Interview: Karin Del Rey — on Generative AI, Venture Building, and the Future of Impact Innovation

At INSEAD AI Venture Lab, I spoke with Karin Del Rey, whose insights revealed how Generative AI reshapes venture building

I recently had the pleasure of meeting Karin Del Rey through the INSEAD AI Venture Lab, where she serves as a mentor. Karin brings a wealth of experience as an investor, start-up builder, and sustainability advocate, having held leadership roles at McKinsey, Ula, Big Idea Ventures, and now Katapult Ocean. In our conversation, she shared incredible insights on how Generative AI is reshaping the way founders build companies, particularly in emerging markets, and how it can create opportunities for impact-driven sectors such as ocean innovation and sustainability.

Image: Karin Del Rey, LinkedIn Credits

From your perspective, what excites you most about the potential of Generative AI in venture building?

The ability to build a lean company with minimal capital and a small team. Traditionally, a lot of venture building has relied on needing capital early on to hire a team, pay for engineers, etc. This has placed a lot of pressure on founders to raise money early - fundraising can be a massive distraction and can put the company in a situation where they need to compromise on some of their vision/strategy in order to fit into the VC/ investor mould. Additionally, a company with more employees and structures will find it harder to iterate and test the market vs a small company.

With generative AI, a solo founder could potentially grow their business without needing capital or other staff, allowing the company to iterate and try new ideas whilst staying lean, which I think will be conducive to great businesses being built, as they will be a lot more cost-efficient and able to iterate their ideas until they find product market fit. Thanks to Generative AI, a founder will be able to amplify and accelerate their own skills/abilities, and access those skills they do not have at the moment, from engineering to finance or marketing.

In South East Asia, we are very lucky because many ideas/businesses taking place in China are moving here next! So I am excited to see what comes to our market in the next year, given the speed of change, innovation and iteration that is taking place in China.

How do you see Generative AI transforming early-stage startups, especially in emerging markets?

As per the previous question, the ability to build a business and test new ideas with minimum capital and staff and stay nimble. In the case of emerging markets, this is especially important as there is less access to traditional pools of capital, from VC to government or academia grants. In my experience, founders in these markets are very good at growing businesses with minimum investment, and being scrappy - not needing to find the perfect solution before testing it. They are also less constrained about the level of capital and set-up needed to start something - in developed markets, I see founders claiming they need X millions or they won’t be able to make it work. Whereas in emerging markets, founders know the capital might not be there and already think of how their idea can be tested with a minimum budget, so I believe they will be especially open to the many possibilities that Generative AI can offer. I still have not seen too many examples of this, but I think it will happen soon - especially as Generative AI is able to function in multiple languages beyond the most used ones, and is adapted to local contexts.

Additionally, in emerging markets the access to technology is also not always easy - either there are not that many engineers or the infrastructure is patchy or it’s too expensive. Being able to build and code with Generative AI will be a game-changer. Even if human involvement will be needed, it will allow these companies to reach a level that will allow for market testing.

As both an investor and mentor, what skills do founders need to develop to leverage Generative AI effectively?

I think right now Generative AI has become a buzzword, everyone wants to be part of it, and not many people fully understand it (myself included! I am learning every day). In markets where fundraising has become harder, like Southeast Asia, AI is still attracting investor interest, and founders see it as a way to get funds, but I have seen many examples of business ideas involving AI where AI is actually not needed for the business to function, or the ideas are extremely conceptual and unlikely to work for the time being. Additionally, too much pressure is being put on the Generative AI to change our lives and businesses in a radical way - I am closer to the school of thought where we need to think about the actual improvements and efficiencies technology can bring to our lives, even if it’s not perfect or extremely visionary. I believe boring, functional improvements with a clear price tag (eg cost efficiencies, shortening lead times, etc) are actually very important.

This said, I believe founders should be:

• a) realistic with what Generative AI can actually do, both when developing their business idea and when approaching investors

• b) not need a perfect solution to test their ideas - perfect solutions don’t exist, and good can be good enough to test

• c) seek advice and support from experts - whilst I think innovations like vibe coding can go a long way to build ideas, they can have massive gaps - for now, there is only so far the technology can go.

• d) be very clear of the problem you are trying to solve and the demand there is for it, and how will consumers/ businesses adopt it - there is sometimes the misconception that just because an idea has AI or an exciting technology attached to it, it will work. The truth is that a good technology might not have a good market fit, and the users that you are targeting might not be interested in it or be able to afford using it. Have a clear business model and do your research in terms of who your market is and what their needs are.

What opportunities or risks do you think Generative AI presents to impact-driven sectors, such as ocean innovation and sustainability?

I think some people’s initial reaction is that Generative AI is bad for the environment, and they stay at that- due to the amounts of electricity needed to train the models, water to cool them down, and their subsequent carbon footprint. Whilst this is true, it is only part of the answer. Generative AI is here to stay, we like it or not, so now we need to focus on how to make it more environmentally friendly. There are a lot of renewable energy solutions being developed, many of them in the ocean, including using wave energy, that will both use AI to function and generate cleaner energy for AI to function. This is a great chance to find alternative fuels and ways to generate energy that will be more environmentally friendly

Additionally, a lot of innovative solutions that have a positive impact in our oceans are leveraging Generative AI - from supporting oceanographic research to better understand the ocean and track the impact of climate change and solutions to alleviate it, track the origin of our fish and seafood to ensure it’s sustainable, AI driven logistics to create more efficient routes for ships and better managed ports... the list is endless. There is a lot of potential to leverage AI for good.

Looking ahead, how do you envision the role of human creativity alongside AI in building breakthrough companies?

I see AI as a thought partner and a resource, a way to multiply our reach and potential. It should help us move faster, get even more access to ideas, and allow non-technical people to leverage technology in simpler, cost-efficient ways. It should not do all the work for us, or we risk losing our creative instincts and becoming obsolete. Additionally, we should not stop questioning AI’s responses - they might be wrong or biased, and exercising our critical thinking will remain essential. But it is an enormous opportunity to broaden our horizons on what is possible.

Speaking with Karin left me with a strong sense of optimism. She views Generative AI not as a magic bullet, but as a powerful amplifier of human creativity and resourcefulness, especially for founders in emerging markets, who are accustomed to building with agility and limited resources. Her perspective reminds us that while technology can accelerate innovation, the real breakthroughs will come from founders who remain grounded: those who stay realistic about what AI can and cannot do, focus on solving real problems, and keep human creativity at the heart of their ventures.

Karin’s insights are a timely reminder that the future of venture building will belong to those who balance innovation with impact, vision with pragmatism, and technology with humanity.

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