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Design for User Trust in a World with Generative AI

Zoë Zapata

Oct 8, 2026

It used to be common sense to trust in print and not believe everything you see on the Internet. But today, people are wary of any medium that uses generative AI. By mid-2025, ChatGPT use grew by 113% year-over-year. Since ChatGPT launched in 2022, generative AI has moved quickly from novelty to everyday tool. With a world now filled with generative AI use, trust in information has changed. Generative AI has affected every source of information, from a generative AI tool for Washington Post readers to AI-generated content used in education. When content can be altered without any indication, establishing user trust is vital, whether the designer uses generative AI or not.


Designers today must tread a fine line between using the newest, advanced technology, creating reliable and trustworthy creative solutions. Whether it is a website or a printed pamphlet, distrust in generative AI use is well-earned, because this technology cannot guarantee 100% accuracy. Most view generative AI as a brain that can discern what is an appropriate answer to the user’s prompt. But in actuality, generative AI functions by generating probabilistic, reasonable responses based on data deemed relevant by algorithms. Generative AI is not thinking; it is choosing the most probable response that fits your request.


This inaccuracy cannot be resolved by the designer alone, but we can use design to help re-establish trust between the user and the information. As we all adapt to this evolving technology and its integration, how can we deliver user experiences that keep up with the pace of generative AI adoption while still preserving user trust? The answer lies in designing for the skeptical user.


Design for Skepticism

The spike in generative AI adoption over the past 2 years has led many to consider whether the information they see is AI-generated. To design for the skeptical user, designers should:

Remember visual design alone cannot establish trust.

Polished visual design and branding are no longer solo indicators of a trust-worthy experience. Whether it’s a clean UI website or a perfectly branded poster, decent visual design is basic output for any generative AI model as of mid-2026. But credibility requires more authentic user experience design choices. Content in any digital experience is a key indicator of reliability, including real photos and media and real people for teams and testimonials; these signal to the user that this is a credible experience.

When you ask users to invest their time, money, or effort into your project, it’s imperative to show them that your work is genuine. Demonstrating your process, whether for a product or creative piece, helps establish credibility by showing the real, human effort and involvement of actual people. Recent marketing trends, such as Apple's "Behind the Scenes: An Apple Event Shot on iPhone," reflect a growing demand for “proof” of authenticity, highlighting the importance of transparency in fostering user trust.

Prioritizing authenticity garners greater trust from users. Users are shown to view human-made content more favorably, regarding it as credible and of higher quality than automated content. Authenticity can be encouraged through a range of creative approaches across all mediums:

  • Clearly label sources to establish credibility for any information presented.

  • Highlight the human element of a project by sharing your company story, providing an about page, and including team photos to demonstrate there are real people behind the work.

  • Feature testimonials from real individuals to further reinforce credibility.

Generative AI use in research is highly scrutinized, with it regarded as highly inaccurate and embedded with false information and social biases based on its dataset. Generative AI is constrained in finding relevant and chance-driven information, unable to discern between stereotypes and facts. AI-generated user personas and research analyses carry social biases, creating personas and conclusions based on racism, sexism, and other inequalities. Using generative AI in research must be done sparingly and, at best, in an administrative manner. Refining text, formatting information, and brainstorming methodologies are ways to use generative AI in your workflow while not compromising the reliability of your research. 

The visual giveaway of using generative AI in design is the overused layout and motifs seen in every poster and social media ad. 

The fault of generative AI is that it is never truly creating something “new” but creating the most reasonable design based on data inputted to the model.

AI-generated or assisted websites, posters, and other creative media fall into the same repeated design choices. Similar typography, layout, and diction create a monotonous experience where all posters, ads, websites, and apps look the same.

Be aware of falling into restrictive design and challenge yourself, even when using generative AI. Use generative AI to support creative workflows, prototypes, or to polish ideas. 

When designers rely on generative AI to ideate instead of skill, they fall into the same restrictive design mistakes people judge AI-generated content for.

Crediting AI-generated or AI-altered images, video, text, and other content further builds user trust and holds the creator accountable for using AI-generated content. Labeling AI-generated or altered content removes the mental confrontation of whether the content before the user’s eyes is human-made or computer-made. Transparency about AI-generated content allows the user to make an informed decision about whether to trust the information they are interacting with.

Trust in Design

Designing for a world of distrust isn't easy, but it is achievable. Generative AI use is more prevalent than ever, and whether the AI bubble will pop or not, creatives must anticipate this skepticism and design ahead of it. Emphasizing transparency in the design process and creating authentic experiences are essential for garnering trust. By creating a thoughtful, honest user experience, we can design for the skepticism people feel more than ever.

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