Innovation no longer travels in a straight line
For years, the paradigm that structured the relationship between science and industry followed a clear logic: basic research, applied research, development, market. Each stage in its own compartment, each actor in their assigned place. It was a comfortable model, predictable in its timelines and relatively easy to fund and evaluate. It was also, to a large extent, a fiction.
The reality of how impactful innovation is actually produced was never so orderly. Yet for a long time, the system insisted on managing it as though it were.
What has changed in recent years—and what by 2026 is already becoming a structural condition rather than an emerging trend—is that this model has been replaced by an ecosystem logic. Innovation no longer advances sequentially but through networks: universities, companies, startups, public bodies, investors, and end users interact simultaneously, with roles that overlap and continuously feed back into one another. Knowledge does not wait to be published before it can become useful. And in the most transformative projects, the boundary between those who conduct research and those who apply it is deliberately porous.
This is compounded by the mission-oriented agendas reshaping European innovation policy. Horizon Europe does not fund scientific excellence alone: it funds the capacity to solve systemic challenges—decarbonisation, health, food, mobility—in which no single actor can make progress on their own. This redefines not only what is researched, but also how and with whom. A researcher working on a mission-oriented project cannot afford to ignore the ecosystem of which they are part.
The researcher the system needs is not the researcher of the past
This paradigm shift is not neutral for researchers. It requires skills that the traditional academic system did not train—and in many cases did not even value: the ability to translate knowledge into different languages depending on the audience, identify potential applications before they are fully mature, and build relationships of trust with industrial stakeholders without compromising scientific independence.
In practice, the researcher’s new role encompasses several dimensions that are worth distinguishing.
The most obvious dimension is that of the generator of transferable knowledge. Not everything that is researched needs to be transferred, nor does every form of transfer require the same channels. But in projects with a clear impact orientation, a researcher who incorporates from the outset the question of who might use the knowledge—and how—produces qualitatively different results from one who ignores it. This is not a concession to the market: it is a more comprehensive way of framing the problem.
The second dimension is that of the researcher as an ecosystem node. In a networked innovation system, the value of a scientific team lies not only in what it knows, but also in whom it connects and which conversations it takes part in. Researchers who engage in spaces that bring academia and industry together—technical committees, consortia, collaborative projects, industrial PhD programmes—generate returns that extend far beyond the specific project: they build the fabric through which future knowledge will flow.
And there is a third dimension that remains uncomfortable to name in many academic environments, but is becoming increasingly real: the researcher as an agent of institutional change. Scientific evaluation systems are evolving—slowly, but evolving—towards frameworks that recognise impact in broader terms than citation counts. Those who lead this change from within their institutions are not doing so at the expense of scientific quality; they are expanding the definition of what quality means.
What changes when science and innovation cease to be separate worlds
The benefits of this new relationship between researchers and the innovation ecosystem are not limited to companies gaining earlier access to cutting-edge technology, nor to institutions improving their technology transfer metrics. They are also—and above all—benefits for science itself.
Research that engages with real-world problems tends to produce more robust hypotheses, more creative methods, and a greater awareness of its own limitations. Exposure to the constraints of the applied world—the timelines, costs, regulations, and user expectations—does not contaminate basic research; it grounds it. And a researcher who understands the ecosystem in which they operate is better equipped to decide which questions are worth pursuing.
There is also a less visible but equally relevant effect: when researchers actively participate in the innovation process, the social legitimacy of science is strengthened. In a context of growing distrust in institutions and increasing demands for accountability over the use of public R&D resources, the ability to demonstrate that research contributes to solving concrete problems is not merely a matter of communication. It is a condition for the sustainability of the scientific system itself.
Compass’ Conclussion
The new innovation paradigm does not ask researchers to stop doing research. It asks them to stop conducting research as though the rest of the system did not exist.
That is a more profound change than it may seem. It means revisiting incentives, redesigning career paths, and building institutions capable of recognising and rewarding a broader definition of excellence than the one that has dominated for decades.
The good news is that researchers already working within this logic are not heroic exceptions: they are signals of where the system is heading. Knowledge that does not find its place in the world has not finished its work. It has only done half of it.
