AI-generated ads can weaken brand trust for some Canadian consumers, but the effect is not automatic.
The clearer warning is that many Canadians become more cautious when they know AI was used to create advertising images or video. At the same time, a significant group reports no change in trust, and a smaller group becomes more trusting. The outcome therefore depends on more than the tool itself. It also depends on how the ad looks, what it claims, how personal it feels and whether someone has taken responsibility for the final result.
For Canadian businesses, the practical question is not simply whether to use AI. It is whether AI-assisted production is being directed by a professional who understands the brand, the audience and the risks of publishing weak or inaccurate creative work.
What Canadian Consumers Are Saying
The Ipsos AI Monitor 2025 provides a stronger Canadian reference than broad global statistics. Ipsos surveyed approximately 1,000 Canadian adults aged 18 to 74 between March 21 and April 4, 2025 as part of a 30-country online study.
When Canadian respondents considered the wider use of AI in advertising images or video:
- 45% said they would trust the companies and brands using it less.
- 41% said their trust would remain the same.
- 15% said they would trust them more.
The percentages total 101% because of rounding.
The same study found a stronger preference when respondents were asked about advertising such as television commercials and video ads on YouTube or TikTok. In Canada, 73% preferred human-driven content, 17% had no preference and 10% preferred AI-driven content.
These figures do not prove that an AI-assisted campaign will fail. They do show that businesses are working in an environment where the use of AI may introduce doubt before the audience has even considered the offer.
AI Use Is Not Automatically the Trust Problem
An advertisement can involve AI without looking careless, misleading or disconnected from its brand. A designer might use AI to test compositions, develop background concepts, create early visual variations or speed up repetitive production tasks.
The problem begins when generation replaces direction.
An AI tool can produce a polished image without knowing whether it communicates the intended message, follows an established visual system or suits the people who will see it. It may create imagery with the wrong emotional tone, inconsistent products, inaccessible text, distorted details or cultural references that do not fit the market.
These are design and review problems, not proof that AI should never be used.
The distinction matters because audiences normally see the final advertisement, not the production process behind it. When the finished work feels generic, inaccurate or inconsistent, the brand receives the criticism. The software does not carry that responsibility.
The Difference Is Professional Creative Direction
Human-directed AI creative is not simply an AI image followed by a quick logo placement. Professional graphic design begins before anything is generated.
A designer defines what the advertisement needs to communicate, who it is meant to reach and how it should relate to the broader brand. AI may assist with production, but the designer remains responsible for the decisions that shape the final work.
Concept and message
The visual idea must support the campaign objective. An attractive image is not enough if it draws attention away from the product, misrepresents the service or makes the message harder to understand.
A designer connects the concept to the offer, the audience and the next action. This is especially important in advertising, where a viewer may decide within seconds whether the message feels relevant or credible.
Brand system and visual consistency
Typography, colour, layout, image treatment and logo use should make the advertisement recognizable as part of the same brand. AI-generated visuals can vary dramatically between prompts, even within one campaign.
Professional direction creates a consistent system across social posts, display ads, landing pages and print materials. Without that system, individual assets may look polished while the campaign as a whole feels disconnected.
This issue is examined further in the article about AI and templates making brands feel interchangeable.
Emotional and cultural suitability
An advertisement may be technically correct and still feel wrong for its audience. Facial expressions, gestures, clothing, locations, symbolism and humour can carry different meanings across communities.
A designer reviews those elements in context rather than assuming that a plausible image is an appropriate one. This is particularly relevant for Canadian campaigns that may address multilingual and culturally varied audiences.
Accessibility, accuracy and accountability
AI-generated assets still require human checks for readable contrast, clear hierarchy, legible type and formats that work across different placements. Product details, prices, packaging, people and written claims must also be reviewed for errors.
Someone must make the final decision to approve or reject the work. That accountability cannot be assigned to the generation tool.
A human-directed graphic design process keeps responsibility with the designer and business using the asset. The same principle can be seen in a branded Instagram campaign design, where individual posts belong to one coordinated campaign rather than functioning as unrelated images.
Advertisers May Be More Positive Than Consumers
Canadian businesses should also be careful about judging public comfort from inside the advertising industry.
The IAB’s 2026 research found a substantial difference between how advertisers expected younger consumers to respond and how those consumers actually responded. In its United States survey, 82% of advertising executives believed Gen Z and Millennial consumers felt positive about AI-generated ads, while 45% of surveyed consumers reported that view.
This is not Canadian evidence, and the study was limited to 505 U.S. Gen Z and Millennial consumers and 104 U.S. advertising executives. It should not be applied directly to all Canadian audiences. However, it identifies a useful risk: the people commissioning and producing AI advertising may be more enthusiastic about it than the people receiving it.
That makes audience research, testing and professional judgment more important—not less.
Personalization Creates a Separate Privacy Concern
The visual quality of an ad is only one part of trust. AI-assisted targeting and personalization can also raise questions about how personal information was collected and used.
The Office of the Privacy Commissioner of Canada surveyed 1,500 Canadians for its 2024–2025 public opinion research. It found that 91% had at least some concern about personal information being used to create marketing profiles based on their interests and personal traits. It also found that 83% had at least some privacy concern when using AI tools.
These results do not measure reactions to AI-generated advertising specifically. They provide important context: an advertisement may feel invasive because of how precisely it targets someone, even when the creative asset itself looks professional.
A strong design cannot compensate for unclear or uncomfortable data practices. Creative decisions, targeting decisions and privacy responsibilities need to be considered together.
Disclosure Does Not Replace Good Design
Transparency about AI use may be necessary in some contexts, but a disclosure label does not automatically create trust.
The Nuremberg Institute for Market Decisions tested reactions to AI-generated marketing content in controlled studies involving participants in the United States, United Kingdom and Germany. In one experiment, participants saw identical advertising content, but one group was told the image was AI-generated. The AI-labelled version received lower responses, particularly on emotional measures, and slightly weaker engagement intentions.
The research is not Canadian and should not be treated as a prediction for every campaign. It does show why disclosure and quality should not be confused. Telling an audience that AI was used does not solve problems with relevance, credibility or emotional connection.
Businesses should make truthful disclosure decisions based on the context, platform and applicable requirements. Regardless of the label, the advertisement still needs a clear idea, careful execution and accountable review.
A Better Role for AI in Advertising
AI can support advertising production without becoming the creative director.
A responsible process keeps people in control of the decisions that affect public trust. The designer establishes the concept and visual system, evaluates generated material, corrects inconsistencies, checks accessibility and accuracy, and confirms that every asset suits the audience and campaign.
The business remains responsible for its claims, targeting choices and final approval.
This approach does not guarantee that every audience will trust an advertisement. No design process can promise that. It does reduce avoidable problems caused by publishing unreviewed content, inconsistent visuals or work that does not reflect the brand.
For Canadian businesses, the lesson from the available evidence is not “never use AI.” It is that speed and volume should not replace judgment. When AI is part of the production process, professional human direction becomes more important because the brand—not the tool—will be remembered for the result.
Planning an AI-Assisted Advertising Campaign?
See Zahra’s human-directed graphic design services for professionally guided campaign concepts, digital graphics and consistent branded assets.
