Survey Reveals How Many Consumers Would Feel Manipulated by an AI Ad

A survey of 446 U.S. adults found that many consumers would feel manipulated by an advertisement created entirely with artificial intelligence. That reaction grew when the advertiser disclosed the AI use only after the purchase.

The survey also found that timing affects more than a consumer’s immediate reaction. Respondents who learned about the AI involvement after buying a satisfactory product were less likely to trust the advertiser or buy from it again than respondents who received the information before making the purchase.

Among respondents who were told upfront that an advertisement’s words and images were created entirely using AI, 62.3% said they felt manipulated a lot or some. The share rose to 70.4% among respondents who learned about the AI use afterward and were told that the advertisement had not disclosed it.

That amounts to roughly six in 10 consumers in the upfront-disclosure scenario and seven in 10 in the later-discovery scenario. The difference was 8.1 percentage points. It pointed in the direction advertisers should take seriously, although it did not remain statistically significant after the survey’s adjustment for multiple comparisons.

The strongest movement appeared in the feeling-misled measure. Fifty-seven percent of the upfront group said they felt misled a lot or some, compared with 70.0% of the later-discovery group. That 13-point difference remained statistically significant after adjustment.

The distinction matters. Feeling manipulated can describe a consumer’s reaction to the persuasive force of an advertisement. Feeling misled more directly reflects the discovery that an important fact about the advertisement was withheld. In this survey, the second reaction changed more sharply when disclosure came after the purchase.

A survey of 446 U.S. adults found that the timing of an AI advertising disclosure was associated with consumer trust. Respondents who learned before purchasing that an advertisement was created entirely with AI were more likely to trust the advertiser and buy from it again than those who discovered the AI use afterward. Later discovery was also associated with stronger feelings of being misled, even though every respondent was told the product experience was satisfactory. The findings support visible, pre-purchase disclosure and meaningful human review, while the separate nonprobability samples and hypothetical scenarios limit how broadly the results can be applied.

ContentEngine surveyed two separate samples of 223 U.S. adults. Both groups read a hypothetical scenario about an online advertisement for a product they had not planned to buy. In both versions, the advertisement persuaded the respondent to make the purchase, and the respondent was satisfied with the product afterward.

The timing of the AI disclosure separated the scenarios:

Both groups then answered questions about trust, repeat purchase intent, regret, feeling misled, recommendation intent, feeling manipulated, the importance of AI disclosure and the importance of human review.

The setup gives the results a clear practical meaning, while also placing limits on what can be claimed. The survey compared separate nonprobability samples rather than randomly assigning people to one scenario or the other. The later-discovery scenario also included an explicit nondisclosure statement. That wording may have increased the number of respondents who felt misled, independently of their views about AI itself.

The clearest business effects involved trust and future behavior. Among respondents who saw the disclosure before buying, 76.7% said they would trust the advertiser a great deal or a fair amount. The figure fell to 65.0% for respondents who learned about the AI use afterward.

Repeat purchase intent showed a similar pattern. About 79.8% of the upfront group said they would be very or somewhat likely to buy from the advertiser again. Only 67.3% of the later-discovery group gave one of those favorable answers.

The gaps were 11.7 percentage points for trust and 12.6 points for repeat purchase intent. Both remained statistically significant after the analysis used the Holm method to adjust the p-values across eight comparisons. The reported 95% confidence intervals also stayed above zero for the size of the difference.

The product experience was positive in both scenarios, which makes the finding more useful for advertisers evaluating campaign performance. Every respondent was told that the purchase ended satisfactorily. A good product experience did not fully protect the advertiser from lower trust after undisclosed AI use was revealed.

A successful sale can still leave a trust problem when the consumer learns that an important part of the advertising process was hidden.

That result should affect how brands judge AI-generated creative. Immediate conversion figures may show that an ad worked in the short term. They do not necessarily show how the audience will evaluate the brand after learning how the ad was made.

The survey makes a persuasive case for treating AI disclosure as part of the customer experience rather than as a legal footnote. Telling consumers before they act gives them relevant context, but it is not enough on its own: many respondents still felt manipulated even with advance notice. Brands should therefore pair clear, material disclosure with a named human reviewer who is accountable for claims, imagery, targeting and the overall persuasive message.

Disclosure produced better results than later discovery on the survey’s main trust measures, but respondents who received advance notice still expressed discomfort.

In the upfront group, 57.0% said they felt misled a lot or some, and 62.3% said they felt manipulated a lot or some. Those are substantial shares even though the scenario gave consumers the information before the purchase.

Several parts of the scenario may explain that reaction. The advertisement persuaded respondents to make an unplanned purchase, which could make the persuasive act feel manipulative on its own. The scenario also described an advertisement created entirely with AI, a stronger form of AI involvement than using a tool to resize an image, suggest headlines or generate a few creative variations.

The survey did not ask respondents why they felt manipulated. As a result, the findings cannot separate discomfort caused by the AI, the unplanned purchase, the persuasive technique, or a combination of those factors.

That uncertainty should discourage simple interpretations. A disclosure can give consumers information before they act, but it cannot guarantee that they will approve of the ad’s claims, targeting or emotional appeal. Transparency creates a fairer basis for a decision; it does not replace responsible creative judgment.

The survey found broad support for both disclosure and human oversight. Across the two samples, 90.1% of respondents said it was very or somewhat important for brands to tell consumers when an advertisement had been created entirely using AI.

Human review received nearly the same level of support. In total, 88.3% said it was very or somewhat important to know that a person had reviewed and approved an AI-generated advertisement before publication.

The human-review figures were almost identical across the scenarios: 87.9% in the upfront group and 88.8% in the later-discovery group. The difference was less than one percentage point and was the smallest gap measured in the survey.

For advertisers, disclosure and review serve different purposes:

A human approval step needs a defined scope to have practical value. A reviewer who only checks spelling has not fully reviewed an advertisement that makes health claims, uses synthetic people or targets a vulnerable audience. Brands should document who reviewed the creative, what the reviewer checked and whether the reviewer had authority to reject or revise it.

The survey fits a wider concern about whether audiences can tell when marketing content was made with AI. A 2026 Bentley University-Gallup survey reported that 79% of Americans had seen advertisements in the previous 30 days that appeared to be made using AI. Canva has reported that 70% of consumers believe it will eventually become impossible to identify AI-generated advertising without disclosure.

As synthetic images, voices and copy become harder to distinguish from human-produced material, disclosure becomes more important as a source of context. Consumers may not object to every use of AI. They may object to discovering that the advertiser made a material choice about the ad and kept that choice out of view.

Industry guidance is also becoming more specific. The Interactive Advertising Bureau’s AI Transparency and Disclosure Framework V2 uses a risk-based, materiality-driven approach to help determine when and how AI involvement should be disclosed in consumer-facing advertising. That approach recognizes that a minor production assist may carry different implications from an advertisement in which AI generated the central image, voice, testimonial or message.

The European Commission’s guidance on Article 50 of the EU AI Act also addresses transparency obligations for certain AI-generated or manipulated content. The requirements can depend on the system, the content and the parties involved, so brands operating in or serving European markets should review the applicable rules with qualified legal advisers.

U.S. advertisers may face different legal requirements depending on the product, claim, audience and advertising channel. Regardless of jurisdiction, the survey suggests a practical standard: information that could change how a consumer evaluates an advertisement should be available before the consumer acts.

A disclosure buried in a terms page or added after checkout gives consumers little help with the decision the disclosure is supposed to inform. An effective notice should be visible near the advertisement and written in ordinary language.

For an advertisement whose words and images were entirely AI-generated, a clear notice could state that fact directly. If AI played a narrower role, the disclosure should describe that role accurately rather than using a vague label that leaves consumers guessing.

A useful disclosure process should answer several operational questions:

The exact wording will vary by channel. A social advertisement, product page, video and voice assistant may need different treatments. The core requirement remains stable: the information should be noticeable, understandable and available at the point where it can affect a consumer’s judgment.

Responsible AI advertising shifts disclosure and accountability to the point where consumers can use them.

The results provide a warning about hidden AI use, but they do not prove that later disclosure alone caused every difference between the groups. The samples were separate, respondents were not randomly selected from all U.S. adults, and the results were not weighted. A conventional margin of sampling error was not reported.

Measured demographic characteristics did not differ significantly between the two samples, but similar age, gender, income, device and regional profiles cannot rule out differences in attitudes or other traits. The scenarios were also hypothetical. Respondents did not view a real advertisement, spend money or use a real product.

The survey tested advertisements created entirely with AI. It does not show how consumers would react to a human-written ad with AI-assisted editing, an AI-generated background image or automated audience segmentation. Those uses may raise different concerns.

Some secondary differences were less conclusive. The later-discovery group reported more regret and manipulation, while fewer respondents said they would recommend the advertiser or considered disclosure important. Those differences did not remain statistically significant after adjustment for all eight comparisons.

These limits make the most defensible reading fairly narrow: advance disclosure was associated with higher trust and repeat purchase intent, while later discovery was associated with more reported feelings of being misled. The results support better disclosure practices without providing a universal prediction for every AI advertising campaign.

Brands can treat the survey as a reminder to evaluate trust after the sale, not only performance at the moment of conversion. Before launching an AI-assisted campaign, an advertiser can identify the AI’s role, decide whether that role is material to the audience and place the disclosure where it can be seen before action.

The review process should be just as concrete. A named person or team should check factual accuracy, product depictions, rights to source material, potential bias, targeting logic and the tone of the persuasion. The reviewer should have enough context and authority to make changes rather than simply approve whatever the production system generated.

Campaign testing can also include questions about perceived manipulation and disclosure expectations. A strong click-through rate alongside high discomfort would give the brand a different signal from a campaign that performs well and preserves confidence. Monitoring comments, customer support contacts, repeat purchase behavior and post-campaign surveys can help reveal problems that conversion data misses.

The central finding is straightforward. Consumers who learn about AI before making a purchase appear more willing to trust the advertiser than consumers who learn about it afterward. Many consumers still feel manipulated even with advance notice, which gives brands a second responsibility: disclose the production method early and make sure a human takes real responsibility for the message.