AI tools are now part of most marketing workflows. That raises a practical question many global marketers are still working through: when you use AI to help create content, do you need to say so?
Labeling AI-generated content is part regulatory question, part brand decision. Requirements vary by market and platform. Consumer expectations vary too. And the line between “AI-generated” and “AI-assisted” is genuinely blurry.
This post breaks down what the current landscape looks like, how to label effectively and the situations where a label isn’t necessary.
Here’s our recap:
Why AI content makes consumers cautious
AI tools are now built into the programs marketers use every day. Microsoft Office, Adobe Creative Suite and Canva all include AI features. In a 2024 survey, 75.7% of digital marketers said they use AI tools for work.
But adoption hasn’t automatically translated into consumer trust. Several recent studies show where the friction is:
- About half of consumers across 17 markets said they’re uncomfortable with brands using AI to create digital brand ambassadors or generate images used in advertising.
- 41-42% said they’re uncomfortable with AI generating product descriptions, taglines or determining ad placement.
- In a 2024 study of 1,000 Americans, respondents could identify AI-generated content about 54.6% of the time. They were slightly better at spotting AI-written copy (57.3%) than AI-generated images (53.4%).
“AI is not human—it doesn’t think, work or understand as we do. Its responses may appear fluent because of its training on vast amounts of data and its ability to predict the next word based on probability. But it lacks genuine comprehension.” – Naomi Bleackley, Editorial Account Manager and AI specialist at VeraContent
The emotional stakes are real. In a 2025 study, participants who were told a sales letter was AI-generated responded negatively, even when the content itself was the same as a human-written version. They were less likely to recommend the brand, more likely to switch and gave lower simulated review scores.
Factual communications triggered less negative reaction than emotional ones. And consumers responded more positively to AI-generated messages signed by a clearly labeled chatbot than those signed by a real company representative.
See also: Generating quality global content at scale using AI tools
What causes the consumer to dislike AI?
There’s a myriad of reasons: fear of the unknown, media overhype, knowing that AI can suffer hallucinations, fear of job loss or media manipulation, privacy and environmental concerns, and biases inherent in AI due to the biased data it’s trained on.
“The public’s mistrust comes from AI-generated content feeling so human that it’s confusing. Discovering something that is AI-made can feel deceptive, as we’ve long assumed content is human-created. It’s similar to previous reactions to Photoshopped images—people felt it was ‘cheating.’ With AI taking over more of the creative process, it raises questions: ‘How do I know what’s real anymore?’ This uncertainty is likely the core issue.” – Naomi Bleackley, Editorial Account Manager and AI specialist at VeraContent
While some of these concerns and inherent negative reactions may lessen as people adjust to AI’s everyday use, how can marketers reconcile AI’s powerful capabilities in content creation with consumers’ mistrust and dislike of AI? That’s where labeling (might) come into play.
See also: AI can’t replace cultural adaptation in localization
Why labeling AI-generated content matters
Labeling AI-generated content appears to be the current “solution” to the brand/consumer divide over AI use. And its application is important for a myriad of reasons: brand reputation, campaign success and even legal obligation.
In a 2024 survey, 94% of consumers said all AI content should be disclosed. However, consumers were split on who should be disclosing. 33% said that it should be the brand’s responsibility, 29% said it should be the hosting social network’s responsibility, and 17% thought that brands, social networks and social media management platforms should all be responsible.
Using AI to generate content can raise some ethical considerations you should take into account as a marketer:
- Should consumers be explicitly informed that they’re talking to a computer and not a real person?
- How does your brand remain authentic when a machine helps develop your brand voice?
Customers don’t want to feel lied to, or like a brand is hiding something. When customers recognize AI-generated content but don’t see it disclosed, they may question both the content and the brand. To maintain trust, establish a clear framework for deciding when to label content as AI-generated.
Clearly labeling AI-generated content can build trust with your audience by showing your brand’s commitment to honesty and integrity. It can also differentiate the brand as one that engages in ethical content creation practices, and enhance engagement by starting a conversation about AI that can lead to curiosity and interest instead of aversion.
Regulation is moving fast. The EU AI Act, fully applicable from March 2026, requires disclosure of AI-generated content and compliance with EU copyright law. Generative AI isn’t classified as high-risk under the act, but transparency requirements still apply. In the US, a bipartisan AI disclosure bill was introduced in 2023. In the UK, an AI regulation bill is under development.
If you’re operating across markets, your disclosure obligations may differ by region. Keep up with regulatory developments in the markets you’re active in.
How to label AI-generated content: platforms and best practices
Effective labeling depends on what type of content it is, how AI was involved and where it’s being published. As an organization, it’s helpful to set clear disclosure guidelines for each type of content so your disclosures are consistent.
Many social media platforms offer native ways to disclose AI use in your posts:
Meta (Facebook and Instagram)
Posts, reels and stories can all be labeled as having AI content. In each case, adding the label is simple, though it can only be done on mobile devices. In a post, click the dropdown menu next to AI Label off and turn on the Add AI label switch. On reels, this switch is on the publishing screen, and for stories, it’s in the story settings.
When you label your content, it will have a label in the corner that says “AI info.” When users click or tap that label, they can see how AI could have been used to create the image or video in the post.
Meta may also flag your content with this label if it detects that your content has been created with AI, whether you choose to disclose that or not. Meta will also say whether the label was self-disclosed or imposed. For content modified or edited—not created—with AI, the post’s menu will have an AI info label.
YouTube
In the YouTube creator studio, there’s a checkbox you can see when uploading a video to self-label it as containing AI-generated material. YouTube mandates labeling if the content is extremely realistic-seeming, and will also add this label automatically if the content is realistic or involves sensitive topics. The AI label will appear in both the video and the video description.
Content that is considered “clearly unrealistic,” like animation or a dragon, doesn’t have to be labeled under YouTube’s guidelines. The label also isn’t mandated if you use AI for things like lighting or beauty filters, or to blur backgrounds.
TikTok
Like the two previously mentioned social media companies, TikTok offers a label for AI content, where users can disclose if the content was completely AI-generated or significantly edited with AI. Under more options when posting a video, you can turn on the AI-generated content switch.
TikTok also has a policy that automatically labels posts that it deems to have been either created or heavily edited with AI. A creator-added label is visually distinct from an automatic TikTok label.
LinkedIn, in partnership with the Coalition for Content Provenance and Authenticity (C2PA), has pioneered a slightly different approach from other social networks. Instead of only labeling AI-generated content as such, the platform has suggested that all posts be labeled.
Clicking on the label would display content credentials, content source (like which AI tool was used to help generate the post) and other information. However, this label is only available if your content contains C2PA credentials. If not, you should manually disclose your AI content.
While these tools are helpful in certain situations, what if your content isn’t posted on one of these platforms, or you want to provide your own context about AI-generated content? Labeling content as AI-generated directly may make your labeling more effective and comply with higher standards and best practices.
Ways to label AI-generated content
There are many different ways to label AI-generated content, depending on the type of content and where it’s being posted. Some of the most common methods are:
- Including a small overlay within an image or video, usually in the bottom right-hand corner. This can be simple text like “AI-generated” or you could design a small graphic that incorporates this text in a more visually appealing way. Meta, for example, has a small graphic they put in the corner of all of their AI-generated posts.
- Adding a label in the text or caption of a post can allow you to add more context or integrate the label more naturally. For example, you could use a caption like “Explore our AI-generated vision of the perfect mountain retreat for your next getaway.”
- You can also include hashtags in a social media post indicating that it’s made with AI, and use the same one to maintain brand consistency. For example, Meta tags their AI posts with #imaginedwithai.
- For articles or blog posts that were created with the help of AI (we don’t ever recommend fully AI-generated articles), you can add a simple disclaimer at the end of the article. A good example is: “Disclaimer: This article was created with some help from AI, but edited, reviewed and fact-checked by a real person.”
- When posting partially AI-created articles, it’s a best practice to not include a specific author’s name. Don’t say that “AI” was an author, either, as people can take that to mean that it was completely made by AI, even if you include human authors on the byline as well. It would be better to say it was written by “the team” or another generic placeholder, maybe with a small AI disclosure near the byline. For example, Buzzfeed publishes AI-generated articles under the name “Buzzy the Robot.”
Regardless of how you choose to label your AI-generated content, the most important thing to do is keep up to date with best practices, regulations and ethical considerations, and meet with your team(s) regularly to discuss your approach.
Which words work best?
A 2023 study across five countries and four languages tested nine different labels. “AI-generated,” “Generated with AI” and “AI Manipulated” were most effective at signaling AI involvement without implying deception. “Edited,” “synthetic” and “not real” were the least effective.
Language matters for global teams, too. The same study found that Chinese speakers associate “artificial” with human involvement, while English-, Portuguese-, and Spanish-speaking participants associate it with automation. Work with local linguists to confirm your labels land correctly in each market.
At VeraContent, this is part of the localization process for every market. Labels that feel transparent in one region can feel alarming in another.
“Brands, especially larger ones with wide audiences, should have an internal policy to maintain ethical standards and consistency. This ensures clarity on how to handle AI-related content and avoids ambiguity. Additionally, they should communicate this policy clearly with any agencies, creators or partners they collaborate with.” – Naomi Bleackley, Editorial Account Manager and AI specialist at VeraContent
When you don’t need to label AI content
Labeling AI-generated content is the current “best” way to make AI content palpable for consumers, but the practice comes with criticisms and limitations. Labeling isn’t always necessary. Here are the clearest situations where you can skip it.
AI labels are supposed to be neutral descriptions explaining what technology was used to generate or modify a specific piece of content. However, many consumers perceive them as indicators of whether the content is true or false. Sometimes, real images with cosmetic or artistic edits facilitated by AI are triggered to be labeled as AI content on social media platforms, which can cause problems for those accounts.
Overall, users expect the most amount of transparency, in this case labeling, for content that is completely AI-generated, is photorealistic, depicts current events, or includes real people doing or saying things they didn’t do or say. Many people agree that AI-generated and AI-edited content should have different labels on social platforms.
In many situations, you’re not using AI to completely create and generate your content. Most marketers use AI as a tool to aid in the content creation process. We always recommend that you review, edit, and fact-check any AI-created content before posting it to make sure it’s high quality, correct, and in line with your brand standards.
“While labeling AI-generated content should be standard, the real challenge is determining where to draw the line between AI-generated and AI-assisted work. People have different opinions, so there’s no clear-cut answer.” – Naomi Bleackley, Editorial Account Manager and AI specialist at VeraContent
For example, with a blog article, AI might help create a structure or draft, which is then edited—so is it AI-generated or just AI-assisted?
“I think if you’re using AI for brainstorming or rewording a sentence, but you’re putting in the effort and the final work feels like your creation, it shouldn’t need to be labeled as AI-generated. While labeling AI-generated images should be standard as they are at their core AI-created, written content remains a gray area, making it a tough call.” – Naomi Bleackley, Editorial Account Manager and AI specialist at VeraContent
How much you want to disclose AI involvement in your content creation process is ultimately up to you and your team. However, there are some common situations where it may not be necessary to label AI content:
AI-assisted photo editing
Many image editing apps, like Photoshop, have AI tools built into their programs. Generative fill, for example, is a tool in Photoshop where you type in what you want to add or remove certain elements from an image, like removing a hand or adding a water drop to a leaf. While these tools use AI, the pictures and images they’re being used on are still primarily human-generated.
If generative fill (or other tool you’re using) modifies the image but doesn’t change it substantially, AI labeling isn’t necessary. After all, most images used in advertising these days are edited in some way using Photoshop, and its use isn’t always disclosed. Be careful, though, as some social networks have been known to slap an AI-generated label on something that was only mildly retouched using AI tools.
AI used for research or ideation only
Many writers and content creators use AI to help them generate ideas on a topic or compile research from sources fed into the program. If the actual article that results from this work is completely human-written and edited, and the information is reliable and objective, AI labeling isn’t necessary.
If you think it’s a good idea, you could disclose your editorial process either at the bottom of the article or on your About Us page on your website. But a large AI-generated tag isn’t necessary and may lead people to distrust your content unnecessarily, particularly if the article is attributed to a human author.
Routine or functional copy
Content that doesn’t involve creative expression, like summaries, titles, metadata descriptions, and generic functional web and app copy, has long been machine-generated. As outputs of these types of copy are predictable, generating them with AI is normal and won’t affect the quality of the actual work. Specifically labeling them as AI-generated isn’t necessary, either.
Content derived from someone else’s work
Content reconfigured directly from someone else’s work should be approached the same way it was before we started regularly using AI. For example, suppose you’re creating a table or graph based on data from a copyrighted study. In that case, you should include a notice and properly attribute the source to avoid any accusations of copyright infringement.
However, short derivative content based on your own work may not need to be labeled as AI-generated. For example, if you feed ChatGPT a list of successful email subject lines that your company has used in the past and ask it to generate new ones based on the ones on that list, you wouldn’t need to disclose those subject lines as being AI-generated.
Using AI well: keeping the human in the loop
AI works best as a partner, not a replacement. It handles the repetitive parts of content creation. Your team handles the judgment, the nuance and the accountability.
“At VeraContent, we view AI as a tool, a friend and a helping hand. Something to make our jobs easier and our work better. While many fear AI might replace jobs, our approach is to use it to assist linguists and enhance the consistency of our content.” – Naomi Bleackley, Editorial Account Manager and AI specialist at VeraContent
When those roles are clear, you can use AI confidently without it undermining your brand. If you need help incorporating AI into your global content workflow, book a call with our team.