I’ve seen two companies go to zero. Not because of bad products, not because of a lack of funding, but because they were completely blindsided by risks they never saw coming. It’s a painful lesson to learn, and one that has stuck with me throughout my career as an entrepreneur and investor. Today, we’re facing a risk that dwarfs anything I’ve ever seen before: climate change. And just like those two startups, most of the financial world is still trying to understand it with outdated tools.
Climate change isn’t just an environmental issue; it’s a financial one. It’s about the tangible, dollars-and-cents impact of a changing planet on every single asset, every single portfolio, every single company. For years, the financial industry has been trying to model this risk with spreadsheets and teams of consultants. It’s like trying to navigate a hurricane with a paper map. It’s not just inadequate; it’s irresponsible.
I’ve spent my career in the heart of Silicon Valley, building and investing in companies that are solving hard problems. I was lucky enough to have two successful exits – RemoteTeam, which was acquired by Gusto, and MovieLaLa, which was acquired by Gfycat. I’ve also been fortunate to be an early investor in over 200 companies, including some of the most transformative AI companies on the planet like Anthropic, OpenAI, Scale AI, and Hugging Face. I’ve seen firsthand how powerful AI can be when applied to complex problems. And that’s why I’m so convinced that AI is the key to understanding and navigating the financial risks of climate change.
The Old Way of Assessing Risk is Broken
Think about how a bank or an investment fund traditionally assesses risk. They look at historical data. They build financial models in Excel. They hire expensive consultants to write long reports. It’s a process that’s slow, expensive, and, frankly, not very good at predicting the future. It’s like driving a car by only looking in the rearview mirror.
I remember one of my early investments, a company in the agricultural space. They had a great product, a solid team, and a growing market. But they were completely wiped out by a once-in-a-century drought that their models never saw coming. The data was all there – changing weather patterns, soil moisture levels, historical drought cycles – but it was spread across dozens of different sources, in different formats. No human could possibly analyze it all. The company went under, and it was a brutal lesson in the limitations of traditional risk assessment.
Now, multiply that by a thousand. That’s the challenge we face with climate change. We’re not just talking about a single drought or a single storm. We’re talking about a systemic, global shift that will impact everything from real estate and agriculture to insurance and energy. The old way of doing things just won’t cut it.
AI to the Rescue: Seeing the Invisible Risks
This is where AI comes in. If traditional risk assessment is like looking at the world through a keyhole, AI is like having a panoramic, 360-degree view. It’s a superpower. It allows us to see the invisible risks that are hidden in plain sight.
Machine learning models can ingest and analyze massive, unstructured datasets from a huge variety of sources. We’re talking about satellite imagery that can track deforestation and sea-level rise in real-time. We’re talking about weather data that can predict the frequency and intensity of extreme weather events. We’re talking about social media sentiment that can gauge public perception of a company’s environmental impact. We’re even talking about analyzing corporate disclosures and news articles to understand a company’s exposure to climate-related risks.
It’s about finding the patterns in the noise. It’s about connecting the dots between seemingly unrelated data points. It’s about building a dynamic, real-time picture of climate risk that is simply impossible to create with human analysts alone.
Real-World Examples: The AI-Powered Climate-Tech Scene
This isn’t just a theoretical concept. There’s a whole new generation of startups that are using AI to tackle this problem head-on. As an investor, this is one of the most exciting spaces I’m looking at right now. I’m seeing the same kind of energy and innovation that I saw in the early days of the internet and mobile.
Take a company like ClimateAi. They’re using AI to help companies in the agriculture and food sectors build climate resilience. They’re analyzing everything from long-term climate projections to short-term weather forecasts to help farmers make better decisions about what to plant, when to plant, and how to manage their resources. It’s a perfect example of how AI can be used to turn a risk into an opportunity.
Then there’s Eoliann, an Italian startup that’s using machine learning and satellite data to quantify climate risks for businesses and financial institutions. They’re helping their clients understand their exposure to everything from floods and wildfires to hurricanes and droughts. This is the kind of granular, asset-level data that is essential for making smart investment decisions in a changing climate.
These are just a couple of examples, but there are dozens of other companies that are doing incredible work in this space. It’s a testament to the power of a focused, mission-driven startup to solve a really big problem. It’s one of the reasons I love being an investor. I get to meet these brilliant founders and help them build their companies. While I haven’t invested in a pure-play climate-tech company yet, my investments in foundational AI companies like Anthropic and OpenAI are providing the picks and shovels for this gold rush.
It’s Not Just About Defense, It’s About Offense
So far, we’ve been talking about using AI to manage the downside risks of climate change. But what about the upside? What about the opportunities?
This is where things get really interesting. The transition to a low-carbon economy is going to be one of the biggest investment opportunities in history. We’re talking about trillions of dollars being invested in everything from renewable energy and electric vehicles to sustainable agriculture and carbon capture. AI can help us identify the companies that are going to be the winners in this new economy.
We’re starting to see the emergence of what some people are calling “climate alpha” – the idea that you can generate superior returns by investing in companies that are well-positioned for a low-carbon future. AI can help us find this alpha. It can help us identify the companies that are truly innovating, the ones that have a real competitive advantage, and the ones that are going to be the leaders in their respective industries.
This is a huge shift in mindset for the financial industry. For too long, sustainability has been seen as a cost center, a box to be checked. But now, we’re starting to see that it can be a source of value, a driver of returns. And AI is the engine that is going to power this transformation.
The Future is Uncertain, But We Have Better Tools
Look, I’m not a climate scientist. I’m a tech guy. But I know a big problem when I see one. And climate change is the biggest problem of our lifetime. It’s a challenge that is going to test our ingenuity, our resilience, and our will to act.
But I’m an optimist. I believe in the power of technology to solve hard problems. I’ve seen it happen time and time again in my own career. And I believe that AI is the most powerful tool we have in the fight against climate change.
The storm is coming. There’s no doubt about that. But for the first time in history, we have a weather forecast. We have the ability to see what’s coming, to understand the risks, and to prepare for them. It’s up to us to use it. The financial industry has a choice. It can either be a victim of this storm, or it can be a part of the solution. I know which side I’m betting on.
Frequently Asked Questions
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.