AI Makes Entrepreneurship Easy? Insights from My Capstone Project

By Chomsky (Class of 2025)

If you still think entrepreneurship has nothing to do with your life, I hope you will stay and read this article.

To be honest, I used to think the same way before joining Hitotsubashi University Business School, School of International Corporate Strategy (Hitotsubashi ICS). As a former English language instructor, I was comfortable leading a group of students, designing lessons, and helping people grow through learning. But building a company? That was never part of my plan. Entrepreneurship sounded like something distant — something for founders, investors, engineers, or people who had always dreamed of launching a startup.

However, my experience at Hitotsubashi ICS gradually pushed me into unfamiliar territory. It encouraged me to step outside the identity I was used to and explore a different version of myself. Among many valuable learning experiences, the Entrepreneurship Project in the Capstone course became one of the most memorable. It was not only a project about creating a business idea. It was also a journey of learning how to think, test, decide, and lead when there is no single correct answer.

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 How Does the Entrepreneurship Project Work? 

Unlike a traditional classroom assignment, the Entrepreneurship Project required us to move from business concepts to real entrepreneurial action. We formed a team, identified a real-world problem, developed a business idea, tested our assumptions, refined our value proposition, built a demo, and finally presented our venture to evaluators from real investment and business backgrounds.

What made this project special was that there was no fixed route. Each team had to define its own problem, choose its own direction, and continuously improve the idea through research, interviews, feedback, and discussion. In that sense, the project was not simply about creating a startup proposal. It was about experiencing how entrepreneurs think and act when facing uncertainty.

Professor Thomas Brayman’s support played a huge role in this process. His teaching style was open-minded, encouraging, and practical. Rather than pushing every team into the same framework, he gave us the freedom to explore different possibilities. At the same time, he also challenged us to make our ideas clearer, more realistic, and more convincing. This balance between freedom and guidance was extremely valuable. It allowed us to experiment, but it also prevented us from getting lost in imagination.

Another important feature of this year’s project was the role of AI. AI was not simply a tool for writing or polishing. It became a thinking partner throughout the entrepreneurship process. We used AI to support divergent brainstorming, generate alternative business ideas, compare different positioning options, and structure convergent discussions. It also helped us create early demo concepts and communicate our product vision more clearly.

Through this process, I realized that AI can significantly lower the barrier to starting an entrepreneurial project. It helps teams move faster from vague ideas to concrete prototypes. It can support creativity, execution, and communication. But as I later learned through the project, making something easy to create does not mean making it easy to survive.

 Our Project KURA and How It Was Evaluated 

Our project was called KURA. At the beginning, KURA was designed as a cross-clinic AI diagnosis support tool. The original idea was to reduce doctors’ pain caused by fragmented medical information and help them make better-informed decisions. It was an ambitious starting point, but the project quickly taught us that a good business idea must survive contact with reality.

The first major evaluation came through customer interviews. We interviewed doctors and dentists from clinics in China, Spain, and the Philippines, as well as a cosmetic clinic doctor in Japan. Through these conversations, we discovered that the problem was not only fragmented medical information. A deeper issue was the tension between clinic efficiency and patient engagement. Doctors wanted to explain carefully and build trust with patients, but the pressure of daily clinic workflows often forced them to move quickly.

This insight changed our direction. KURA could not remain only a doctor-side AI diagnosis tool. It needed to become a platform that connected clinics and patients more effectively. We redesigned KURA around patient revisit management, recovery reporting, post-visit communication, easier booking, and digital access to treatment history. For doctors and clinic staff, KURA would reduce repetitive administrative work. For patients, it would make the care journey smoother, more transparent, and more continuous.

The second major evaluation came from regulatory and legal analysis. We realized that if KURA directly intervened in diagnosis, the service would face stricter supervision, longer approval processes, and higher uncertainty. This would make the project harder to launch and less convincing from an investor perspective. Therefore, we repositioned KURA as a workflow-improvement and patient-clinic communication platform rather than a direct AI diagnosis intervention tool.

This shift was not easy, because “AI diagnosis” sounded more dramatic and innovative. But the project forced us to ask a more important question: What can realistically create value in the market? Giving up the more eye-catching version of the idea was not a retreat. It was a strategic decision to make the business more feasible, responsible, and credible.

The project was also evaluated through business logic. We had to think about market size, target customers, ARR assumptions, ideal customer profiles, go-to-market strategy, sandbox testing, pilot projects, and clinic trust-building. This was very different from simply presenting an attractive idea. We needed to explain why the problem mattered, who would pay for the solution, how we could enter the market, and why our team could realistically move the project forward.

The final presentation became the most direct test of our project. The evaluators asked difficult but valuable questions: How could a team without healthcare industry experience persuade investors? How could we attract customers who already use established systems such as Fujitsu? Since many of our interviews were conducted outside Japan, how could we prove that this was also a real issue in the Japanese market?

These questions exposed weaknesses in our implementation plan, but they also helped us understand what it means to evaluate a business seriously. A pitch is not only a performance. It is a stress test of assumptions, evidence, and execution. The final presentation reminded me that entrepreneurship is not about making an idea sound perfect. It is about proving that the idea can stand under pressure.

My Thoughts on Leadership, AI, and Entrepreneurship 

Through the Entrepreneurship Project, I came to understand leadership as ownership.

Before this project, I often associated leadership with standing in front, giving direction, and confidently pushing an idea forward. However, KURA changed my understanding. My main role was pitch storytelling and coordination, but I gradually realized that ownership is not limited to the tasks assigned to me. When a project is uncertain, everyone needs to care about the whole mission.

Sometimes ownership meant coordinating meetings. Sometimes it meant rewriting the pitch story. Sometimes it meant stepping in when another teammate needed support. Sometimes it simply meant noticing that something was unclear and taking responsibility before it became a bigger problem. Through this process, I learned that leadership can be quiet and practical. It is not always about being the loudest person in the room. Sometimes it is about making sure the team keeps moving.

KURA also taught me that leadership does not mean stubbornly defending the original idea. At first, I thought ownership meant protecting our initial concept. But as we went through interviews, regulatory analysis, business modeling, and final evaluation, I realized that true ownership means protecting the purpose of the project, even if the solution has to change. If the original idea does not match customer needs, market conditions, or legal realities, then insisting on it is not leadership. It is attachment.

This realization also shaped my view of AI in entrepreneurship.

AI has great potential in execution and idea divergence. It can help generate many possible directions, compare different business models, create early demo concepts, and make vague ideas more concrete. In the early stage of entrepreneurship, this is extremely powerful. It lowers the barrier to starting a project and allows teams to move from imagination to prototype much faster than before.

However, the project also made me more aware of AI’s limits. AI can help us create ideas, but it cannot decide whether those ideas deserve to survive. It can help us build a demo, but it cannot prove whether customers will trust the product, whether investors will believe the business logic, or whether the market will accept the solution. Those judgments still require human evaluation, field research, ethical thinking, and strategic decision-making.

For me, this was one of the most important realizations from the project. In the AI era, creating something has become easier. But making something survive in the real market is still extremely difficult. A beautiful demo does not automatically become a viable business. A creative idea does not automatically become customer value. A convincing pitch does not automatically remove legal, operational, or market risks.

Entrepreneurship still requires evidence, patience, humility, and the courage to face reality. AI may accelerate the process, but speed alone does not create a sustainable business. The real challenge is not only whether we can build something. The harder question is whether the thing we build solves a real problem, creates real value, and earns real trust.

Looking back, the Entrepreneurship Project helped me see leadership and AI in a more balanced way. Leadership means owning the mission, not just the idea. AI is a powerful partner for thinking and execution, but humans must still evaluate, choose, and take responsibility.

That is why this project was meaningful to me. It was not only about building KURA. It was about learning how to think, decide, and lead when an idea meets the real market. It showed me that entrepreneurship may now be easier to start because of AI, but it is not easier to make real. And perhaps that is exactly why the human side of entrepreneurship matters even more.