Real Ways AI Can Support Your Design Workflow

Vicky, Product Designer at Sprint

May 8, 2025
3 min read
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AI is a powerful tool that can enhance your design process. It won’t design your product for you or solve user problems instantly. That said, when used correctly, it can help you progress faster and identify issues sooner. It may also surprise you with new ideas. Here’s a look at practical ways AI can support various aspects of design work, that we've been using at Sprint Innovations

Using AI as a Research Assistant

AI is especially useful for spotting trends and patterns in large datasets. Such as survey responses, user feedback, or customer support tickets. It can help to group information into common themes. This makes it easier to extract useful insights from large amounts of data.

Example tools: ChatGPT, Gemini, or DeepSeek

Method: Begin with a spreadsheet where each row represents a single data point. This could be a user comment, survey response, or support ticket. Using your chosen LLM, you can prompt it to:

  • Identify recurring themes across the entries.
  • Categorise feedback into relevant groups (e.g. usability, features, bugs).
  • Highlight common issues, concerns, or positive points.

Limitations: AI can mislabel data. You’ll need to check its output and refine prompts as needed. While the AI can speed up analysis, it doesn’t remove the need for human judgment.

User Interview Practice

An underrated use of Large Language Models or LLMs is to simulate customer interviews. They can help you ask better questions and get up to speed on industry-specific knowledge.

Example tools: ChatGPT, Gemini, or DeepSeek

How it works:

  • Set the context: Give AI a persona (e.g. "You are a 32-year-old tech-savvy project manager who uses productivity apps daily".) and product background.
  • Run a mock interview: Ask open-ended questions as if you were interviewing a real user. The AI will answer in character.
  • Analyse the conversation: Check if your questions are strong enough. Do they reveal blind spots, or surface needs and objections you hadn’t thought of?

Limitations: AI is not a replacement for real customer research. Real customers will surprise you in ways AI can’t fully simulate. It can, however, help you arrive prepared and empowered so you get the most out of (often time-constrained) customer interviews.

Refining Designs with Predictive Heat Maps

Heat maps are visual representations of user attention, showing where people are most likely to focus on a page. In traditional usability testing, they are generated by tracking real users’ eye movements. Predictive heat maps use AI to show where users focus based on design patterns. This helps you assess your layout before testing it with real users.

There are various tools available to analyse landing or marketing pages before spending on user testing. Many of them report over 90% accuracy compared to real (non predictive) heat maps.

Example Tools:

  • Attention Insight: Predicts user attention based on design structure. Offering clarity scores and benchmark comparisons.
  • Heatmap.com: Simple predictive heat maps—great for quick checks.
  • VisualEyes: Combines heat map prediction with emotional scoring (e.g., clarity, attention, engagement).

Best for:

  • Ensuring the visual hierarchy supports your page’s primary goal.
  • Stress-testing landing pages. In scenarios where small tweaks can really impact conversions.

Not good for:

  • Data-heavy applications or complex UIs highly dependent on user context.
  • Replacing usability testing. It’s better viewed as a high-level QA tool rather than a user validation method.

Limitations: These tools use visual pattern recognition to predict where users are likely to focus. They don’t account for authentic user intent or content clarity. Think of them as a “visual hygiene” check—ideal for catching flaws before moving to real testing.

Illustration of heat maps on a website page

Image Generation: An Alternative to Stock

Finding the right stock photo can take longer than expected. They can also be pricey, generic, or not quite fit your brand. AI-generated imagery gives you options. There are many AI image generation tools available, two of which have made it into my workflow.

  • Midjourney
    • Best for stylised, artistic imagery. Can be used on mood boards, concept exploration, and general visuals.
  • Adobe Firefly
    • Trained on Adobe Stock so the output can be used for commercial use. (This is often overlooked, but not all AI-generated images can be used commercially without copyright risks.)
    • Offers powerful editing features within Photoshop. These include, Generative Fill, Distraction Removal, and Generative Expand.
    • Firefly includes lots of helpful inputs to allow you to create solid prompts. Even with limited prompt writing experience.
  • Google Imagen
    • Unlike the others mentioned Google Imagen is free to use. It offers many of the same features as other tools but with really easy to use UX.

Limitations: AI-generated photographs don’t always look right. Hands and faces often look strange, and you can't reliably recreate the same person. In high stake marketing campaigns or UX, AI photos can feel “off.” Real photos or edited stock images are often better for creating trust and relatability.

Chrome custom letter effect generated with Illustrator & Firefly

AI Wireframing and Prototyping tools

There are too many new AI wireframing and prototyping tools to list them all. The practical impact (so far) is extremely mixed. The tools worth noting, integrate with Figma or are inbuilt and can provide responsive design ideas.

Magic Patterns (Application and Chrome extension)

  • Can directly export components with a Figma plugin
  • Can produce react code
  • Capable of responsive mockups

Figma AI Beta

  • Accelerated Design with AI Prompts: Figma can now generate UI designs, text content, and even images from simple prompts — ideal for fast prototyping and ideation.
  • Smarter Workflows: Features like one-click prototyping, asset search via image input, and auto-renaming layers streamline collaboration and reduce manual effort.

Image of Figma Beta AI, launched April 2025 to all paid plans

Final Thoughts

If used with intention, purpose and sufficient preparation AI tools can help you in a number of ways. They can help you to prepare for interviews. Test designs early, find patterns in feedback, and create cool visuals. Ultimately, having this help at hand can speed up your creative process.

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Vicky Billett
Hi, I'm Vicky, a Product Designer at Sprint Innovations. I'm passionate about visual storytelling and crafting awesome experiences and interfaces.
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