How Knowledge Becomes Impact

Impact is a word I hear every day in conversations about the interface between science, business and society. In academic publishing the impact of research can be measured in a variety of ways - through citations, downloads, media attention, patents, policies and clinical applications. While these indicators matter, they only take us so far. For me, the real impact of research is when knowledge changes how people understand the world, the decisions they make, or what they believe is possible.

That journey is rarely immediate. Some discoveries are recognised quickly but others often sit quietly for years before their importance becomes clear. AlphaFold 2, the AI system that transformed protein structure prediction, which was unveiled in 2021, is one recent example of research already helping scientists advance treatments for heart disease, malaria and many conditions. At the other end of the spectrum, the science that made Magnetic Resonance Imaging (MRI) possible was discovered in 1946 but the first MRI image wasn’t published until 1973. The technology went on to earn its pioneers the 2003 Nobel Prize in Physiology or Medicine. A dataset can be reused in ways its creators never imagined. A method developed in one field can transform another. This is one of the things I find most inspiring about research: its value often grows through the connections made over time, across disciplines, institutions and communities.

Academic publishers play an important role in enabling that impact, by helping research move from individual discovery to shared, trusted knowledge. This is why I believe the systems around research matter so much. Publishing, libraries, universities, funders, technology providers and policymakers all influence whether knowledge remains within a small circle or becomes something that many others can test, challenge, reuse and apply. Impact does not begin only when research is put into practice. It begins much earlier, in the choices we make about how knowledge is created, evaluated, shared and preserved.

Over my career, I have seen technology change those choices profoundly. The move from print to digital was not simply a change in format. It changed the reach, rhythm and ultimately impact of scholarship. Research that once depended on proximity to a particular library could now be discovered across borders and disciplines in seconds. Open access publishing has pushed this further, widening the audience for knowledge beyond those with traditional institutional or subscription access. A teacher, clinician, entrepreneur, policymaker or citizen can now access evidence directly and use it in ways the original authors may never have anticipated.

But access alone is not enough. For knowledge to be impactful it must also be trusted. As the volume of research grows, the ability to assess quality, protect integrity and distinguish reliable evidence from noise becomes more important, not less. Technology can help by supporting editors, reviewers and research integrity specialists, and by identifying issues that may otherwise be difficult to detect at scale. But trust itself cannot be automated. It depends on judgement, transparency and accountability.

That balance is important because research is, at heart, a human enterprise. Technology can reduce friction, reveal patterns, connect literatures and make information easier to navigate. Used well, it can give researchers more time for the work only people can do such as asking original questions, exercising judgement, challenging assumptions and imagining new possibilities.

Artificial intelligence brings this into sharper focus. AI can help researchers scan vast bodies of literature, identify connections, summarise findings and speed up routine tasks. It may open new routes to discovery, as we have already seen in fields where computational tools can model complex biological or physical systems. At the same time, it can raise questions about originality, accountability, bias, transparency and the future diversity of research itself, something we need to closely monitor.

For me, the most important question is not whether AI will increase output. It almost certainly will. The more important question is whether it will help science become more insightful, more collaborative, more useful – and therefore more impactful. If everyone has access to similar tools trained on similar material, will research become broader or more uniform? Will AI help early-career researchers join conversations more easily, or will it reinforce existing inequalities? Will it surface overlooked knowledge, or amplify what is already prominent?

The history of scientific communication shows that technology can expand the impact of research when it is shaped around human goals. Digital platforms, open access, data-sharing practices and AI-enabled tools all have the potential to help knowledge travel further and be used more effectively. But they need to be guided by values: openness, rigour, inclusion, integrity and responsibility.

So I do not think we should treat impact as a destination reached after publication. It is better understood as a condition we create together. It depends on whether research is findable, accessible, understandable, reusable and trusted. It depends on whether different communities can engage with it. And it depends on whether the systems around science encourage curiosity as well as productivity, collaboration as well as competition, and long-term value as well as short-term metrics.

Publishers have a role in that ecosystem, but we are only one part of it. Our responsibility is to help make high-quality research visible, reliable and usable, while continuing to adapt to the changing ways in which knowledge is produced and consumed. That means embracing technology where it strengthens research, being cautious where it introduces new risks, and remaining clear that human expertise is central to trust.

In the end, the impact of research is not simply that it is published, read or cited. It is that it becomes part of our shared capacity to think, decide and act differently. In an age of accelerating technology and growing complexity, that mission feels more important than ever.

Frank Vrancken Peeters is the CEO of Springer Nature and a member of its Management Board. He advocates for greater collaboration across the research community to accelerate open science and has played a leading role in Springer Nature’s transition to open access.