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Making climate funding catalytic in the age of AI
At Milkywire we are always asking the same question: how do we make every dollar invested for climate and nature as catalytic as possible? To us, catalytic means leverage. It means stepping in where others won't, generating learning that benefits the wider ecosystem and building things that outlast our funding. That north star shapes every funding decision we make. With climate funding in retreat globally, doing more with less has become even more urgent.
Anna Samuelsson
Chief Impact Officer
AI is one of the most powerful multipliers we have seen in years.
The organizations we back dedicate their time to some of the hardest things you can do: defend Indigenous land rights, restore ecosystems, test novel carbon removal methods, hold governments accountable and much more. In the past years, they have become more resource constrained than ever, while the urgency to address the problems they work on keeps increasing.
These organizations could compound their impact dramatically if they had the means to use AI well. That case is not hard to make. But for most teams this capacity does not happen by itself. Many of our organizations testify that they are held back by a fear of getting it wrong. Some are curious but cautious, others not willing to try at all. That is not a technology problem. About a year ago I met Anna Lerner, CEO of Climate Collective, who taught me about the concept of "AI fluency." It means going beyond access to tools, building the knowledge and judgment to use AI in ways that actually move the needle. The AI for Earth Accelerator is set up to address exactly that problem.
Together with Klarna, we supported 14 of our organizations through the AI for Earth Accelerator. They spent five months building practical AI fluency, not just how to use the tools, but how to identify where AI actually adds value, and how to navigate it responsibly. The results were impressive:
105% increase in participant confidence.
Learnings reaching teams of 60+ staff inside those organizations.
One team cut reef ecological reporting time by 75%, freeing their scientists to get back in the field.
Another hit a $300,000 fundraising goal in weeks.
This is a great example of what catalytic funding looks like. Not just backing great organizations financially, but making sure they have what they need to move the needle in a world that is changing fast.
We hear a lot about the risks and negative impacts of AI, and that conversation matters. But so does this one. For fellow funders: the question is not whether your grantees are using AI. It is whether your funding is helping them use it well, and responsibly. By doing so, you are also part of ensuring AI has a positive footprint in the world.
