6 Key Lessons From a Year of AI-Powered Workshops

2024 was transformative in how we approach innovation workshops. After running over 10 AI-powered sessions across major enterprises, we discovered that artificial intelligence isn’t just a tool – it’s a catalyst that fundamentally changes how teams innovate. These sessions revealed both the immense potential of AI and the nuances of integrating it effectively into team workflows. Here are the key lessons we learned.

Lesson 1: The Power of Starting From Edit

The most profound insight came from Alex Osterwalder‘s observation: successful teams “use AI to help them start from a place of edit.” Instead of facing a blank canvas, teams work with AI as an intelligent team member that provides a foundation of ideas to build upon.

This shift represents more than a simple productivity boost. It redefines how teams allocate their cognitive resources. Traditionally, brainstorming sessions often began with participants staring at an intimidating blank slate, unsure of where to begin. By leveraging AI to generate initial concepts, teams bypass the paralysis of the blank page. This allows them to focus their cognitive bandwidth on what humans do best: critical thinking, decision-making, and refining ideas into actionable strategies. In essence, AI isn’t replacing human creativity; it’s amplifying it by giving teams a push-start.

Lesson 2: From Visual Aid to Innovation Catalyst

What began as a simple tool for rapid visual development evolved into something far more powerful. Initially, we used our  AI tool, Rapid Visual,  to create customer value scenes and storyboards in minutes rather than weeks. This capability alone was impressive, as it saved significant time and resources. However, it quickly became clear that AI’s potential extended beyond visuals – it could be integrated into the entire business modelling process. Thankfully, Mathias, an AI engineer and the newest addition to our team, was constantly evolving the tools.

For example, AI tools weren’t just generating visuals; they were helping teams map out customer journeys, identify pain points, and propose solutions in real time. This shift allowed teams to iterate faster, exploring more possibilities in less time. In one session, what would traditionally take weeks of meetings and iterations was condensed into a single workshop, with AI acting as both an enabler and a catalyst for deeper insights.

Lesson 3: Tripling the Number of Ideas

One of the most exciting outcomes of AI-powered workshops was the dramatic improvement in ideation. The integration of AI-generated visuals with context-specific trigger questions led to a multiplication of ideas.

While traditional workshops typically generated 8-11 ideas per person, AI-enhanced sessions produced 20-30 ideas per participant. But it wasn’t just about quantity. These ideas were more refined, actionable, and aligned with the business objectives of the teams. AI’s ability to provide diverse perspectives and prompt deeper thinking meant that participants could explore angles they might not have considered otherwise. The result was not only a higher volume of ideas but also a more targeted approach to innovation.

Lesson 4: Addressing the AI Elephant in the Room

One crucial lesson was the importance of addressing AI anxiety upfront. Every successful workshop began by acknowledging two parallel conversations: “what could we do with AI” and “should we use AI.” These discussions often revealed underlying concerns about job security, ethical implications, and the fear of losing human control over creative processes.

By separating these conversations and focusing on exploration rather than ethical debates, we created a safe space where participants felt free to experiment and learn. Once the initial apprehension was addressed, teams were more willing to embrace AI as a partner in the innovation process. This approach not only built trust but also encouraged a mindset of curiosity and openness, which is essential for innovation.

Lesson 5: The Art of Sequential Prompting

Another key insight was the value of sequential prompting. We discovered that the key to effective AI usage isn’t about being a “prompt engineer” – it’s about understanding how to chain AI interactions. Each output becomes an input for the next step, creating a compound effect that improves accuracy and relevance.

For instance, in one workshop, participants began by using AI to generate high-level ideas. These ideas were then refined through a series of iterative prompts, each building on the last. This process freed participants from the pressure of “perfect prompting” and helped them focus on the actual innovation process. The result? Teams could move from initial concept to comprehensive pitch – complete with visual assets, business models, value propositions, and customer insights – in timeframes that would have been impossible before.

Lesson 6: The Balance Between Augmentation and Replacement

More importantly, these workshops underscored the importance of maintaining human agency and creative control. AI wasn’t seen as a replacement for human intelligence but as an enhancer. Teams used AI to expand their capabilities, allowing them to achieve more while remaining firmly in control of the innovation journey.

Expanding What’s Possible

As we look ahead, it’s clear that AI isn’t just changing how we innovate – it’s expanding what’s possible in the innovation process. The key is finding the right balance where AI augments rather than replaces human creativity. This balance allows teams to push boundaries, explore new possibilities, and achieve breakthroughs that would have been unimaginable without AI.

2024 was just the beginning. As AI continues to evolve, so too will our understanding of its role in innovation. The lessons we’ve learned this year provide a strong foundation for the future, reminding us that the true power of AI lies not in its ability to replace human ingenuity but in its capacity to amplify it. We’re really excited to see the evolution of our workshops in 2025.

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