To me, AI image generation has always been one of AI’s most enchanting features.
As a self-proclaimed creative who often has more ideas than time, being able to describe a concept in simple terms and watch it instantly transform into a visual felt like magic.
My favourite project involved creating assets for my rec soccer team. What started as simple promotional images grew week by week, eventually evolving into cinematic video trailers that I shared every Friday before our games, a weekly tradition my teammates genuinely looked forward to.
At the time, I felt like I was constantly finding new ways to push the technology. Each week gave me a chance to explore a new concept and create something that would have been too expensive, too time-consuming, or simply impossible for me to produce on my own.
From a professional perspective, the potential was obvious. AI-generated imagery offered quick concept development, creative flexibility, easier adaptation of existing assets, and, of course, the ever-present allure of cost savings.
As the models improved and adoption increased, those use cases started shifting from distant possibilities to realities.
That is where the dilemma became more complicated: what happens when AI-generated imagery becomes an option for public-facing marketing?
Maybe you feel similar to how I did: a little uneasy about the idea, especially when it still felt like unfamiliar territory. That feeling led me to dig deeper.
As I started exploring that reaction, I came across a paper titled “Customer reactions to generative AI vs. real images in high-involvement and hedonic services” by Daniel Belanche, and colleagues.
The article explores potential factors that affect consumer acceptance of AI-generated images in advertising. The authors focus on two key factors: the type of service being advertised and the consumer’s level of involvement in the decision.
Factor 1: Service Type
Factor 2: Consumer Involvement
After analyzing feedback based on these factors, the researchers drew three main conclusions.
First, generally speaking, people were less likely to use or recommend a service when they saw AI-generated images instead of real photos.
Second, that negative reaction became stronger depending on the context. Consumers responded more negatively to AI-generated imagery in hedonic services than in utilitarian ones.
Finally, the researchers identified what they call a “triple interaction effect” between image type, service type, and consumer involvement. In plain language, this means a combination of factors can intensify a consumer’s reaction.
At one end of the spectrum, consumers were most averse to AI-generated images when evaluating high-involvement hedonic services.
Imagine a family searching for the perfect restaurant to celebrate a milestone birthday or anniversary. The meal is not simply about satisfying hunger. It is about creating a memory. In that context, people are likely to care more about atmosphere, authenticity, and whether the experience they see online will match reality. In this scenario, consumers are more likely to be averse to AI-generated images in advertising.
At the other end of the spectrum, consumers were least averse to AI-generated images when evaluating low-involvement utilitarian services.
Imagine someone grabbing a hot dog from a street vendor on the way home. That person is probably looking for convenience and hunger relief, not a once-in-a-lifetime dining experience. In this context, AI-generated images may be received more positively.
It is important to note that the same service may be perceived as either a high- or low-involvement decision depending on the consumer’s scenario. That is where the marketer’s judgment matters.
One practical marketing example is a content shoot.
Suppose you are planning a professional shoot and only have the budget to capture five final images. But the website or campaign needs more than five visuals. In that situation, the question becomes: where does authenticity matter most?
If certain images support more utilitarian parts of the experience, such as a payment page, confirmation screen, or FAQ section, AI-generated imagery may be a reasonable way to fill visual gaps.
But if the images are being used to sell the core experience or service promise, such as the atmosphere of a restaurant, the feeling of a hotel stay, those are probably the moments where real photography matters most.
To briefly explore why this may be the case, the research draws on Processing Fluency Theory, which suggests that people are more comfortable with information that is easier for their brains to process. Since AI-generated images can sometimes appear “off,” they may require more cognitive effort to interpret, which can lower fluency and trigger skepticism.
In my view, despite the clear evidence in favour of real imagery, there is still merit in considering AI images when they are used appropriately. As covered, it should depend on the service being promoted, the audience’s level of involvement, and the degree of scrutiny and emotional trust placed in the visuals. But these images may still be a practical option for organizations working within specific creative and budgetary constraints.
However, these conclusions reflect only the current state of the technology. How significantly do you feel AI images will advance throughout 2026 and beyond, and will the gap between generated imagery and authentic photography ever fully close?
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Belanche, D., Ibáñez-Sánchez, S., Jordán, P., & Matas, S. (2025). Customer reactions to
generative AI vs. real images in high-involvement and hedonic services. International Journal of Information Management, 85, 102954. https://doi.org/10.1016/j.ijinfomgt.2025.102954
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