34% Would Feel Misled ‘A Lot’ in an AI Ad Scenario, Consumer Poll Reveals

A new consumer poll suggests that the timing of an AI disclosure can shape how people judge a brand, even after a purchase turns out well. The strongest reactions center on a basic expectation: consumers want to know who or what created the sales pitch before they act.

ContentEngine surveyed 446 U.S. adults about an online advertisement made entirely with artificial intelligence. Every respondent imagined buying the advertised product on impulse and feeling satisfied after using it. The groups then received different information about the ad: one learned about the AI use before buying, while the other learned afterward and was told the ad had not disclosed it.

The difference was substantial. About 76.7% of people who saw an upfront disclosure said they would trust the advertiser a great deal or a fair amount. That share fell to 65% among people who learned about the AI afterward. Repeat purchase intent followed the same pattern, dropping from 79.8% to 67.3%.

The survey headline focuses on the share who said they would feel misled a lot. The broader result is equally important: when the responses for feeling misled a lot or some are combined, the later-discovery group reached 70%, compared with 57% among those who knew about the AI before the purchase.

The survey tested a simple consumer experience with one important difference in timing. In the upfront version, the ad clearly stated that its words and images were created entirely using AI. In the later-discovery version, the consumer saw no disclosure, made the purchase, used the product, and then learned how the ad had been produced.

That sequence gives the consumer two separate pieces of information. The first concerns the product and the purchase. The second concerns the way the sales message was created. A satisfactory product helped establish a positive experience, yet it did not erase the reaction to the undisclosed production process.

The later-discovery scenario produced three statistically significant differences after the analysis adjusted for the survey’s eight comparisons:

The gap in trust was 11.7 percentage points. The gap in repeat purchase intent was 12.6 points. Feeling misled moved 13 points in the other direction.

Those numbers give advertisers a practical warning. Immediate conversion and product satisfaction provide only part of the picture. A campaign can persuade someone to buy and still create a weaker relationship when the buyer later feels important information was withheld.

The result also fits a wider shift in consumer expectations. Research from Gallup found that 79% of Americans had seen advertisements in the previous 30 days that appeared to use AI. As AI-generated images, video and copy become harder to identify by sight, consumers have fewer ways to judge how an ad was made without a disclosure.

A ContentEngine poll of 446 U.S. adults found that the timing of an AI disclosure was associated with how consumers evaluated an advertiser after a satisfactory purchase. Respondents who were told before buying that the ad had been created entirely with AI reported higher trust and repeat-purchase intent than those who learned about the AI use afterward. The later-discovery group was also more likely to feel misled. The findings suggest that advertisers should place clear, meaningful disclosures before the consumer acts and pair them with accountable human review, while recognizing that the survey used hypothetical scenarios and nonprobability samples.

Upfront disclosure produced better results on trust and future purchase intent, but it did not make every concern disappear. In that group, 57% still said they felt misled a lot or some, and 62.3% said they felt manipulated a lot or some.

Several features of the scenario may explain that discomfort. The ad persuaded people to make an unplanned purchase, which can make the persuasive experience feel aggressive even when the product works as promised. The scenario also described an advertisement whose words and images were created entirely with AI. That is a more extensive use of the technology than tools that resize an image, suggest a headline or generate a few background variations.

The poll did not ask respondents why they felt misled or manipulated. That leaves several possible explanations in play:

The survey cannot separate those reactions. It does show that a label alone will not settle every question about an ad. Brands still have to review the claim, the imagery, the targeting and the tone of the creative.

That distinction matters for companies that treat disclosure as a compliance checkbox. A small label can tell an audience that AI was involved. It cannot establish whether the ad is accurate, fair or appropriate for the people who see it.

Across the two groups, 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: 88.3% said it was very or somewhat important to know that a person had reviewed and approved the ad before publication.

The human-review result was almost identical across the samples. It reached 87.9% in the upfront-disclosure group and 88.8% in the later-discovery group. That consistency suggests the question was important to respondents regardless of when they learned about the AI use.

Disclosure and review serve different purposes. A disclosure gives consumers information about the production process. Review gives the brand a chance to take responsibility for the finished material.

A meaningful review should cover more than spelling and visual quality. It should include:

A reviewer also needs authority to reject or revise the ad. If approval means clicking through a queue after a system has already decided the creative, it offers little accountability.

The most useful lesson is not simply that consumers prefer an AI label. It is that disclosure works as a signal of respect for the decision-making process. Telling people before the ad persuades them gives them context; revealing the information afterward can make a successful transaction feel like an incomplete one. Brands should therefore treat disclosure as part of creative strategy and accountability, not as a compliance footnote. A visible notice cannot repair inaccurate claims or manipulative targeting, but withholding it can weaken trust even when the product delivers.

The central consumer expectation is straightforward: information that could affect a decision should arrive before the decision. A disclosure placed after the sale may document the process, but it comes too late to inform the purchase.

That timing question applies across formats. An AI notice may appear beside an image, in a video frame, in a caption, on a landing page or within a sponsored post. The placement should match the moment when a person encounters the persuasive content. A disclosure buried in terms of service or placed after a click has limited value for the original decision.

The wording also needs to describe the role AI played. Consumers may respond differently to these statements:

Those uses are materially different. A broad label that says only AI assisted may leave consumers guessing about whether the system wrote the claims, created the person shown in the image or selected the audience.

The IAB’s AI Transparency and Disclosure Framework V2 takes a risk-based and materiality-driven approach to these questions. That approach gives advertisers room to distinguish minor production assistance from AI involvement that changes the substance or appearance of an ad.

For a consumer, the useful test is simple: would knowing about the AI use change how the person evaluates the ad, the brand or the decision to buy? If the answer may be yes, the information belongs close to the ad and before the action.

The poll is not a legal test, and its findings do not determine what a brand must disclose in every market. Legal duties depend on the jurisdiction, the type of AI system, the content and the way the ad is distributed.

The European Commission’s guidance on transparency obligations under Article 50 of the AI Act provides one example of the direction regulators are taking. The guidance discusses transparency duties for certain AI-generated or manipulated content and identifies the legal person using an AI system under its authority as the relevant deployer in examples such as advertising companies.

That framework carries an operational message for brands: responsibility remains with the organization using the system. Employees who work under the company’s direction are not treated as separate deployers simply because they operate the tools.

Companies advertising in the United States also face a broader consumer protection concern. If an AI-generated ad makes a false claim, uses a deceptive image or creates a misleading impression about a product, the production method will not excuse the underlying conduct. Disclosure and review need to sit alongside ordinary standards for truthful advertising.

The survey points to several concrete changes for marketing teams and agencies.

The label should appear where the consumer encounters the ad, before a click, sign-up or purchase. A post-purchase explanation cannot provide the same decision-making value.

Teams should document whether AI created the words, images, voices, video, targeting or only a minor production element. That internal record supports a more useful consumer-facing notice.

Someone with the authority to edit or stop a campaign should approve the final ad. The owner should be able to explain the evidence behind product claims and the reason for the selected audience.

A creative team may like an ad before seeing its AI label. Testing the complete experience, including the disclosure, can reveal whether the ad feels artificial, manipulative or confusing once the production method is known.

Click-through rate, conversion rate and immediate sales do not show the whole customer response. Brands should also monitor repeat purchase, complaints, unsubscribe behavior, comments and questions about how the content was made.

A basic record can include the AI tools used, the prompts or source materials, the human edits, the fact-checking process, the final disclosure and the person who approved publication. That record supports internal learning and gives the company a clearer response when a consumer asks for details.

The survey offers a useful signal, yet it should be read within its design limits. ContentEngine used two separate nonprobability samples of 223 U.S. adults each. Respondents opted into online survey panels, and the results were not weighted to represent the U.S. adult population.

The participants were not randomly assigned to the two scenarios. The groups had similar measured demographic profiles, but unmeasured differences may have influenced the results. The research therefore shows an association between the scenario and the responses rather than a definitive estimate of the causal effect of disclosure timing.

The later-discovery version also told respondents that the ad had failed to disclose its AI use. That wording directly highlighted the nondisclosure and may have increased feelings of being misled. The survey also described complete AI creation, so the findings may not apply to every campaign that uses an automated tool in a limited way.

The purchase itself was hypothetical. Respondents did not see a real advertisement, spend real money or use a real product. Stated trust and repeat purchase intent can differ from behavior in a live market.

Those limits call for careful interpretation. They do not make the result irrelevant to advertisers. The pattern matches a sensible consumer expectation and points to a low-cost operational choice: tell people about meaningful AI involvement before the ad has done its work.

The strongest business lesson comes from the gap between a successful transaction and a durable relationship. Product satisfaction helped every respondent feel good about the purchase in the scenario. Earlier disclosure still produced higher trust and stronger willingness to buy again. For brands using AI in advertising, transparency belongs at the start of the customer experience, with a human reviewer accountable for what the audience ultimately sees.