We present a method for rapidly developing and validating data-driven hypotheses by connecting AI to all stages of empathy, problem definition, ideation, prototyping, and testing.
We combine core tools such as Empathy Maps, Personas, Service Blueprints, Kano Models, and Ambidextrous Organizational Design with AI to make them immediately applicable in practice.
This book provides a detailed blueprint for innovation workshops for practitioners and leaders seeking to leverage AI, focusing on people rather than technology. The AI ​​Encyclopedia
You can find the artificial intelligence knowledge you need at aiseries.oopy.io.

Design thinking is an innovation methodology systematized as a business approach by Tim Brown of IDEO and developed into an educational program by the Stanford d.school.
This methodology is based on a human-centered design philosophy that directly observes and understands what users want from life.
By examining user preferences and inconveniences throughout the entire process, from product development to sales and support, we can find opportunities for innovation.
It also connects user needs, technical feasibility, and actionable business strategies to create customer value and market opportunities.
--- From “01_“New Map of Thought””

When creating POV sentences, leveraging AI can help clarify the problem definition process.
Simply input your user research results and ask them to “write a problem statement that includes your users, needs, and insights.”
If you add, "Please give me three different perspectives," you can get multiple forms of problem definitions based on the same data.
This process allows us to derive a balanced perspective that considers various situations without being biased towards one perspective. Leveraging AI tools goes beyond simply accelerating analysis.
It helps broaden the scope of problem definition by reclassifying and interpreting customer feedback from various perspectives.
--- From “03_“A Lens to View Problems””

For user testing to be effective, it must be observation-centric.
When developers directly observe users' actual reactions, they can concretely identify the product's problems and potential.
Information that cannot be obtained through questions and answers alone emerges from actions, and within these, clues for improvement can be found.
Developers can interpret these behaviors within context and repetitive patterns, and refine their products based on the results.
Testing goes beyond simple verification and becomes an opportunity for learning, and as learning accumulates, the product evolves.
--- From “06_“Deep Dialogue with Users””

Organizations believe that "adopting better technology will solve problems," but they face a paradox: the more they invest in technology, the wider the gap between expectations and reality.
This gap stems from a perspective that approaches technology adoption and organizational change separately.
Organizations can transform with technology adoption only when collaboration methods, decision-making authority, and information flows are redesigned.
Leaders must focus on creating an environment where the organization can learn and change through communication, collaboration, and execution.
Only when strategic thinking, human-centered values, and execution are integrated can real change be achieved.

--- From “09_“Architect of Innovation””