AI is now at the center of how we talk about teaching, learning, and employability, at KTH in general, and very concretely at a school level within SCI. The question isn’t whether generative AI will be used; it already is. The real question is how we integrate it so it becomes a resource rather than a shortcut that quietly erodes learning.

Our SCI faculty breakfast on AI in education highlighted both strong engagement and a clear need. Faculty explicitly asked the school to facilitate structured sharing of experiences, teaching materials, and course experiments so we can learn faster together. That kind of open exchange is a powerful tool, one we are in the process of building. It also reinforces something I feel strongly about: we will not navigate this transformation by writing policies and documents alone. Policies can set boundaries and provide a shared vocabulary, but practice is built in the everyday, in assignments, seminars, feedback, and assessment design.

A term that is often used is “AI readiness.” But AI readiness is not about becoming a prompt expert; it is about judgment, i.e. the ability to evaluate outputs, verify claims, recognize uncertainty, and decide when AI supports learning and when it replaces it. That kind of judgment rests on deep disciplinary knowledge and critical thinking, and it’s part of a university’s responsibility to teach it explicitly. Research comparing ChatGPT with human tutors points in this direction: AI can be helpful as a structured dialogue partner, but human guidance remains essential for nuance and tailored feedback (Frontiers | Socratic wisdom in the age of AI: a comparative study of ChatGPT and human tutors in enhancing critical thinking skills).

At the same time, we should be honest about risks. If AI becomes an “answer engine,” students may produce polished outputs while thinking less, a concern raised clearly in STEM education discussions about (Gen)AI and learning design.  And this is also an equity issue: students differ in access, confidence, and literacy, and a “GenAI divide” can widen if universities don’t provide structured support and shared expectations (The GenAI divide among university students: A call for action – ScienceDirect). KTH’s decision to provide Copilot access to all students and staff is an important step. The next question is how we align tool choices, whether Copilot or other platforms (free or paid) with our learning goals and with students’ development of judgement.

This is why, at KTH (SCI), as at many other universities, we are treating AI integration as ongoing academic development, not a one-off compliance exercise: raising a shared baseline of AI competence among teachers and building on-site platforms, workshops and recurring arenas, where we can share materials, compare course designs, and learn from each other as practice evolves.  If we keep the focus there, on judgement, critical learning, and collegial exchange, I genuinely believe we can navigate this transformation, and do it in a way that serves our students best.

At the risk of repeating myself (I wrote a similar blog just a few months ago), I felt it was important to return to this issue in light of the latest VR grant outcomes. The trends continue, and they demand our attention.

Here is the VR project grant data for Natural and Engineering Sciences (NT), 2021–2025:

The total funding has remained relatively stable. What’s changed is the number of applicants, up by nearly 200 in five years, and the resulting success rate, which has dropped steadily. This isn’t a case of declining quality, but of a system stretched too thin.

Rather than restating why fundamental, curiosity-driven research is important, a point that is, by now, broadly understood, I want to raise a different question: Are we simply too many researchers competing for the same pot of money?

My answer is no. The system doesn’t suffer from an excess of researchers, it suffers from structural misalignment. We are, rightly, growing our research capacity in strategic areas like AI, quantum technology, and nuclear energy, where special initiatives and targeted investments exist. But these researchers may also apply for general project grants, which means the competition in that shared pool intensifies, while the size of the pool remains largely unchanged.

This imbalance creates pressure not because the science is weaker or less relevant, but because the system hasn’t adapted to its own strategic expansions.

If we continue expanding our research ambitions without recalibrating the funding architecture, we risk cultivating frustration instead of innovation. Excellence is no longer enough, luck and timing increasingly decide who gets to move forward. This is a dangerous signal to send to our most ambitious minds, especially early-career researchers.

In recent years, Sweden has made some of its most ambitious and forward-looking research investments to date. The Wallenberg Foundations have committed more than SEK 5 billion to long-term programmes in artificial intelligence, quantum technology, life sciences, and renewable materials.

At the same time, the Swedish government’s Budget Proposition for 2026 and the forthcoming Research and Innovation Bill (2025–2030) continue to prioritise research that drives the green transition, AI, quantum technologies, life sciences, and more. Across Europe, the Horizon Europe missions channel major funding toward similar grand challenges (AI, health, energy, and sustainability).

These investments matter. They enable groundbreaking research, attract international talent, and connect academia more closely with society’s needs. They also show confidence in science’s power to address global challenges, a confidence that is essential and worth celebrating.

Yet amid this momentum, I find myself returning to a question that may not fit neatly into policy frameworks but deserves to be asked:

Are we focusing too much on the visible outcomes — and too little on the invisible foundations?

And are we overlooking other parts of STEM that, while less directly tied to current strategic themes, remain essential to the long-term strength of science and engineering?

Behind every major technological advance lies decades of foundational work in mathematics, physics, and other basic sciences that form the conceptual and methodological infrastructure of innovation. At the same time, the broader landscape of STEM fields provides the continuity, diversity, and resilience that sustain our research ecosystem. If we concentrate too narrowly on a limited set of highly visible priorities, we risk reducing the breadth of scientific inquiry that enables unforeseen breakthroughs in the future.

Mission-oriented programmes and strategic initiatives are crucial, and they have changed Swedish research for the better. But as the focus on short-term relevance and measurable outcomes grows, there is a need to ensure that less visible areas of STEM, those not directly aligned with today’s dominant agendas, continue to receive attention and renewal. Sustainable innovation depends not only on its peaks of excellence but also on the quiet continuity of the disciplines that connect and underpin them.

At KTH, and across Sweden’s technical universities, we see how interdependent these layers of science truly are. Our leadership in applied and emerging fields depends on maintaining depth and vitality across the full STEM spectrum.

To innovate responsibly, we must nurture both the vision to apply and the patience to understand. As Sweden prepares its next Research and Innovation Bill, this balance deserves renewed reflection!

Last week, I took part in the WASP panel webinar on Diversity and Inclusion in Academia, where we discussed how global mobility shapes the competitiveness of Swedish research and innovation. Only days later, the U.S. announced new restrictions on its H-1B visa program: a $100,000 fee for all new petitions. For early-career researchers, that barrier is not small.

This matters for Sweden. For years, the U.S. has been the primary magnet for ambitious young scientists and engineers. If that door narrows, a major opportunity opens if we act strategically.

The good news is that we are not starting from zero. The Wallenberg Foundations have already launched some of the largest private research investments in Swedish history, from WASP (AI and autonomous systems) to WISE (materials science), programs explicitly designed to attract and nurture top international talent. The Swedish Research Council (VR) is also running schemes to bring outstanding researchers to Swedish universities.

At KTH, we see the value of international talent every day. We host international PhD candidates, postdocs, and faculty whose expertise is vital to Sweden’s research and innovation ecosystem.

But here is the real challenge: attraction is not the same as retention. Funding packages and recruitment programs bring people in, yet what keeps them here is a different story:

• Predictable career paths and long-term contracts
• Immigration and residence rules that support families and stability
• Strong industry links and opportunities for collaboration
• A sense of belonging and inclusion in our research culture

So the questions we face are:

• How can Sweden convert this moment of opportunity into a lasting advantage?
• What barriers still make us lose talent after a PhD or postdoc?
• How do we ensure that the talent arriving through Wallenberg, VR, Vinnova, and other programs — and joining us at KTH and other Swedish universities — builds roots here rather than treating Sweden as a stepping stone?

The global competition for talent is intensifying. China, in particular, is stepping up its recruitment efforts through major funding and talent return programs. Other non-European countries are also scaling up their strategies. The U.S. decision may have made international talent more accessible for us, but accessibility is not the same as success. That will depend on how well we align national policy, university structures, and industry partnerships to turn attraction into retention. Beyond research investments, Sweden’s social system itself is a major advantage. Universal healthcare, affordable childcare, generous parental leave, and a strong emphasis on work–life balance offer international researchers a kind of stability that is rare in many competing countries. This is not just a social benefit; it is a competitive strength. We should be better at highlighting and advertising these qualities when attracting global talent.

Because in the end, talent is not just a resource to be imported. It is the foundation of our ability to innovate, grow, and respond to society’s biggest challenges.