Tony is a Senior Advisor for natural capital and nature and Blu Skye Alum
AI and the planet
Like many of us, I have been closely watching the evolution of AI over the past 5 years. Topics of interest have included the impact on work and the economy, the energy footprint, and new intelligence platforms. The question that I am pondering is: Can AI have a net positive impact on the natural environment?
With the right intentions and execution, I believe that AI can be a powerful catalyst for the environment, equipping us with the data-driven tools to protect ecosystems, monitor biodiversity, and combat climate change. Conversely, AI has the potential to short the planet by expediting the depletion of natural resources and negatively impacting the quality of life for all species, while simultaneously providing short-term GDP growth. Which path will we choose?
The problem
Having stepped off the corporate bus 12-months ago, I have been exploring how I can use my experience and network to help regenerate the planet, starting with my birth continent, Africa. I was blessed to spend my formative years deeply immersed in nature throughout sub-Saharan Africa, and this connection has led me to spend most of my career working to protect nature. Recently, I have been collaborating with several organizations taking big bets on African conservation. In most cases, these organizations are operating with a structural gap in ecological intelligence.
For organizations that want to invest in natural capital (e.g., protected areas, sustainable agriculture), they need to know: What are the risks and which country is most investable? Is nature protected and well managed in that country? Is the specific project well managed and having a net positive impact? For business investments, there is an abundance of sovereign financial data, geopolitical analysis, tools, and metrics to make risk-adjusted decisions. But for natural capital investments, ecological intelligence is not readily available or integrated with business and sovereign data, thereby elevating risk.
An AI solution
To solve this gap, a friend and I have developed an AI model that serves as a pan-African conservation intelligence and finance platform, covering all 54 African countries and key protected areas (PAs). It is designed to support anyone deploying conservation capital across Africa, giving them an apples-to-apples comparison of country risk, country conservation performance, and protected area performance.
The platform uses large language models (LLMs) and data pipelines (e.g., credit ratings, conflict data, satellite feeds, biodiversity and carbon databases) to do at scale what three teams of sector analysts would do one entity at a time 24/7. In simple terms, AI scours the internet for every relevant public record, scores it against a fixed rubric, and rigorously validates the source and score.
While still in beta, our platform provides a defensible country risk and conservation performance score for every country in Africa, an effectiveness score for all target PAs, and a PA operator performance score. AI facilitates bringing real-time ecological, financial, and geopolitical intelligence into natural capital investment decision-making.
Potential applications include:
Guide funders where to invest and facilitates tracking of real-time conservation performance against key metrics over time (e.g., governance, biodiversity, community development, etc.)
Enable PA operators and NGOs to evaluate their performance against peers, thereby encouraging robust reporting, transparency, and shared learning
Provide PA operators with real-time data on security, fire, forest cover, and surface water to anticipate and manage threats to the PA
Give countries a snapshot of the health of their natural capital and performance against the United Nations Global Biodiversity Framework.
Where to from here?
Through our experiment, we have demonstrated that AI can be helpful to investors and operators by integrating ecological intelligence into investment decision-making. Broadening the aperture, a similar approach could be taken for regenerative agriculture, community development, or rural healthcare. Done correctly, this would meaningfully direct capital flows to maximize positive impact on nature and communities.
The recent launch of the United Nations Beyond GDP Report articulates the need to redefine GDP, prioritizing long-term well-being over financial performance that degrades the planet. AI can help achieve this goal, but it will not regenerate the planet by default; it must be intentionally directed towards ecological and social outcomes.
https://canopyconservation.com