AI Research Reveals Just 16% Would Feel No Purchase Regret at All

A new survey suggests that the emotional cost of undisclosed AI advertising can linger even after a customer likes the product. Disclosure timing appears to shape trust, repeat business and how consumers interpret the purchase.

The headline figure focuses attention on a narrow group: only 16% of respondents selected the strongest possible response that they would feel no regret at all after the purchase scenario. The broader results show why that matters. Consumers were told they ended up satisfied with the product, yet many still reported regret, feeling misled or feeling manipulated when they later learned that AI had created the advertisement.

ContentEngine surveyed 446 U.S. adults in two separate groups of 223. Each person imagined seeing an online advertisement for a product they had not planned to buy. The ad persuaded them to purchase it, and the product worked well enough for them to feel satisfied.

The scenarios then split. One group learned before buying that the advertisement’s words and images had been created entirely with AI. The other learned after buying that AI had been used and that the ad had not disclosed it.

That difference in timing shaped the central results. People who learned about the AI later were less likely to trust the advertiser, less likely to buy from it again and more likely to feel misled.

A satisfactory product experience gave every respondent a reason to view the transaction favorably. The purchase worked. The customer received something useful. There was no dissatisfied product, failed delivery or obvious false claim in the scenario.

Even with that positive outcome, regret was common enough to deserve attention. In the upfront-disclosure group, 53.4% said they would regret the purchase a lot or some. In the later-discovery group, that figure rose to 60.5%.

The seven-point difference was not statistically significant after the survey adjusted for its eight comparisons. The result should therefore be treated as a directional finding rather than proof that later disclosure caused more regret.

Still, the pattern fits the larger story. Consumers can be pleased with what they bought while reassessing how the decision was made. The product and the advertising process become separate parts of the experience. Satisfaction answers the question, “Did the item work?” Regret can reflect a different question: “Would the decision have felt the same if the buyer had known how the message was produced?”

The 16% figure in the headline highlights the most absolute form of reassurance, rather than the combined share of people who felt little or no regret. The survey’s reported top-two table combines the two strongest negative response categories, so it does not provide the full distribution for every individual response. That distinction matters when interpreting a result built around a single answer category.

A ContentEngine survey of 446 U.S. adults examined how the timing of AI-advertising disclosure shaped consumer reactions after a satisfactory purchase. Respondents who learned about AI before buying were more likely to trust the advertiser and consider buying again, while those who learned afterward were more likely to feel misled. The findings suggest that disclosure should reach consumers before they make a decision, but they do not prove that timing alone caused every difference. Upfront transparency also does not remove concerns about persuasive tactics, synthetic content or the quality of human oversight.

The clearest differences appeared in measures tied directly to the brand relationship.

The trust gap was 11.7 percentage points. The repeat-purchase gap was 12.6 points. Feeling misled differed by 13 points, the largest gap measured in the survey.

After adjustment for the eight survey comparisons, trust, repeat purchase intent and feeling misled remained statistically significant. Their confidence intervals stayed away from zero under the model used by the researchers.

Those results give advertisers a practical warning. A campaign can produce a conversion and a satisfied customer while creating a weaker foundation for the next transaction. Immediate performance data may show a successful sale. It may not show whether the customer will view the brand as candid enough to trust later.

A later explanation also arrives after the consumer’s decision has already been made. The consumer could reasonably ask whether the disclosure would have affected the purchase, the amount paid, the credibility of the claims or the willingness to share personal information.

A disclosure that reaches consumers after the decision cannot give them the same choice as a disclosure that appears before the decision.

The survey does not support a simple formula in which adding an AI label solves the trust problem.

Among people who were told upfront, 57% still felt misled a lot or some. About 62.3% felt manipulated at least somewhat. Those figures remained high even though the scenario gave them the information before purchase and told them the product was satisfactory.

Several features of the scenario may explain that discomfort. The purchase was unplanned, and the advertisement persuaded the respondent to make it. That setup may make the ad feel manipulative regardless of whether AI was involved. The scenario also described an advertisement created entirely with AI, a stronger use case than an ad that uses AI for background removal, image resizing, translation or early copy suggestions.

The survey did not ask respondents why they felt misled or manipulated. It cannot separate discomfort caused by the AI disclosure from discomfort caused by persuasive advertising or an impulse purchase.

That uncertainty should shape how brands read the findings. An upfront label can improve the consumer’s information position, but it does not automatically make the creative credible, fair or appropriate. Consumers may still object to exaggerated claims, emotional targeting, synthetic testimonials or an ad that appears designed to bypass careful judgment.

The most important lesson is not that every AI-generated advertisement requires the same label. It is that consumers care about whether AI involvement could change how they interpret the message, and whether the brand accepts responsibility for the result. A pre-purchase disclosure gives people information when it can still affect their choice; a named human reviewer gives that disclosure credibility. Brands that treat both as part of creative governance are more likely to protect the relationship beyond the initial conversion.

Respondents placed strong value on both transparency and accountability.

Across the two samples, 90.1% said it was very or somewhat important for brands to tell consumers when an advertisement had been created entirely using AI. Another 88.3% said it was very or somewhat important to know that a person had reviewed and approved the advertisement before publication.

The human-review result was almost identical across the groups: 87.9% among people told upfront and 88.8% among people who learned later. The difference was less than one percentage point.

These are related but separate expectations. A label answers how the advertisement was made. Human review answers who remains responsible for the finished message.

A meaningful review should cover more than grammar or visual quality. A person reviewing an AI-generated ad should check:

A nominal approval step leaves the main accountability question unanswered. If a brand cannot identify who reviewed the ad, what they checked and what standards they applied, the label may provide transparency without much confidence behind it.

Consumer expectations are developing alongside formal guidance. The European Commission’s FAQ on transparency obligations under Article 50 of the EU AI Act discusses responsibilities for certain AI systems and clarifies that employees acting under a legal person’s authority are generally not treated as separate deployers. The legal details depend on the system, use and jurisdiction, so the rule should not be treated as a universal requirement for every U.S. advertisement.

The direction is still relevant to marketers. Organizations using AI under their authority need clear ownership of the output. A brand cannot treat an outside tool, agency or automated workflow as a substitute for human responsibility.

The Interactive Advertising Bureau’s AI Transparency and Disclosure Framework V2 takes a risk-based, materiality-driven approach to deciding when and how AI involvement should be disclosed in consumer-facing advertising and marketing. That approach is useful because AI can play very different roles. Generating an entire campaign asset raises a different transparency question from using software to adjust the dimensions of an image.

For consumers, the important detail is whether AI involvement could change how they interpret the ad. If an artificial voice appears to be a real spokesperson, if a generated image depicts a product inaccurately or if automated personalization affects the message they receive, disclosure may carry more weight than it would for a minor production task.

The findings point to a meaningful relationship between disclosure timing and consumer reaction, but they do not establish a clean causal effect.

The two scenarios used separate nonprobability samples rather than randomly assigning people within one experiment. The samples had similar measured demographic profiles, but they could still differ in unmeasured ways. Respondents opted into online survey panels, and the results were not weighted to represent all U.S. adults.

The later-discovery scenario also included a direct statement that the advertisement had failed to disclose its AI use. That wording may have increased feelings of being misled independently of the timing itself. A real consumer might discover AI involvement through a brand FAQ, a news report, a platform label or a third-party investigation, each of which could produce a different reaction.

The scenarios were hypothetical. Respondents did not see an actual advertisement, spend money or use a real product. Stated trust and purchase intent can differ from behavior at checkout.

The survey also tested only the strongest version of AI involvement: the words and images were described as created entirely using AI. The result may not apply to every form of AI assistance. A human writer who uses AI to brainstorm headlines presents a different situation from a campaign in which the copy, product imagery and spokesperson are all synthetic.

Those limits narrow the claim. The results do not show that every undisclosed AI feature will damage loyalty by the same amount. They do show that consumers notice the difference between learning before a decision and learning after it, at least in this scenario.

Advertisers evaluating AI campaigns should add trust measures to the usual performance dashboard. Click-through rate, conversion rate and cost per acquisition can describe what happened during the campaign. They do not fully capture how customers feel once the production process becomes known.

A practical review can include the following steps:

The wording should match the production reality. If AI generated the text and image, the disclosure should say that. If a person substantially edited the material, the brand can explain that as well, provided the explanation does not blur who or what created the final content.

A short pre-purchase notice will not satisfy every consumer. Some people will continue to prefer human-made advertising, and many will judge the ad on its claims and persuasive style as much as its production method. Clear disclosure gives them information before they decide. Human review gives the brand a defined point of accountability.

The survey’s most useful lesson sits in the gap between a successful sale and a durable relationship. Consumers may like the product and still reconsider the advertiser after learning that AI shaped the message without their knowledge. Brands that disclose early have a better chance of preserving trust, while brands that wait may discover that a completed purchase was only a short-term win.