Why academics make good entrepreneurs, and why sometimes they don’t

When I asked an AI to generate an image of an academic and an entrepreneur, the result was telling.

On the left, a young man in casual denims stands in a bright office in front of a whiteboard and a laptop, arms crossed confidently, exuding youthful energy.

On the right, a silver-haired, bespectacled man in a tweed suit holds open a tome of a book in a dusty old library.

Unsurprisingly, age, race and gender biases are glaring, reflecting common stereotypes (although I was pleased to see academics are no longer seen meticulously pipetting in silence). Also visible are the cultural perceptions: the entrepreneur is fast and messy; the academic is slow and pedantic. Note also: laptop vs book.

As a former cancer researcher, turned funding manager, turned VC, turned CEO of a techbio startup Concr, I can tell from experience that this picture is outdated. We are in the era of deeptech, where the problems we are solving (climate change, cancer, energy) require deep, rigorous science.

Fortunately, academics possess the raw DNA of exceptional entrepreneurs, though there are some habits rewarded in academia and punished in business, which could hold us back.

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1. Critical Thinking, or Asking the right questions: in a world of hype, critical thinking is a USP. Academics are trained not just to seek answers, but to grapple with whether they are asking the right questions. We demand evidence (sometimes to a fault). This allows academic founders to cut through the noise, contextualise risks, and use data to guide product progression. In deeptech, where the stakes are high, this rigour can be your competitive moat
2. Adaptability, or The pivot: in the startup world, ‘pivoting’ is a planned and celebrated occasion. In science, it is foundational. Scientific research is defined by the unknown. You formulate a hypothesis, and often the data proves you wrong. An academic doesn’t quit when the data contradicts them; they listen to it. This serves academic founders to kill features that aren’t working and pivot toward Product-Market Fit faster than founders who are emotionally attached to their original vision
3. Problem Solving, or Managing the chaos: I often liken running a start-up to ‘keeping plates spinning’. This notion is very familiar to a scientist: you are simultaneously managing budgets, supervising students, fixing broken equipment, writing grants, and running experiments. We are trained to troubleshoot constantly. When someone (“accidentally”) leaves the incubator door open and your experiment of three weeks is wasted, you find a workaround. This capacity to manage never-ending fires is the exact training needed for the early days of a startup
4. Presentation, or Storytelling: as scientists, we spend our careers distilling incredibly complex concepts for grant committees, students, peers, and lay audiences. We know how to construct a narrative based on evidence. When an academic founder learns to channel this skill into a pitch deck that translates complex science into a clear value proposition, it is incredibly powerful. Investors trust us because we don’t just sell a dream, we back it up with evidence

However, the academic world also nourished some bad habits which I had to unlearn to keep up with the pace of the entrepreneurial world.

1. The Grant Mindset: in academia, funding is transactional and linear: you tailor your proposal to the grant opportunity that’s available, not necessarily seek funds that will get you the answer. Your primary aim is to publish something within a few years. You expect someone somewhere to absorb the overheads. In a start-up, this mindset is lethal. You are deploying limited capital to find exponential growth. You must think in value-driving milestones and raise the amount you need to actually get there (and contingency). You must be comfortable burning cash to test a hypothesis quickly and build something people will pay to use, rather than hoarding funds to ensure you survive the grant cycle
2. Obsession with Detail: the academic urge is to be comprehensive. We want to understand every mechanism before we proceed. Gather as much supportive information. Obsessing over the details of a feature that the market hasn’t tested is a waste of runway. I had to learn to replace ‘comprehensive’ with ‘sufficient’. You don’t need a perfect product to learn from the market; you need a Minimum Viable Product (MVP)
3. The Lone Wolf-ness: the nature of academic research is such that you are responsible for building out your research. Alone. You are responsible for the concept, development, and execution, exerting tight control over every aspect of the research. We are trained to be hands-on perfectionists. But in a start-up, this can fuel myopia. However few, you must work in an interdependent team and delegate to support each other, especially as you grow. And you cannot lose outward sight of the market and competition. So hire people who are smarter than you in their specific domain, and then trust them to do the work
4. The Ego Trap: finally, and perhaps most importantly, you do not have to be the CEO. In academia, the PI (Principal Investigator) is the head of the lab. Because of this, many scientists assume that if they spin out a company, they must be the Chief Executive. This is an ego trap. ‘Founder’ is a permanent status; ‘CEO’ is a job description. The skills required to discover a drug target are not the same skills required to close a funding round or manage partnerships. Academics make incredible CSOs or CTOs – roles that protect the scientific integrity of the company. Execution-focused and detail-loving individuals often fit well into operational roles. Very early start-ups probably shouldn’t fixate on CXO titles at all and focus on MVP. The smartest academics ask themselves: ‘Do I want to run a business, or do I want to solve this problem?’

So, do academics make good entrepreneurs? For the easy problems, probably not. But we don’t face easy problems. The challenges of the future require founders who understand the fundamental laws of science and can apply their rich skillset to deliver results. Keep the resilience, keep the rigour, but leave the perfectionism in the lab.