Overall, I found Information Strategy an interesting course, mainly because the theory was continuously linked to current companies, technologies and situations that we already knew. This made it easier to understand why we were learning certain concepts and how they could be applied in practice. Instead of learning theory without really knowing where it would be useful, the examples during the lectures gave me a clear picture of what the theory meant in a real business context. I also liked the structure of the AI Strategy Lab. It was obvious from the start what we needed to do, even though I wasn’t quite sure how thoroughly we were supposed to consider every aspect of the concept. As the project developed, this became more evident. Because we could use more of the material we learned each week, I really enjoyed working on the same topic throughout the semester. Instead of finishing individual assignments based on just a portion of the course, we could eventually combine everything into a single final project.
The initial idea for ReUnite came from me. Shortly before the project, there had been a story circulating in Amsterdam about a woman who had left a very exclusive bag in a hotel. The hotel could not find it, which resulted in online discussions about what had happened to it. Although this was not exactly the problem ReUnite eventually focused on, it made me think about how often belongings are lost in hotels and how the process of finding and returning them could be improved. From there, we thought about combining AI matching with hotel information through PMS integration. The rest of the group was enthusiastic about the idea, so we decided to develop it further. My main responsibilities within the project were the competitive and ecosystem analysis, the governance and failure analysis, and the final recommendation. I also spent time making sure the final slide deck looked consistent, as this is something I enjoy doing. Because we divided the written sections between the three of us, I thought it was important that the result did not look like separate pieces put together.
Of my own sections, I enjoyed the competitive analysis the most. Researching competitors gave me a much better understanding of the market and how other companies had designed similar products. It provided inspiration but also forced us to question how new our own idea was. The failure analysis was more difficult for me because we had to define specific criteria for when our solution would or would not be successful. The competitive research also resulted in the biggest surprise of the project. We already knew that companies were operating in the lost-and-found market, which we did not see as a major problem. However, we were surprised by how closely some existing solutions, particularly Loggit, already resembled our idea. We had assumed that AI matching was more distinctive than it was. We still believed ReUnite had potential, but we had to think more carefully about differentiation. One result was our Basic and Premium offering, where Premium combined AI matching with additional features such as PMS integration and analytics. We also became more realistic about the fact that AI matching by itself was not a sustainable competitive advantage.
This experience changed how I think about AI in a business context. Before the project, I mainly thought about AI as a technology that could make processes faster or enable new solutions. I now understand more clearly that adding AI to a product does not automatically create a strong business strategy. The important question is whether AI creates enough additional value compared with existing alternatives and whether that advantage can be maintained when competitors have access to similar technology. The concept of defensibility therefore became particularly relevant to me. I was already familiar with competitive advantage, but this project made it more concrete. A useful AI feature can still be relatively easy for competitors to copy. Being early can help a company establish a position and start building experience and data, but being first is not enough on its own. This is something I would now consider much earlier when evaluating an AI-based business idea.
The collaboration within our group went well overall. One difficulty was that all three of us had different daily schedules, which sometimes made it difficult to find moments when everyone was available. Once we found a time, however, our meetings were clear and structured. Everyone took responsibility for their own sections and was willing to help each other. We first wrote our individual sections in one Word document and later turned this into the final slide deck. We also reviewed each other’s work and gave feedback. I learned from this that it is important to set clear deadlines and immediately agree on the next meeting, so everyone has a clear point to work towards. If I could change something about the process, I would arrange at least one meeting in person at the beginning. I think this would have made it easier to understand how everyone prefers to work and to divide the tasks. I would also do more extensive competitor and market research before fully committing to an idea. Finding out later that existing solutions were more similar to ReUnite than expected was useful, but doing this research earlier would have given us a clearer picture from the start.
Looking back on the assignment, I am satisfied with ReUnite and the result. If we had had more time, I would have liked to develop the prototype further and test it with real cases. I would have found it interesting to see how well the matching worked in practice, although I do not think this was necessarily missing from the assignment. The main thing I take away from the project is that a good AI business idea requires more than finding an interesting use for AI. I would now look much earlier at the market, competitors, alternatives and whether an advantage can be defended. At the same time, I learned how important it is for a group to stay aligned in terms of deadlines, working methods and the final story. This project showed me how many different aspects must come together to turn an initial idea into a convincing business concept, from developing the strategy and questioning your choices to making sure everything eventually forms one coherent story.
