AI use alone does not prove a product is poorly made. But when an ad looks careless, viewers may read that carelessness as a clue about the brand behind it. Lindsay Brillson, Head of Brand and Content at Pika, says that risk can be greater for newer brands without an established reputation to counter a bad first impression.
Why a bad ad can reflect on the product
Brillson’s point is about perceived care, not a demonstrated link between AI and product quality. If a brand’s ad looks rushed or poorly directed, a viewer may wonder whether the company is equally careless elsewhere: “If they cheaped out here, what else are they cheaping out on?” That phrase comes from the framing of the Tom’s Guide interview, not from a measured survey response.
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Established brands may have years of reputation to buffer a weak campaign; a newer business may have less context working in its favor. Brillson explicitly cautions against claiming that an ad’s effect on sales or business results is known from the outside: “No one outside of Coca-Cola knows what those ads actually did to the business, so I won’t pretend that I do.” Read the Tom’s Guide interview with Brillson.
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What makes an AI ad look careless
Obvious generation glitches can undermine confidence, including faces or hands that morph, faulty lip-sync, and text that resembles words without spelling them correctly. But Brillson says the less obvious signals may matter just as much: generic casting, art direction or locations; inconsistent lighting or wardrobe; and camera movement that has no clear narrative purpose.
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Those choices can make an ad feel unconsidered even when there is no conspicuous technical error. The issue, in this view, is not simply whether AI was used, but whether people exercised judgment and craft in shaping the result. Brillson sums up the shift this way: “The artifact hunting phase has a limited shelf life.” As generation flaws become less noticeable, she argues, viewers will pay more attention to whether the idea is distinctive, feels true to the brand, and is elevated by its execution.
Consumer attitudes are more mixed than ad executives expect
The Interactive Advertising Bureau’s 2026 report describes a gap between industry expectations and consumer views. The IAB says 82% of ad executives believed Gen Z and Millennial consumers felt very or somewhat positive about AI-generated ads, while 45% of those consumers themselves reported a positive view. These figures concern different groups’ opinions; they are not a measure of ad quality or a poll of everyone. See the IAB report, “The AI Ad Gap Widens”.
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Disclosure does not automatically translate into resistance to buying. In the same report, 73% of Gen Z and Millennial consumers said knowing an ad was created with AI would increase or make no difference to their likelihood of purchasing the advertised product or service. That is a response about stated likelihood, not evidence that disclosure increases actual purchases or that the result applies to all consumers.
Ad performance depends on the brief and the measure
Findings from Ipsos offer a reason not to treat “AI-made” as a quality verdict in either direction. One Ipsos study tested 20 ads—10 human-created and 10 AI-generated—with 3,000 U.S. consumers. A separate Ipsos research release reported that human-made ads exceeded its sales-validated benchmark by 11 points on average, while AI-made ads fell five points below it. Those are benchmark-index results, not percentages or universal forecasts. The release also said AI performed better on straightforward, product-driven briefs than on storytelling, emotional work or briefs requiring a distinctive point of view. Read Ipsos’s study summary and the release describing its sales-validated benchmark findings.
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Together, these findings suggest a more useful way to compare ads than asking only whether AI was involved:
- Product depiction: Does the product remain accurate and visually consistent from frame to frame?
- Craft and brand specificity: Do the casting, setting, art direction, lighting, wardrobe and camera movement feel deliberate and recognizably suited to the brand?
- Strength of the idea: Is the ad clear and compelling? Does it need a story, emotional response or distinctive point of view, or is it a straightforward product demonstration?
- Audience response and outcome: Who was asked, and what was measured—an opinion, stated purchase likelihood or a sales-related benchmark?
The Ipsos findings concern particular samples, tests and performance measures. They do not establish how every AI ad will perform across markets, formats or brands, and they do not show that AI use itself causes people to judge a product as inferior.
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Brillson’s checks before an ad goes live
Brillson recommends treating creative oversight as part of the work, rather than assuming a tool will supply it. Her interview advice is not a formally validated standard, but it offers practical questions for a team reviewing an AI-assisted campaign:
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- Assign real creative ownership. Make clear who is responsible for the idea and the finished work.
- Test the idea without the tool. Ask whether the concept would still exist if AI had not been used.
- Get an unprimed reaction. Show the ad to people without first explaining how it was made.
- Check brand identity. Ask whether the work is unmistakably associated with the brand, rather than generic.
- Review consistency. Inspect the product across frames, along with details such as lighting and wardrobe.
- Find the likely ridicule point. Identify the frame most likely to distract viewers or become a joke, then decide whether it needs correction.
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