Four Deep Tech Investors Just Revealed Where the Real Money Is Going

At the Private Capital Forum in Riyadh – hosted by SVCI hosted a panel with four investors with deep roots in science, technology, and finance to answer the big questions:

• Where will AI make the biggest impact?
• Where is the smart money looking for value?
• Where are the hottest laboratories for innovation?

When AI becomes the scientist

Nessan Bermingham of Khosla Venturessees the greatest leap ahead in personalized healthcare.

“When we think about deep tech and the impact that will have both from sequencing your genome, understanding from a cellular standpoint what’s actually going on…we can step in and do personalized medicine for you. That’s where the tech is going to guide us, and [will have] the biggest impact on all of our lives.”

His vision: take a tumor sample, analyze its proteins, develop a custom cancer vaccine for that individual patient, and deliver treatment in real time at a fraction of today’s cost.

Andrew Williamson of Cambridge Innovation Capital, also approaching as a scientist-investor, flagged this:

“What’s really exciting me…is the potential for AI to completely disrupt the scientific method and actually start conceiving of experiments, conducting experiments, analyzing the results, and closing the loop. We could see this massive acceleration of AI enabled or AI driven science, and then the rate of discovery rises exponentially.”

The near future: closed-loop labs where algorithms design, run, and analyze experiments with minimal human input – discovering new molecules or materials at exponential speed.

Majid Mufti of NEOM Investment Fund (NIF) placed this moment in recent history. “When Chat GPT was announced at the end of 2022… we saw an incredible amount of acceleration on new products and platforms… but we aren’t even seeing the maximum from LLMs yet.” Reflecting on the Internet’s emergence in the 1990s and the iPhone in 2007, he concluded: “The apex of AI disruption really is going to come from accelerated scientific discoveries, because that’s where a lot of the breakthroughs are coming in.”

Own the Data, Own the Market

Hasan Askari of K1 Investment Management invests in enterprise software. The companies standing out are those turning “a system of record into a system of intelligence”- using AI to find insights that would historically require hiring “dozens, if not hundreds of people.”

He highlighted one of his portfolio companies: a communications archive company that holds all email, text, and chat data for the top 20 global banks—hundreds of petabytes of regulated, immovable data. As he explained: “We hold banks’ communications data, which most people would tell you, you’re not allowed to train models on this type of stuff, but because the banks are incentivized to find what they need to find in our comms data, they actually make us use their data to train our models.”

Another example: an expense management platform (largest competitor to Concur) storing receipts for Fortune 500 companies.

“What stands out is not necessarily that you’re solving a problem that didn’t exist. I’m solving it in a much more efficient, much quicker way. You’ve got less people that need to monitor fraud, because AI can do that for you.”

For investors, it’s not just about big data, but the right data – essential, regulated, hard to move, and increasingly valuable as AI tools proliferate. These moats mean customers are sticky, competitors are locked out, and AI models can improve faster.

Talk the Talk: Why Communication Patterns Matter

There’s a subtlety in Hassan’s insight that separates truly valuable data from mere volume. His communications archive company doesn’t just hold a lot of data – it holds regionally diverse data that reveals how communication norms shift across the world.

“Communications data is actually the best kind of data to train models on top of because I can tell you how people in the US are communicating, how people in Saudi are communicating, how people in Korea are communicating, and what the nuances are and the signals that it provides.”

This point echoes through the broader conversation about AI in different markets. Majid Mufti emphasized that

“the LLMs that are being used in Saudi are going to be very different than the ones that are in Korea, where you’re looking for nuances – culture matters that actually make things more relevant to that region.”

For investors, this signals an important truth: an AI model trained on American data and deployed in Saudi Arabia will miss the mark. It will misread intention, misinterpret tone, misunderstand context. But a company with access to bank communications from across the globe – capturing how traders talk in New York versus Riyadh versus Seoul – builds something competitors can’t easily replicate: a cultural data moat.

Companies with access to regional datasets, trained on local communication patterns and cultural nuances, will build AI systems that work better for their markets. And investors backing those companies are effectively betting on a global advantage.

The Regulatory X-Factor

Majid Mufti explained why the region is uniquely positioned for the next wave of deep tech. “NEOM is meant to be a separate Administrative Region,” he said, “which means it’s going to have different types of regulations and laws that allow it to become a lot more business friendly, that lends itself to accelerated type of development.” The key: balancing “proper approach and governance, but without the bureaucracy and the red tapes that actually delays [innovation] from actually getting into the market.”

NEOM and similar projects are flush with data – from infrastructure, environment, health systems – that’s ready to be harnessed. The lesson: in an age where AI is hungry for unique, regional datasets, regulatory willingness and government support are true global differentiators.

The Silent Crisis: Top Scientists Are Leaving America

A consistent theme emerged: people still matter!  Nessan flagged a troubling reality:

“There’s a disconnect between the need and the actual amount of capital that’s there, and that capital is being eroded over time. Highly trained individuals [in the US] are not getting funding for their labs. They’re not getting the support that they need to enable them to continue to build and do the groundbreaking research. We’re seeing these people effectively either leaving by their own volition, or countries coming in and making offers to them, who actually proactively leave the US.”

Andrew Williamson confirmed this from the UK’s perspective. “I worked in the States for 20 years myself, and got a call a few years ago to lur me back to the UK… recently the UK Government was quick to set up an office for talent.” Today,

“When we want to recruit senior leadership for our portfolio companies from the States, maybe somebody who didn’t get their NIH grant renewed, we now have a toolbox to call them up and offer them a grant here, offer them a great job, bring their lab, and we’re starting to see that happen.”

What Investors Actually Want to See

For entrepreneurs raising capital, Majid’s advice was pointed. He emphasized the need for focus and milestone-driven progression: “We would love for a lot of the entrepreneurs to focus on the North Star. It is very important for us to see milestone-driven type of progression, because that milestone-driven progression says that you have a clear roadmap and you’re actually executing on that.”

Andrew, reflecting on his own journey from academic to entrepreneur to investor, underscored a counterintuitive insight: “It’s all about the people, right? When I was an academic scientist and I created a couple of businesses based on my science, I assumed that once I created that scientific breakthrough, I was 90% of the way there. And actually it’s 180 degrees the other way around. The people who know how to commercialize a breakthrough, turn it into a world leading product, technology, companies and do that scalably – that’s the scarce commodity.”

Looking Ahead

The consensus: AI is a new foundation for discovery, productivity, and value creation across sectors. Investors who understand the environments where talent, data, and supportive regulation combine will shape the future. In Menlo Park, Manhattan Beach, Cambridge, or NEOM, that’s where the real money is going.