Contact Us
    We are committed to protecting and respecting your privacy. Please review our privacy policy for more information. If you consent to us contacting you for this purpose, please tick above. By clicking Register below, you consent to allow Orion Innovation to store and process the personal information submitted above to provide you the content requested.
  • This field is for validation purposes and should be left unchanged.

Artificial Intelligence is the hot topic in technology, and our work is changing quickly as we incorporate it into our workflow. The potential for AI to support the activities involved in design thinking is huge. While the process of adding AI functionality to software used in design is still somewhat nascent, design thinking is one of the creative disciplines that stands to benefit dramatically as these tools continue to mature. 

Design thinking is a human-centered approach to innovation that uses design techniques to integrate user needs, the possibilities of technology, and business requirements. It is characterized by five phases, which are not necessarily sequential and can be carried out in an iterative fashion. This flexibility inherent in design thinking supports creativity, which is organic and not always linear. 

AI functionality is starting to appear in the creative tools we use for design thinking. For instance, Miro’s AI function Miro Assist and Figma’s FigJam AI are starting to include features that can help support each of these five phases. 


Research and observation to understand user needs. 

  • Because AI excels at summarizing text, tools like Miro Assist can summarize transcripts of user interviews and identify key points, saving a great deal of manual effort by the researcher. 
  • Tools like and Supernormal can attend the interview, create a transcript, and identify action items. This allows researchers to stay focused on the interview, and captures verbatim quotes from the interview which are very useful as evidence of the researcher’s conclusions. 

Information gathered in the Empathize phase is synthesized to articulate the main problems we are seeking to solve. 

  • AI’s core ability to recognize patterns comes into play when analyzing the outcomes of a design thinking workshop. When participants have brainstormed ideas for product features, for instance, Miro Assist can analyze a large group of stickies on a digital whiteboard and cluster them into groups by themes or topics – and it defines these themes/topics from the content on the stickies. This is a huge time saver, jumpstarting the process of analyzing large unstructured sets of ideas. When given information like demographics, user goals, and blockers, Miro Assist can draft user personas ready for editing. This gives the researcher a head start in representing user patterns that form the basis of a persona. 
  • Miro Assist can create entire presentations that summarize artifacts on a Miro board. This can save a lot of time during the initial stages of creating presentations. 
  • FigJam AI can convert text inputs into visual representations like diagrams, flowcharts, or mind maps, allowing quick visualization of concepts. This can be very useful when trying to visualize the core concepts from an unstructured set of ideas on a digital whiteboard. 
  • Sometimes in design thinking workshops, we review or generate images rather than just text; Miro Assist can identify themes across a group of images along with any textual content in the images. 

Assumptions are challenged and ideas are generated to solve the problems we identified during the Define phase. 

  • FIgJam AI can facilitate generating ideas in a design thinking workshop by creating slides on a digital whiteboard to support the workshop exercises the researcher defines in text prompts. This can be a huge timesaver. 
  • When ideating during any design thinking process, we frequently have a starting point but need to expand our thinking with more topics. Miro Assist can start from a single idea and generate additional related topics in a mind map. Similarly, FigJam AI can generate additional ideas from stickies or other design thinking artifacts. This can save time by generating more ideas more quickly. 

Designers create design concepts, wireframes, and prototypes, transforming the ideas into tangible artifacts for testing. 

  • Miro Assist and Figma can monitor a user’s workflow and provide AI-powered recommendations for new design objects which are in line with the user’s workflow up to that point. This speeds up the process of creating diagrams to support design thinking. 
  • When design thinking yields hand-drawn screens, the AI-driven design tool Uizard can convert these drawings into actual screen designs. This facilitates follow-on design work based on design thinking processes. 
  • Smart Layouts and Auto-Suggestions: By analyzing design elements and user preferences, Figma AI can propose optimized layouts and consistent spacing, alignment, and proportions across various screens and components. By reducing tedious adjustments to a design, this functionality has the potential to save the designer a great deal of time. 
  • Contextual Design Recommendations: Figma AI can analyze existing design patterns and user behavior to propose relevant design elements, color schemes, and typography choices that align with the project’s objectives. 

Solutions are tested with real users, and their feedback is then used to refine the ideas. 

  • When testing prototypes or software with actual users, we collect data such as success/failure in completing tasks, ease of understanding the UI, usability of the design, and sometimes mouse tracking to gauge ease of interaction. The ability of AI to summarize data and identify patterns has the potential to make it a powerful research partner, identifying patterns and summarizing results of user tests. 
  • AI has the technical ability to simulate user interactions with a prototype to test its functionality, usability, and performance. This is notable because AI is generating the equivalent interactions of a human interacting with the UI, without the need for the time and manual tasks involved in manually conducting a user test. 

As we’ve seen, AI has the potential to significantly enhance design thinking activities by discerning valuable insights into user behavior, generating new ideas, and facilitating rapid prototyping and testing. However, it is essential to remember that AI is a tool to support human creativity and decision making, not replace it. Using AI in design is sometimes referred to as having a virtual “design partner”. Designers bring unique skills and perspectives to the design thinking process, such as judgment, empathy, intuition, and creativity, that AI cannot replicate. By leveraging AI technologies, the design thinking framework can lead to more user-centric and innovative product development, ultimately reinforcing the central role of design thinking in the future of design and innovation. 

XD Strategist  Dennis Crumbine has over 25 years of leadership and design experience spanning companies including Wayfair, The Nielsen Company, JetBlue, and Microsoft. He has a B.A. in Music & Literature from the Gallatin School at New York University and is also a musician, dog lover, and a very proud father. 

Keep Connected