An AI Startup Takes Us Inside the Business of Climate Resilience
Climate change demands climate action. Add artificial intelligence to the problem-solving portfolio, and technology is helping businesses adapt to an increasingly hotter planet. In industry lingo, this is called climate resilience.
To understand this emerging field, Wharton Global Youth explored the intersection of climate change, AI, and business resilience with a startup company among the 2024 innovators selected for the Cypher Accelerator at Wharton’s Stevens Center for Innovation in Finance.
Eoliann, founded in Italy in 2022, uses machine learning and earth observation data to quantify climate risks for businesses and financial institutions. Eoliann’s tagline: Building climate resilience from the sky.
We caught up with Federico D’Albenzio, Eoliann’s business developer, to learn about the company’s software, which provides detailed, quantitative analyses of exposure to climate risks like floods and hurricanes, and how AI supports that work.
Federico, what are three things we need to understand about the business of climate resilience?
Feeling exposed. As temperatures rise, businesses are adapting to survive. For example, banks need to assess the exposure of their credit portfolios to climate risk to know if it is safe to loan money to certain clients. “Climate risk is the potential exposure of a physical asset (i.e., industrial facilities, residential buildings, agricultural fields) to extreme events, such as floods, wildfires and hurricanes,” says D’Albenzio. “We can still save the planet, but we have to adapt to it. That means we need to understand how these phenomena will change our lives. We need to be prepared to mitigate the risks.”
Data-driven decisions. Eoliann provides quantitative data on the probability, intensity and vulnerability of assets to floods and other climate-related threats. Banks, for example, can then make informed decisions about providing loans (or not, if the risk is too high) and encourage clients to take actions that will mitigate their climate risk. Eoliann uses AI to process the huge volumes of data it receives from three different satellite constellations; data that is constantly updating information about the planet. “Thanks to AI, we can process this data…and we can simplify the methodologies,” notes D’Albenzio. “AI makes it possible to use data to create new models that are much more efficient compared to statistical modeling…Our founders are very technical people who studied a lot of math and physics. Then they said, ‘How can we model our reality in numbers; in technology that has an impact?’ If you have the tools to understand the reality, and you know what you want to get in the end, AI becomes an enabler to get you there.” The innovation: detailed, numbers-driven risk assessments.
Unsung climate risks. As Eoliann grows and raises funds to scale its solutions across Europe and the U.S., it is developing a deep expertise in climate-related exposures, even those that don’t get as much airtime as high-profile hurricanes and wildfires. “Droughts are climate risks [that get less attention], observes D’Albenzio. “They are potentially so impactful because they affect every part of the value chain in the end, from energy generation, to the production of agricultural crops, to water accessibility. It’s crazily important in my point of view, and right now, people are not taking droughts into account.”
Intrigued to learn more about climate risk? Tune into a recent episode of Wharton’s Ripple Effect podcast featuring Witold Henisz, vice dean and faculty director of Wharton’s ESG Initiative, who talks about “Why Climate Risk is Financial Risk.”
Conversation Starters
What is climate resilience?
How does Eoliann build climate resilience from the sky?
Federico D’Albenzio says, “We can still save the planet, but we have to adapt to it. That means we need to understand how these phenomena will change our lives.” What does he mean by this? How are you adapting to changes brought about by climate change? Share your story in the comment section of this article.
Hero Image: Ales Krivec, Unsplash+
This article is helpful and packed with valuable information! It really nice my understanding on the topic. Thanks
This article does a wonderful job of outlining how AI startups like Eoliann are moving climate resilience from being a response mechanism to an ongoing, data-driven practice. Through the use of machine learning interpreting satellite imagery, Eoliann allows banks, insurers, and governments to quantify—and price—climate risk correctly.
1. Integrating climate risk into financial decision-making
Eoliann’s framework develops climate resilience by shedding light on latent hazards—floods, droughts, wildfires—before they become monetary loss. It brings to mind my background in AWS and Python analytics, where forecast models analyzed SMS data in underserved populations to predict financial hardship. In each instance, early warnings become strategic handles. Banks employing Eoliann can proactively tweak credit terms or demand climate-resilient plans—transitioning from reactive lending to risk-conscious stewardship.
2. Democratizing climate intelligence with AI
The article explains how AI condenses satellite information into valuable insights—a step ahead of ancient statistical models. In my data work with nonprofits, I built low-cost dashboards to track campaign outreach in real time. Eoliann is doing the same for climate: condensing massive datasets into concise risk scores. This kind of technology translates complexity into clarity—something that human-centered AI does instinctively.
3. Raising awareness about neglected climate risks
I was particularly struck by their emphasis on drought analytics—a less-spoken-about but disastrous danger. Droughts disrupt entire agriculture value chains. Similarly, at Bhoomika Trust during my internship, minor dips in donor engagement frequently preceded campaign burnout—and watching for those signals in advance enabled us to pivot. Eoliann’s sensitivity to nuanced climate data speaks to this—we need to deal with less-wild but systematic risks before they develop into crises.
Where I’d like the conversation to go next
• Integration with insurance products: Are banks or insurers using Eoliann’s risk scores to adjust premiums or tailor micro-insurance for vulnerable regions?
• Ecosystem approach: Could Eoliann partner with fintech and aid platforms, automatically triggering micro-grants or credit extensions for farmers, businesses, or communities flagged as at high risk?
• Transparency and equity: How does Eoliann prevent its models from perpetuating geographic bias—e.g., favoring wealthy regions with more data—while ensuring equitable outcomes?
Climate resilience for societal good demands more than tech—it requires orchestration: AI analytics, financial tools, policy frameworks, and social inclusion. Eoliann is making smart progress on the first two pillars; I’m curious how they’re preparing for the rest.
Thanks, Diana, for bringing global light to startups at the helm of this movement. Saving the world will indeed not be achieved in laboratories in a vacuum—it will take AI-driven vision ingrained in fiscal systems, social movements, and worldwide policy. That’s the resiliency of the future—and next-gen innovators are on the lead.
This article and Eoliann’s role in climate resilience got me thinking about another potential application of AI related to environmental sustainability. Rising and increasingly unpredictable temperature swings, changing tides, and pollution have made parts of the Potomac River near my home often unswimmable, and unhealthy for many species of fish. I am part of a group that tests the water weekly. We report on turbidity, bacteria levels, temperature, and PH level. We also note tides, time of day, air temperature weather, and recent rainfall. Similar to how Eoliann predicts climate related vulnerabilities for businesses, I would like to explore building a program that uses all of the data that we collect to predict when the water might be safe for swimming, even during weeks we don’t perform out testing. Federico D’Albenzio says, “We can still save the planet, but we have to adapt to it. That means we need to understand how these phenomena will change our lives.” This made sense to me. Part of testing the river is to help identify sources of pollution to help keep the river as clean as possible. But it is also to protect the people and pets that swim or boat in the river by letting them know that at times, the river is no longer safe to swim in. As the data starts to tell a different story we communicate it. This is what I liked most about what Eoliann is accomplishing.