Productive struggle is the crucial sweet spot where learners are challenged enough to develop new thinking but not so overwhelmed that they shut down. The goal is to use AI as a scaffold, not an elevator that skips the learning process.
Think of the AI as a climbing partner. It doesn't pull you up the rock face, but it can hold the rope (provide safety), point out a good handhold you missed (offer a new perspective), or suggest a different route (propose a new framework). You still have to do the climbing.
The challenging part is figuring out where the productive struggle is and when. For example, sometimes brainstorming is where some good work happens, but you could off-load it to AI. Or sometimes summarization helps you to organize your thoughts and that's the work you should be doing. Other times, those activities are small stops to places where you want to wrestle with bigger problems.
How to Use AI to Improve Productive Struggle
1. Lower the "Cost" of Curiosity
The struggle is often stalled by a fear of being wrong. AI experimentation is fast and cheap. Participants can try out five different "wild" ideas in ten minutes, encouraging a playful, curious mindset instead of a fearful, perfectionist one.
2. Provide Scaffolding, Not Answers
A great prompt asks the AI to provide a structure, not a solution. For example, asking the tool to provide the Pixar story spine, a scaffold upon which the team must build their own narrative, focuses the struggle on storytelling rather than on formatting.
3. Offer Just-in-Time Prompts for Reflection
When a team is stuck, instead of asking the AI for the answer, they can ask it to help them reflect. For example: "We're stuck on our solution. Act as a facilitator and ask us three questions that would help us re-evaluate our problem statement from a different angle." This uses the AI to deepen their thinking, not replace it.
How to Model When Not to Use AI
To ensure genuine learning and ownership, the facilitator should explicitly model "AI off-ramps." These are moments where the struggle is too important to outsource to AI.
1. The Initial Empathy Moment
When first reading user personas or listening to an interview, do it without AI. The goal is an unmediated human connection. The struggle to understand another person's perspective is fundamental. Use the AI after this moment to help find patterns, but not during the initial connection.
2. The Final Decision
When it comes time to choose the problem statement or the final concept, close the laptops/turn the screens off. This decision must be owned by the team, based on their debate, values, and intuition. The AI can provide options, but humans must make the judgment call. This struggle builds conviction.
3. The Group Synthesis & "Aha!" Moment
When a group is on the verge of a breakthrough, let them wrestle with it. That moment of collaborative synthesis—where one person's idea builds on another's, and they arrive at a solution together—is the peak of creative confidence. Using an AI here can rob them of that feeling of "WE figured it out."
4. The Personal Reflection
After the pitch, ask the team to reflect on their own: "What were you most proud of? Where did you get stuck and how did you get unstuck?" This metacognitive struggle—understanding how you think and create—is essential for building lasting confidence and avoiding the "I don't know how I did it" trap.