Exploring AI as a trusted partner in the design process

The new palette of AI tools for product designers

AI has become one of the defining conversations in design today. For many years it lived at the edge of our profession, discussed in articles, tested in labs, imagined in speculative prototypes. Now it sits inside the very tools we open each morning.

When I first tried AI features in Figma, I expected them to be superficial. I thought they might generate some placeholder shapes or generic images, nothing that would truly matter to real product work. Over time I discovered that the changes were deeper. AI is not replacing the craft of design. It is extending it, giving us a wider palette, reducing friction, and helping us focus more on the parts of our work that demand empathy, judgment, and creativity.

This reflection is about what kinds of AI tools product designers can use and in which cases. It is not a catalog of every feature. It is about understanding which tools fit which moments and how to approach them with humility and intent.

Why AI matters in design

Every profession absorbs new technologies. Architects did not stop sketching when CAD appeared. Graphic designers did not stop drawing when Photoshop emerged. In the same way product designers will not stop designing because AI exists.

The importance of AI is not in whether it can generate something new. It is in how it changes the speed, clarity, and possibilities of our work. Industry leaders have already shown this. Figma for example has placed AI at the center of its roadmap. Its First Draft feature gives designers editable layouts from a text prompt. Its Semantic Search surfaces the right components without guessing file names. And tools like Figma Make build prototypes from natural language.

These are not gimmicks. They represent a shift from design as a sequence of manual tasks to design as a flow of ideas where AI takes on the heavy lifting and humans shape direction.

Starting with exploration

The blank canvas has always been one of the hardest parts of design. AI makes it less intimidating. Instead of starting with nothing we can start with something.

In Figma, First Draft provides frames and layouts we can immediately edit. Tools like Adobe Firefly and Midjourney generate imagery that can inspire moodboards or early directions. Research projects like AIdeation allow designers to remix reference images into new concepts.

The goal is not to let AI decide for us. It is to widen the field of possibilities. Designers still bring the taste, the empathy, and the judgment that turn an idea into a product.

Building for reuse

Every team knows the pain of reinventing the same component. A button built one way in one project, another way in a different file. Over time inconsistency slows us down and erodes trust.

AI helps by making reuse easier. Figma’s Semantic Search can find the right component even if it has been named inconsistently. Tools like UXPin’s AI assistant make it easier to adapt design systems without hunting through files.

The value is not only in saving minutes. It is in reinforcing consistency. A reliable component found quickly is one less decision that distracts us from solving bigger problems.

Designing prototypes with speed

Prototypes are powerful because they make ideas tangible. They invite feedback, they reveal gaps, and they let teams move forward with clarity. But they can also take time to build.

AI tools reduce this friction. Figma Make creates interactive flows from a simple description. Framer AI generates entire websites with copy, layouts, and images from prompts. These tools make it possible to move from idea to testable artifact in minutes.

The risk is that prototypes may look finished when they are not. AI makes them polished, but polish is not the same as thoughtfulness. Designers must frame prototypes as explorations, not conclusions.

Removing the weight of repetition

Design involves countless small tasks such as resizing images, exporting assets, or cleaning up layouts. These are important but not inspiring. They consume energy we could spend elsewhere.

AI is well suited to this kind of work. Tools like Remove.bg eliminate backgrounds instantly. Runway edits and adapts media at scale. Figma itself can now automate repetitive actions like formatting or generating variants.

This is where AI feels most like an assistant, taking on what is heavy so we can focus on what is meaningful.

Making sense of research

Design without research is guesswork. Yet research produces oceans of data from interview transcripts to survey results to analytics.

AI helps us navigate this flood. Tools like Dovetail and Notion AI summarize notes, cluster themes, and highlight patterns. A study in Nature Scientific Reports showed how AI supported decision systems can improve cultural adaptability and user satisfaction.

But AI does not understand context the way humans do. It cannot sense hesitation in a user’s voice or cultural nuances in their words. Designers must still interpret, empathize, and decide.

Refining visual style

Visual polish is where craft meets detail. It is also where AI can expand our options.

Generative tools like Firefly create variations on themes. Recraft produces vector illustrations. Khroma suggests color palettes that balance novelty with harmony.

These tools accelerate exploration. But coherence is human work. A consistent brand identity cannot be generated, it must be designed.

Bridging design and code

The handoff between design and engineering has always been a fragile point. Misunderstandings here can multiply downstream.

AI is starting to close this gap. Figma’s Dev Mode MCP Server exposes design tokens to AI agents, ensuring values are carried into production without distortion. Tools like Anima and Locofy.ai convert designs into responsive code.

These tools reduce friction, but they do not replace collaboration. Engineers still need to refine, optimize, and adapt. The value is in starting closer to the truth.

Knowing the models behind the tools

Many of the tools designers rely on are powered by advanced AI models. Understanding these foundations helps us recognize both their strengths and their limits.

GPT-5 represents the newest generation of large multimodal models, capable of handling text, images, and complex reasoning with a level of nuance that makes it especially useful for design assistants, documentation, and creative ideation. Grok-4 from xAI emphasizes speed and integration within fast-moving environments, making it valuable when designers need real-time insights or lightweight experimentation. Claude continues to stand out for long-context comprehension, which is essential when working with large research datasets or extended documentation. Gemini integrates across Google’s ecosystem, offering strong support for collaboration, search, and analysis. Stable Diffusion remains one of the most flexible open-source platforms for generative imagery, widely used in experimentation. Midjourney has become a benchmark for artistic and moodboard-ready visuals, while Runway Gen-4 continues to advance AI for motion and video design, which are increasingly part of modern product experiences.

Designers do not need to master every model in depth. But knowing what powers our tools helps us choose wisely, and ensures that we use them with both confidence and intention.

The human side of AI

The more I use AI, the more I see that it is not about automation. It is about partnership. AI can generate but it cannot care. It can suggest but it cannot empathize.

The most important role of the designer remains unchanged, to bring humanity into products. To ensure that what we create is not only efficient but also inclusive, not only fast but also meaningful.

AI tools are powerful. But their impact depends on how we use them and how we balance them with our own craft.

Reflections

Looking back, I see AI not as a replacement but as a multiplier. It removes friction, expands possibilities, and accelerates progress. But it also asks more of us: more judgment, more clarity, more responsibility.

For product designers the opportunity is clear. AI is a new palette. Each tool offers a different color, a different brush. Our craft is to choose carefully, to paint with intent, and to never forget that the picture we are painting is for people.

That is why I use AI in my work, and why I see it not as a threat but as an invitation, to expand, to focus, and to elevate the practice of design.