Consumer Poll Reveals Strong Demand for AI Ad Disclosure

A survey of 446 U.S. adults found that consumers responded more favorably when an advertisement disclosed its use of AI before a purchase. The results also show that disclosure alone may not settle concerns about manipulation or accountability.

The timing of an AI disclosure can shape how consumers judge a brand after a purchase, even when the product performs well. In a ContentEngine survey, 76.7% of respondents who knew an ad was entirely AI-generated before buying said they would trust the advertiser a great deal or a fair amount. That share fell to 65.0% among respondents who learned about the AI use afterward.

The same pattern appeared in repeat purchase intent. Nearly 80% of the upfront-disclosure group said they would be very or somewhat likely to buy from the advertiser again. Among people who learned about the AI later, the figure was 67.3%.

The practical message for brands is direct: consumers want information about AI before an ad influences a decision. A disclosure added after the sale may explain the production process, but it arrives after the point when the information could have affected the consumer’s choice.

ContentEngine used two separate online samples of 223 U.S. adults. Each respondent read a hypothetical scenario about an online ad for a product they had not planned to buy.

Both scenarios described a successful outcome. The ad persuaded the respondent to make an unplanned purchase, and the respondent was satisfied with the product after using it. The product experience was held constant in the basic setup.

The difference involved the timing and framing of the AI information:

The respondents then answered questions about trust, future purchases, regret, feeling misled, recommendations, manipulation, AI disclosure and human review.

The scenario given to the later-discovery group included a clear statement that the ad had failed to disclose its AI use:

The advertisement didn’t disclose this when you saw it.

That wording matters. It may have shaped feelings of being misled directly, rather than merely measuring a neutral response to learning that AI had been used. The survey therefore offers a strong warning about hidden AI use, while its design limits claims about disclosure timing as an isolated cause.

A survey of 446 U.S. adults found broad support for disclosing substantial AI involvement in advertising before a consumer makes a purchase. Respondents who learned about an ad’s AI use after a satisfactory purchase reported lower trust, weaker repeat-purchase intent and stronger feelings of being misled than those who saw the disclosure upfront. The findings also show strong support for human review, while the survey’s hypothetical scenarios, separate samples and nonrandom online panels require the results to be interpreted as an association rather than proof that disclosure timing caused every difference.

Trust was one of the strongest differences between the two groups. Among respondents who received the information upfront, 76.7% said they would trust the advertiser a great deal or a fair amount. The later-discovery group registered 65.0%, a gap of 11.7 percentage points.

Repeat purchase intent moved in the same direction:

Those figures carry a useful business lesson. A brand can generate an effective first purchase and deliver a satisfactory product while still weakening its chances of earning a second purchase. Immediate conversion gives an incomplete view of the ad’s performance when consumers may later question how the message was made.

The adjusted statistical analysis found that the differences in trust and repeat purchase intent remained significant after accounting for the survey’s eight comparisons. The reported 95% confidence intervals stayed away from zero for both measures under the statistical model used by the researchers.

Recommendation intent also favored the upfront group, but the difference was smaller and less conclusive. About 73.1% of respondents who knew about the AI use in advance said they would recommend the advertiser, compared with 67.7% of those who learned later. That 5.4-point gap did not remain statistically significant after adjustment.

The largest measured gap involved feeling misled. Seventy percent of respondents who learned about the AI use afterward said they felt misled a lot or some. The corresponding figure among respondents informed before the purchase was 57.0%.

That 13-point difference remained statistically significant after the comparisons were adjusted. It reinforces why timing matters. Information received before a decision can be part of the decision. Information received afterward can feel like a correction to a decision already made.

Regret showed a similar direction but weaker evidence. The later-discovery group was more likely to report regretting the purchase, at 60.5% compared with 53.4% in the upfront group. The 7.2-point difference did not remain significant after adjustment.

The product’s success did not erase the disclosure issue. Every respondent was told they were satisfied with the product, so the survey describes a situation in which the consumer’s practical experience went well. That detail makes the trust finding more pointed: satisfaction may reduce some complaints about the product while leaving concerns about the brand’s conduct intact.

AI disclosure should be treated as a form of consumer control, not merely as a compliance box. Giving people clear information before an ad influences them lets them decide how much weight to give an automated message, while meaningful human review establishes who is accountable for the final claims and creative. Brands that disclose vaguely, bury the notice or treat approval as a technicality may win the transaction while weakening the relationship that follows.

Upfront disclosure produced better results on trust, future purchases and feeling misled. It did not make consumers entirely comfortable with the scenario.

Among those told before buying that the ad was entirely AI-generated:

Those responses suggest that consumers may react to several parts of the experience at once. The ad persuaded them to make an unplanned purchase. The ad was described as entirely AI-generated. The disclosure may have changed how they interpreted the persuasive process, even though the product met their expectations.

The survey did not ask respondents to explain why they felt misled or manipulated. That leaves several possible interpretations. Some respondents may object to AI-generated creative itself. Others may associate the technology with a lack of human accountability. Some may simply dislike being persuaded into an unplanned purchase and view the AI disclosure as evidence that the ad was designed to influence them in a calculated way.

Brands should read this part carefully. A visible label can address one information gap while leaving broader questions about the ad’s claims, targeting and persuasive tactics. Transparency gives consumers more context. It does not automatically make every advertising approach feel acceptable.

Support for disclosure was broad across both groups. Of all 446 respondents, 90.1% said it was very or somewhat important for brands to tell consumers when an advertisement had been created entirely using AI.

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

The results were especially consistent for human review:

That consistency suggests that consumers see two related but separate responsibilities:

A label such as made with AI tells the audience about the production method. It does not tell them whether anyone checked the factual claims, reviewed the images for misleading details or considered whether the targeting was appropriate. Human approval provides a separate signal about responsibility, although the survey did not test what consumers would consider meaningful review.

A disclosure placed after the transaction cannot serve the same purpose as one shown before the ad has influenced the consumer. The earlier notice gives the consumer a chance to weigh the information. The later notice mainly gives the brand a chance to explain itself.

That distinction also fits existing advertising guidance. The Federal Trade Commission’s digital disclosure guidance says disclosures needed to prevent deception should be clear and conspicuous. The FTC has also warned in AI-related policy materials that a disclaimer hidden in fine print may not be enough when the information matters to a consumer’s understanding.

The European Commission’s guidance on AI transparency obligations provides context for organizations operating under the EU AI Act, including transparency obligations under Article 50. The IAB AI Transparency and Disclosure Framework offers industry guidance intended to balance useful labeling with disclosure fatigue.

Those materials do not create a single global rule for every AI-assisted ad. The relevant obligation can depend on the jurisdiction, the type of system, the content of the ad and the way the disclosure appears. The consumer response in this survey points to a practical standard that brands can apply across many settings: disclose material AI use where the audience will see it before making a decision, and make the notice understandable enough to matter.

The findings are useful for identifying a trust risk, but they should not be treated as a nationally representative estimate of all U.S. adults.

The two samples were nonprobability online panels. Respondents opted into SurveyMonkey Audience rather than being randomly selected from the U.S. population. The results were not weighted, and the researchers did not report a conventional margin of sampling error.

The respondents also were not randomly assigned to the two scenarios. Each tranche was fielded as a separate sample. The measured demographic characteristics did not differ significantly between the groups, but similar age, gender, income, device and region profiles cannot rule out differences in other traits.

The scenario itself changed more than timing. The later-discovery group was explicitly told that the ad had not disclosed its AI use. That language could have increased feelings of deception or unfair treatment. The survey therefore supports an association between later discovery and less favorable responses, with a plausible explanation for the gap, rather than a clean experimental estimate of timing alone.

Other limits include the following:

These constraints make the strongest finding narrower and more useful: when consumers are told about undisclosed, fully AI-generated advertising only after purchase, their stated trust and willingness to buy again are lower than among consumers who received the information before purchase.

Responsible AI advertising moves transparency and accountability to the point of influence.

Brands using AI in advertising can turn the survey’s findings into a straightforward review process.

The disclosure should appear with the ad or in the same user experience, before the consumer acts. A post-purchase email, help-center explanation or buried terms page cannot provide the same decision-relevant information.

Placement matters as much as wording. A label that disappears on mobile, competes with a crowded caption or requires several clicks may fail to reach the audience. The FTC’s clear-and-conspicuous standard is a useful benchmark for thinking about visibility, even when a particular campaign falls outside a specific legal requirement.

A brand should avoid using a broad label that gives consumers the wrong impression about the production process. Entirely AI-generated copy and images present a different disclosure question from AI-assisted editing or automated ad variation.

The label should match the actual workflow. It can identify whether AI generated the copy, images, voice, video or targeting elements, while making clear where people remained involved.

A human approval step should involve more than checking a box. Reviewers should evaluate:

The survey measured consumer interest in human review, not the effect of a specific review process. Brands should therefore define who owns the approval, what that person checks and how the decision is recorded.

A campaign dashboard focused only on clicks and purchases can miss a delayed reputation problem. Brands should consider measuring trust, perceived honesty, willingness to buy again and feelings of manipulation alongside immediate performance.

A useful test might compare reactions to the same creative with different disclosure placements, while keeping the wording and audience as consistent as possible. Follow-up questions can ask whether consumers understood the label and whether it changed their view of the brand.

The upfront group still reported substantial discomfort. That result gives brands a reason to review the ad’s underlying persuasion, not simply its label.

A transparent ad can still make unsupported claims, exploit a vulnerable audience or create pressure to buy. Disclosure should sit within a broader review of advertising quality and consumer impact.

The survey captures a tension that many brands will have to manage as generative tools become part of routine creative work. Consumers may accept the efficiency of AI in production while still wanting to know when it shaped the message and whether a person took responsibility for the final result.

The strongest support in the data was for information, not for a particular opinion about AI. Nine in ten respondents considered disclosure important, and nearly nine in ten wanted to know about human approval. At the same time, the upfront group still reported feeling misled and manipulated at meaningful rates.

That combination gives brands a more realistic standard to work toward. Consumers are asking for visibility and accountability before they decide. A label can meet part of that request. A responsible review process, truthful claims and sensible persuasion determine whether the disclosure leads to lasting trust.