Empathy, Play and AI: How Democratized Design Moves Business Forward
When I first starting leading design thinking workshops over a decade ago, I learned a lot about how to bring groups together to co-create.
Some excellent mentors over the years taught me that it’s more than just a process—it’s a mindset. It's about finding ways to activate the group’s collective intelligence, avoid pitfalls, and explore as far as the imagination can carry us.
Traditional design thinking is a powerful framework, yet it’s fair to say it demands significant training and skill. I absolutely appreciate the types of game-changing insights that the trained innovators bring. But I also believe in the idea of democratizing the approach. After all, design thinking is a human-centered approach to problem-solving that emphasizes empathy. How do we uncover that empathy? By including more people in the process.
Should it Always Start at the Beginning?
Design thinking uses the classic Double Diamond framework.
The first diamond is focused on Discovering and Defining (exploring and establishing the problem space), and the second diamond is focused on Developing and Delivering (imagining and refining the solution space).
Across the two diamonds, the steps in the process follow a traditional flow:
Empathize: Understanding the user’s needs through observation and engagement.
Define: Clearly articulating the problem based on insights from the empathy phase.
Ideate: Generating a wide range of ideas and solutions.
Prototype: Building low-fidelity experimental models of the proposed solutions.
Test: Evaluating the prototypes with users and refining them based on feedback.
Yet in today’s fast-moving market, sometimes the traditional process isn’t always practical. Particularly when there are time and resource constraints. A few years ago during a UX course, I was introduced to a great book called Just Enough Research, by Erika Hall. The author argues that there’s a point where “first-diamond” endeavors (particularly empathize) can have diminishing returns. She suggests that a broader group of team members could potentially be trained to ask better questions in research process, enabling the organization to get more diverse input faster, more quickly moving into ideation and iteration.
This is actually a great place for AI to come in. It can take quite a bit of time to gather and interpret insights within that first diamond. But AI can help plus-up primary research with secondary and broader culture-commentary. It can also quickly summarize just the right information, so non-specialists can more quickly put the data to work. This is particularly helpful for agile projects where rapid test-and-learn and speed-to-market are essential.
Giving different project stages to different teams can also help create efficiencies. Specialists/researchers are needed at the moment where an “empathize” activity is designed. But a broader pool of generalists may be able to join the execution of that “empathize” plan. Those same generalists may also be able to help define the insight, and undertake the ideation. AI can be the co-pilot throughout, helping ensure no data point goes un-analyzed.
AI Agents Offer a Unique Approach
I founded The Navigator Collective earlier this year, and we’ve already evolved our approach to now bring trained AI agents into the design thinking process. AI agents act as skilled mentors, guiding those generalists with real-time feedback and support. We train each agent with at least 40,000-50,000 words of theory, case studies and thought leadership. Much of this content is more recent than ChatGPT's general updates. The agentic approach offers some unique benefits:
Scalability: AI agents can mentor an endless number of ideators, which would be unsustainable with human mentors alone. They can give expert, real-time guidance to all participants in a workshop simultaneously, without overwhelming the resources of the organization.
Conversational Engagement: Unlike typical ChatGPT interactions, agents are scripted to ideate and train users in a format that feels like natural conversation. The agents actually prompt the user, rather than the other way around. This eases the learning curve and makes the process more engaging and intuitive.
Accessibility: Agents trained on design thinking and also social psychology, inclusivity and cognitive behavior therapy, can help make both AI and design thinking processes accessible to many more people, regardless of their prior experience or training. This can open a design team up to a much more diverse array of ideas. Not to mention helping generate a massive amount of raw ideas, any of which could become the next big thing.
Play is Serious Business
Many years ago, I attended a keynote from former Nike Play Innovation guru, Kevin Carroll. He spoke about some of the key takeaways in his book, The Rules of the Red Rubber Ball. His talk sold me on play as a stress reducer, collaboration-builder, fulfillment-bringer, and innovation accelerator. In other words, play stimulates creativity and encourages risk-taking, breaking down psychological barriers, forming stronger bonds among teammates, and making the process more engaging.
The last few years, I’ve interpreted Kevin’s guidance as giving people “permission to be silly” in workshops. To that end, we put a lot of silly props on the table to give people kinesthetic things to fidget with while they think. We do silly stand-up/sit-down exercises that get the blood flowing. We give people giant foam hands to raise when they have question. We play games like Affirmation Bingo. It’s all an attempt to break the ice, improve group dynamics, and take the pressure out of the ideation process.
AI-powered Design is on the Rise
I’ve seen some incredible use cases where companies like Nike are using AI to push their own boundaries on design. One member of The Navigator Collective sent me a piece from Nike’s design blog, highlighting how the company is revolutionizing its internal design processes using AI to analyze vast amounts of data from athletes to identify performance patterns and insights. Using AI this way enhances empathy and speeds up prototyping, allowing for more personalized and effective product designs. IDEO U has also been promoting their own AI-powered design thinking workshops of late.
In my view, democratizing the design thinking process with AI isn’t just an abstract goal to work on; it feels like a necessity in our insanely fast market. When we open the doors to more people, we get more perspectives faster, break down hierarchies and foster creativity. Getting ideas from everywhere makes solutions more reflective of the diverse world we live in.
We’re at a truly fascinating moment in culture, where AI is suddenly changing everything. Yet I’m a firm believer that only humans can meaningfully create the new. I think innovators can benefit from AI as a specialized tool to bring more humans into the process. AI can help give a much broader range of people the ability and desire to challenge the status quo, take risks, and push the boundaries of what’s possible.
