AI-volution:
A Design Thinking Workshop for AI

Many AI projects fail because they focus too much on the technology and not enough on the real problem they’re supposed to solve. Our approach to design thinking and AI flips the usual script—we start by understanding the business and the people behind it. It makes teams ask, “What are we really trying to fix here?” and “Does this AI solution fit into how people actually work?” This helps avoid the common trap of building AI models that don’t deliver value or don’t get used. Plus, it brings technical teams and business stakeholders into the same conversation, helping avoid misalignment and the costly mistakes that come with it. In short, AI and design thinking make sure you’re solving the right problem in the right way, cutting the failure rate that’s been stubbornly stuck around 80% for years. This is a core part of what we cover in our AI workshop, where cross-functional teams learn how to tie real business problems to realistic AI solutions.

When you bring design thinking for AI into your projects, the results go beyond just cool prototypes—they actually make a difference in how your business runs. Take General Electric, for example. They used design thinking and AI to cut equipment downtime by 15%, improve customer satisfaction, and speed up how quickly they bring new ideas to life. Nike shortened their product development from months to weeks while creating products that really connect with their customers. This approach ensures AI solutions aren’t just technically solid but also fit what people need and what the business wants to achieve. In our AI for business workshop, we help you focus on practical results like smoother operations, better workflows, and new ways to bring in revenue by testing AI ideas grounded in real-world problems. We use the same principles in every AI workshop to make sure your team leaves with tangible progress, not just ideas.

Absolutely. The AI strategy workshop is designed to help you clarify where and, most importantly, if AI fits in with your company and which problems it should solve. We guide you through identifying high-impact AI use cases grounded in your unique context, so you don’t waste time nor resources chasing shiny tech that doesn’t move the needle. This structure is what makes the AI for business workshop effective, even for companies that are just starting out with AI.

Integration options are a key part of the AI strategy workshop. We don’t just brainstorm ideas—we map out how AI solutions will fit into your existing tech stack, workflows, and data infrastructure. To make sure the solutions connect smoothly, we review your current systems—including APIs, data formats, authentication methods, and pipeline dependencies—before proposing anything. If your environment uses tools like Kafka, Snowflake, or custom-built middleware, we factor those into the design early. That way, what we build is technically feasible from day one and avoids a common pitfall: AI projects that look good on paper but stall during implementation. We apply the same focus whether it’s an internal innovation sprint or a broader AI workshop setting.

AI projects often get bogged down by conflicting priorities. Our AI and design thinking approach is about using specific design thinking for AI tactics to get business, engineering, product, and customer teams in the same room with a shared goal. We map use cases to business KPIs, define success metrics up front, and document technical and data constraints early. This keeps conversations focused, aligns priorities, and helps teams make faster, better decisions that stick. That consistency is a major reason clients return to our AI workshop format: it makes cross-functional interaction feel structured, not chaotic.