As a deep-tech venture capital company focused on shaping the future of health, food, and the environment, we're constantly monitoring global trends that will inform our investment strategy. We’re also frequently asked about our insights on the impact AI is having on acceleration of deep-tech development.

Pacific Channel venture partner Paul Muckleston shares his thinking on the current state of venture capital and the role of AI in deep-tech investments in this video.

The unique nature of deep-tech startups:

Deep-tech startups are at the forefront of technological innovations and advancements, using scientific research and development to solve some of the world’s most complex challenges.

However, unlike software startup’s, early stage deep-tech companies can be pre-revenue for a lot longer which means demonstrating a clear path to profitability is critical. This involves thinking well beyond the technology to be more about the full commercial package that sits around the engineering and scientific innovation – a change which is particularly relevant in sectors like health tech, agritech, and clean energy, where long-term sustainability is crucial.

The changing nature of VC Funding

In recent years, venture capital has experienced a reasonable level of change. Just two years ago, the mantra was "growth at all costs," with VC firms encouraging startups to spend aggressively. However, what we’re now seeing is a swing in the opposite direction with the focus being more on the path to profitability with the right product-market fit, followed by sustained growth. This is particularly evident in the world of Enterprise SaaS startups where funding velocity has declined materially.

But this broad shift in VC funding has implications for startups seeking capital to fuel growth and scale, particularly in the deep-tech space.

Companies now need to demonstrate not only their technological ability but also a clear path to profitability and articulate how they will scale into sustainable businesses. For deep-tech startups, this means developing a robust commercialisation strategy alongside their scientific innovations.

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The AI revolution and it’s implications on deep-tech

Among this changing landscape, one trend stands out above all others: the AI revolution. The excitement surrounding AI, particularly generative AI, has reached what can only be described as ‘fever pitch’. For companies operating in this space, it's almost as if the normal rules of venture capital don't apply. Valuations are soaring, and funding rounds are reaching unprecedented levels.

However, this AI whirlwind has also led to a phenomenon called "AI-washing" which is where companies hastily add an AI component to their existing products or services, hoping to capitalise on the trend.

As VC investors specialising in deep-tech, it’s important that we distinguish between genuine AI innovations and superficial applications.

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Navigating the AI Landscape in Deep-Tech

For deep-tech companies in our focus areas of health, food, and environment, the key to leveraging AI lies in understanding its dual nature

‍Efficiency and Learning:  At a basic level, generative AI can enhance efficiency in various business processes, from copywriting to data analysis and customer service chat bots. It can also serve as a powerful learning tool, allowing teams to quickly grasp new concepts and stay updated in rapidly evolving fields.

Value-Add: The real power of AI in deep-tech lies in its ability to extract insights from unique datasets. Companies that possess proprietary data in areas like (as examples) genetic sequencing, crop yield optimisation, or environmental monitoring have the potential to create truly innovative AI applications that could solve some fairly large global problems.

Our Investment Approach

As a venture capital company, our strategy in this AI-dominated landscape is multifaceted:

1. We encourage our portfolio companies to explore AI applications, but without committing significant capital prematurely.
2. We're particularly interested in companies that have developed deep, unique algorithms or machine learning models in our focus areas.
3. When reviewing and evaluating potential investment opportunities, we conduct thorough due diligence to distinguish between superficial AI applications and genuine innovations.
4. While the AI hype can be characterised as intense,we take a long-term perspective, focusing on how AI can drive sustainable improvements in health, food security, and environmental protection.

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Rounding out our thoughts

There’s no doubt the AI revolution presents both opportunities and challenges for deep-tech and those who invest in the sector.

From our perspective, maintaining a balanced approach – embracing the potential of AI while remaining grounded in the fundamentals of building sustainable, profitable businesses which are built on scientific and engineering based innovations – enables us to successfully navigate this landscape and leverage the benefits while ensuring we're investing in potential solutions that address sigficant global challenges.

Our focus remains on identifying and nurturing companies that use AI not just as a buzzword, but as a powerful tool to drive meaningful advancements in health, food, and environmental technologies.

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