Behind the scenes in Data & AI: how interns are building solutions with impact 

One of the main differences with school is how projects are approached. At university, students often work within a fixed structure. Here, projects start from zero. This means making choices, setting priorities, and working closely with mentors and colleagues.

It takes time to find the right approach, but it creates a strong learning experience. Interns also work with technologies and ways of working that are less present in school, such as using different AI models, setting up testing, writing documentation, and deploying solutions in real environments. 

The projects also show that working with AI is not only about what is technically possible, but also about making the right choices.

When sensitive data is involved, for example in healthcare, solutions often need to run locally. This can result in lower performance, but ensures that data remains secure and under control. It reflects the balance between innovation and responsibility.

At the same time, AI already adds value in practical tasks. Especially for repetitive work such as writing tests or documentation, AI can support time-saving efforts and allow more focus on meaningful work and collaboration.

As the interns also highlighted, AI is mainly used to generate structured examples or drafts, which still require human input and supervision. AI does not yet have the full context on its own, so human review remains essential. 

Beyond the projects, the working environment plays an important role. Interns mention that it is easy to ask questions and that colleagues are open and approachable.

There is space to share ideas, receive feedback, and improve along the way. This combination of guidance and autonomy helps interns take ownership and quickly become part of the team. 

These projects show how Data & AI is applied in practice within Solutions, across internal processes, client solutions, and societal use cases.

They also show how young talent can contribute from the start, and how collaboration between interns, mentors, and teams leads to new ideas and continuous improvement.

For colleagues, this means that what is being developed today can become relevant for broader use tomorrow. It creates opportunities to simplify processes, save time, and apply technology in a meaningful way. 

In the coming weeks, the focus will be on further development and testing. The healthcare project in particular, with upcoming tests in a care home, will be an important step in improving the solution based on real user feedback.