Artificial intelligence has quickly become part of the modern designer’s toolkit. Over the past two years, a wave of AI-powered tools such as Galileo AI, Figma’s built-in assistant, and Uizard have promised to turn text prompts into ready-made layouts, icons, and prototypes. What used to take hours can now appear on the screen in seconds.
For Osman Gunes Cizmeci, a New York–based UX and UI designer known for his commentary on emerging design trends, this transformation represents a fundamental shift in how creative work happens. “AI is great at creating possibilities, but the designer still decides what belongs,” he says. “The real skill now is editing, not generating.”
A Shift in the Creative Process
Generative AI has changed the starting point of design. Instead of opening a blank canvas and sketching by hand, many designers now describe a concept in natural language. The system generates wireframes, typography, and visual hierarchies that can be refined or discarded.
“It feels more like directing than drawing,” Cizmeci explains. “I can describe a tone or behavior instead of specifying every detail. The AI interprets, and I react to what it creates.”
This new workflow allows for broader exploration. Designers can now prototype several creative directions simultaneously, test them quickly, and choose the best direction to refine. “It encourages experimentation,” Cizmeci says. “When generating ideas takes seconds, you become less protective of any single version. That’s liberating.”
The result is more conversation and iteration early in the process. In collaborative sessions, design teams can test multiple approaches instantly, allowing product managers and engineers to see variations in real time. “It has changed how teams talk about ideas,” he adds. “Instead of debating hypotheticals, we’re looking at live examples and adjusting them together.”
Where the Tools Fall Short
Yet the excitement around generative design comes with clear limits. These systems are trained to recognize patterns, not understand context. They can reproduce the visual language of a product but rarely understand why that language exists.
“You can tell an AI to create something welcoming, and it will produce rounded corners, soft colors, and friendly typography,” Cizmeci says. “But tone is about intention, not appearance. A layout that looks friendly can still feel cold if the interactions are impersonal.”
Accessibility remains another blind spot. Many AI-generated mockups look sleek but fail to meet contrast standards, omit alt text, or use animations that create unnecessary cognitive load. “They reproduce design trends, not human needs,” Cizmeci notes. “Designers have to review every result critically, the same way they review code.”
Ethics also plays a growing role in how AI outputs are evaluated. Generative systems trained on biased datasets risk perpetuating stereotypes or exclusionary patterns. “AI doesn’t have values,” he says. “It mirrors what it has seen. That’s why judgment still matters.”
Collaboration, Not Replacement
Cizmeci prefers to think of AI as a creative partner rather than a competitor. “I see it as a junior collaborator that works fast but needs direction,” he says. “It can generate options, but it doesn’t understand empathy, responsibility, or tone. Those are still human skills.”
In his view, the most valuable applications of AI occur within existing design systems. When generative tools are trained on a company’s visual language, accessibility standards, and brand principles, they can create drafts that reflect identity and intent. “If AI understands the rules of a design system, it stops being a toy and becomes an amplifier,” he says.
He believes the next few years will define how AI fits into creative work. “Designers who know how to use these tools well will be the ones who can move between automation and authorship,” Cizmeci explains. “They’ll understand when to generate and when to guide.”
For now, he sees the technology as an accelerant, not a replacement. “Good design has never been about efficiency alone,” he says. “It’s about clarity, empathy, and accountability. AI might change how we get there, but those values don’t change.”