label management option. Label status can also be reviewed through the relevant column and filters.
Can I remove a label that Google applied automatically?
Google says an automatically applied AI label cannot be overwritten by the advertiser.
Will the label appear directly on advertisements in India?
Google says local requirements may result in a label appearing directly on the advertisement. Its advertiser guidance specifically identifies campaigns targeting India among those that can receive visible disclosure overlays.
Can I add my own AI disclosure to the creative?
Yes. Google says these disclosures are not treated as prohibited text overlays or watermarks. Keep them away from edges and verify that automated cropping or enhancement will not remove them.
Does using Google’s AI-label setting guarantee compliance?
No. Google explicitly states that using its label does not guarantee compliance with every applicable regulation. Businesses should obtain appropriate legal guidance for uncertain or high-risk advertising.
Final Takeaway
Google’s new AI-labelling controls make creative provenance a practical campaign-management responsibility.
Indian businesses do not need to stop using generative AI. They do need a reliable process for recording how assets were produced, separating minor edits from substantive synthetic content, preventing misleading representations and applying the appropriate disclosure before launch.
The safest workflow is simple: document the source, compare the creative with reality, review the label requirement and keep an accountable human involved in the final decision.
Build a More Reliable Google Ads Creative Process
Rizelex Digital helps Indian businesses manage Google Ads, creative production, landing pages and conversion tracking as one connected customer-acquisition system.
If your account contains AI-generated assets but lacks a documented review and approval process, Rizelex Digital can audit the campaigns, organise the Asset library and establish a practical creative-governance workflow without slowing down production.