Consumer preferences between human and AI design vary depending on the type of product, the context and need of a user, and whether the customer is aware of who designed the product. Learn more about how to correctly include AI tools in the design process.
Generative AI has brought a shift in the design of interfaces and products. A basic question still exists: Do consumers favor designs by artificial intelligence or by humans? An increasing amount of empirical data indicates that the answer is not so simple.
In April 2025, Adobe Firefly crossed the huge number of 22 billion created assets, which is essentially the same as all of the world’s best graphic designers working continuously for multiple years, compressed into just months of machine output. The market for AI design was estimated at $5.68 billion in 2024 and is expected to grow to $98.66 billion by 2035.
What is Human-Centered Design?
In order for any educational project to be successful, designers must take into account the demands of students, teachers, and administrators. This applies to official initiatives like degree programs and classrooms as well as informal ones like home tutoring programs and self-learning courses. In light of this, human-centered design is an iterative design methodology that places a high value on end-user empathy.
In order to develop solutions that genuinely benefit the user group, it centers the design process around them. In addition to recognizing and highlighting the user’s needs, desires, and constraints, the HCD method establishes the user as the standard for success and performance.
Human-Centered Design Process and Principles
A methodical way to develop user-friendly learning experiences is offered by the human-centered design methodology. Four distinct concepts serve as the foundation for a human-centered design strategy that is both accessible and strategic:
Empathy: comprehending the circumstances and needs of the user
Iteration: designing by prototyping and getting input
Collaboration: incorporating a variety of stakeholders (students, teachers, designers)
Accessibility: making the product useful for as many individuals as feasible, including those with disabilities
What to keep in mind when using AI in the design process
The majority of us are familiar with the phases involved in a conventional product design process. You start by spending time getting to know the user. You conduct exploratory research to find out how they currently resolve issues, identify pain points, and identify areas where the experience could be improved.
The next step is to establish the objectives, tenets, and success criteria for a new solution. The group comes up with a number of potential ideas that fit the success criteria. After that, you create a low-fidelity prototype to test the idea and gather input before going on to a higher-fidelity prototype or launch.
While certain essential stages have been added, the design process for AI is similar. Some of these processes are specific to AI-based product experiences, while others are essential for AI but can also be useful when developing other products.
Empathizing with users is important when designing for AI, but you also need to carefully consider the future you want to see and the AI/human cooperation you want to establish. Along with defining the project’s needs, you must also specify the AI capabilities you intend to use and determine whether they are yet developed enough to be put to use. Building a solution that satisfies the use case is not enough while brainstorming; you also need to consider how AI will obtain the necessary data and develop over time.
Lastly, when you start developing the concept, you must take the time to consider how to reduce the unexpected negative effects of this tool’s existence in the world or the activities of bad actors that use it.
All of this does not mean that AI’s contribution to design is exaggerated.
When AI applies visual criteria to thousands of assets, consistency across large-scale branding operations becomes feasible. It would take massive amounts of time and money if it were to be done by hand. Human labour alone would not allow for the type of personalization at scale that a company like Netflix has turned into a competitive advantage.
According to researchers, 47.5% of designers save four or more hours per week by integrating AI into their workflow. These hours are then used for strategy and the aspects of design that actually require human intervention to succeed.
However, CHI 2025 researchers found a conflict: when AI technologies are introduced too early in the design process, the results aren’t very innovative.
Early-stage design is usually experimental and features crude drawings and ambiguity in designs. AI will always produce a polished result, which might limit creativity for human designers.
If AI is introduced too soon, it will be a great solution to the wrong issue.
The Only Sensible Conclusion
Budget, timeline, medium, and audience limitations have always been a part of the design profession. Instead of creating a new designer to compete with, AI can help with the repetitive tasks while freeing up your time for creative jobs.
Going into the future, designers relying only on AI tools and those who don’t use them at all will both be at a disadvantage to someone who uses these tools smartly and as an aid to the design process.
FAQs
Does AI-generated design perform better than human-generated design?
When it comes to functional conversions, like marketing or landing page design, AI occasionally performs better than humans. In a 2026 test, An AI landing page had a conversion rate of 80.65% compared to a human-designed page, which had a score of 55.68%.
Why are users suspicious of AI-generated designs?
Uncertainty. 76% of consumers claim they are unable to tell with certainty if an image was produced by AI or is real. This translates into designs. Even if the design performs better objectively, people tend to lose faith when they discover it was made by AI.
How should AI tools and human creativity be used into the design process?
Humans define the problem and carry out the creative tasks. AI handles massive amounts of data as well as tedious and repetitive tasks. Make the most of both. Start with human research, use AI to optimize it, and then test it on actual customers.
How do customers react when a design is revealed to be made using AI?
In a bad way, at the moment. Particularly when it comes to art, revealing that the work was created by AI afterward diminishes favor and trust. The unfavorable response is marginally lower for things that are high-tech, inventive, and visually appealing.
Will AI tools replace UX designers?
Human designers are not going anywhere. AI cannot define problems, doesn’t have empathy, cannot develop a strategy, or validate its results. All of these are important factors in the design process and can only be carried out by a human.
