The AI Era: When Learning Spaces Must Transform into Workspaces

Artificial intelligence (AI) is transforming nearly every sector, including higher education. If the main challenge for universities was previously knowledge transfer, the issue has now shifted. Knowledge is increasingly easy to obtain through AI, digital platforms, and open learning resources. What is becoming more important is how students can use that knowledge to solve real problems. This change demands that campuses undergo a transformation. Learning spaces can no longer be defined merely as lecture halls where lecturers deliver theory. Students need to experience for themselves how knowledge is applied in professional work, so that the learning process takes place concurrently with the working process. Therefore, project-based learning, studios, simulations, field visits, and the involvement of industry practitioners are increasingly relevant. It is not enough for students to understand concepts; they also need to learn to read technical documents, understand project schedules, recognise risks related to cost, quality, and time, and practise making decisions in situations that closely resemble actual conditions. One approach that is beginning to be implemented is the concept of ‘SKS Ruang Kerja’ (Work Space Credit Hours), which places students in a professional work environment as part of the curriculum. Its essence is not merely an internship, but making the workspace a learning space. The experience of the Landscape Architecture Study Programme at ISTN provides an illustration of this approach. Through the SKS Ruang Kerja programme over two years, students begin entering a professional work environment from the third semester. They learn alongside lecturers, practitioners, and partner companies in activities that are part of the landscape architect profession. Interestingly, students are not placed as administrative staff or general interns. They are introduced directly to the work that constitutes their study programme’s competencies, such as project management, the preparation and interpretation of S-Curves, understanding hardscape technical specifications (RKS), simulating pedestrian bridge projects, and visiting project sites. This material is indeed not easy for early-semester students. However, it is precisely this early introduction to the complexity of the work that helps them understand the professional standards they will face after graduation. Feedback from partner companies indicates that this approach provides benefits. Students who are accustomed to viewing technical documents, understanding project workflows, discussing with consultants, and following the rhythm of professional work tend to adapt more quickly when entering the workforce. Ultimately, the industry needs not only graduates who master theory, but also prospective professionals who can work in teams, understand processes, ask the right questions, and learn from field experience. It is in this context that AI finds its role. AI can help students understand difficult concepts, summarise technical documents, create simulations, compile reports, and act as a learning companion at all times. However, AI cannot replace the experience of facing real projects, interacting with clients, resolving conflicts on the ground, or bearing professional responsibility. That experience must still be obtained through direct practice. A question naturally arises regarding scale. With millions of students in Indonesia, must all of them be placed in companies? The answer is not necessarily. The workspace can be defined more broadly. Companies, laboratories managed to industry standards, teaching factories, research centres, government agencies, startups, and collaborative digital projects with practitioners can all serve as both workspaces and learning spaces. The most important thing is that students perform work relevant to their field of study competencies and receive adequate mentoring. This transformation requires closer partnerships between universities, industry, government, and professional organisations. However, this investment will produce graduates who are better prepared to face the increasingly rapid changes in the world of work. In the AI era, a graduate’s advantage is no longer determined solely by their grade point average or the number of courses taken. What is becoming more decisive is the experience of solving real problems, the ability to use AI responsibly, a project portfolio, and the readiness to contribute from the first day on the job. It is time for campus learning spaces to evolve into educational workspaces, so that higher education produces not only scholars who know many things, but also young professionals who are ready to create.