Over the course of the project I learned a lot about myself, my role in a team, and how to approach a business proposal. I started with a technical background and little confidence in business, but finished with a better understanding of how technology and strategy connect. During our first brainstorm session, I proposed using AI to help customers design a room through IKEA. The rest of the team quickly built on this idea and together we came up with the concept of allowing people to scan or measure their room, describe what they like through a prompt and let AI design the room for them. The AI would then generate a design using IKEA products and create a shopping list that users could add directly to their shopping cart.
After deciding on the topic of the project, we divided the tasks based on the areas each team member had already researched. Drawing on previous experience with Figma during my bachelor’s degree, I took responsibility for building the prototype, conducting the evaluation, and creating the corresponding PowerPoint slides. I also created an appendix slide containing a video demonstrating the prototype’s interactions. Towards the end of the project, I reviewed the final slide deck with my teammates, checking the details and ensuring that everything in the prototype worked as intended. Our responsibilities remained relatively consistent throughout the project, but we supported each other whenever needed, making the collaboration feel balanced.
The most important thing I learned about myself was that I know more than I think. Initially, I was sceptical about how much I would know about developing a business proposal and how much time I would need to spend in understanding the business side. However, as we explored the assignment and brainstormed ideas, I became more confident in identifying a suitable company and envisioning how we could develop the prototype. My technical background proved valuable, because I had already used Figma before. It was also a practical choice for the team, as it allowed to visualise the concept and demonstrate its functionality without having to develop a fully functioning app or website. Having the necessary experience and a clear idea of how to visualise the concept, motivated me to take the initiative in developing the prototype and conducting the evaluation.
One important decision we made as a team, was to build an additional AI layer on top of the IKEA Kreativ rather than propose an entirely new application. Since IKEA Kreativ already allows customers to visualise furniture in their own spaces, we saw an opportunity to build on this existing service. Users would need to scan or measure their room, describe their preferences through an AI chat, and receive a personalised room design with corresponding IKEA shopping list. We believed this approach would be more feasible for IKEA, because it would build on existing functionality rather than require the company to develop an entirely new platform. This also helped us focus on the additional value that AI could provide by reducing the effort required to make design decisions and helping customers translate their ideas into actual purchases. Through this decision, I learned that a business proposal should not only identify an existing problem but also consider a company’s existing capabilities and propose a realistic way to improve its value proposition.
The most challenging part of the project for me was the evaluation. Building the prototype in Figma was relatively straightforward because I already knew how to use the tool and could visualise the different screens and interactions. However, determining how to evaluate whether our proposed AI feature would actually be useful was much more difficult than expected. I needed to look beyond the prototype’s appearance and functionality and consider whether AI would make designing a room easier, faster, or more satisfying to customers.
Because the prototype was created in Figma, it could demonstrate the intended user journey, but it could not provide a fully functional AI room-design experience. Making it difficult to conduct a realistic comparison between designing a room with and without AI. Although the literature helped us asses the assumptions behind our concept, it also highlighted the limitation in our evaluation. Literature evidence about that personalisation can improve the shopping experience does not necessarily demonstrate that customers would trust AI-generated room designs or purchase the recommended products. I realised that demonstrating how a feature could work is different from proving that it solves a genuine customer problem. This challenge changed my understanding of what it means to validate an AI-based business idea. Initially, I focused on creating a convincing prototype that demonstrated the proposed functionality. But I learned that evidence must support the specific claim being made, rather than simply suggest that AI could improve the customer experience.
Looking back, I would approach the evaluation differentlyby identifying theassumptions that need to be tested before developing the prototype and use them to guide both design and evaluation. For example, I would create a prototype or simulation that allows users to complete the same room-design task with and without AI, comparing task completion time, usefulness of the resulting designs, and customer satisfaction. I would also collect feedback from potential users to understand whether they trust the AI recommendations and would actually purchase the recommended products. This would provide stronger evidence of the feature’s value and help distinguish potential benefits from assumptions that have not yet been validated. Ultimately I learned that a prototype should not only communicate an idea but also enable its underlying assumptions to be tested.
Working with the team taught me that a strong individual contribution is not enough if it does not fit into the overall proposal. Because I was responsible for the prototype, I initially focused on making the user journey clear and demonstrating the functionality. However, the prototype also needed to communicate the same assumptions and value propositions as the business analysis. Reviewing the presentation together helped me recognise that technical work is most valuable when it supports a shared argument rather than functioning as a separate deliverable.
Finally, the project changed how I think about AI and business strategy. Before the project, I tended to focus more on what technology could do than on whether it would create value for a business and its customers. Working on the IKEA concept showed me that introducing AI is not automatically an improvement. The feature must solve a genuine customer problem, fit into the company’s existing services, and provide enough value to justify its implementation and operating costs. Going forward, I would start by identifying the customer problem and desired business outcome, rather than focusing on the technology itself. I would then determine which assumptions need to be validated and design a prototype that allows them to be tested. This project showed me that my technical background is a strength, but that creating a convincing solution also requires commercial reasoning, critical evaluation, and an understanding of customer needs.
