AI, Climate Tech and the Futures We Choose

When we talk about “climate tech” or “AI for climate”, the imagination often defaults to techno-optimistic scenarios like carbon capture, renewables, or Silicon Valley-driven innovation. But in Asia, where climate vulnerabilities are deeply entangled with questions of equity and governance, the intersection of AI and climate looks very different.

At Digital Futures Lab, as we wind down the first season of the Code Green series, we look back at the last few years of our work in the domain. Through both Code Green and AI + Climate Futures in Asia, we captured the complexities in the arena, surfacing plural, often overlooked innovations and ground-level challenges of developing and implementing AI solutions, and asked: How is AI shaping climate action in the region, and whose futures are being imagined in the process?

From foresight exercises with regional experts to mapping everyday climate-tech innovations across Asia, here’s what we’ve learnt:

1. It’s critical to think beyond dystopia; we need futures thinking and hope

When we first began, conversations around AI and climate were few and far in between. During our first foresight workshop with regional experts from Asia, we found participants chiefly defaulting to dystopian futures. The present data was grim, and the pace of climate and tech change felt overwhelming. Using foresight methods like scenario-building and backcasting helped bring structure to climate imaginaries and surfaced the need for principles to guide AI adoption in climate work. Experts worked backwards from desired futures — such as resilient, low-carbon societies — to identify the interventions and governance frameworks that could make them possible.

2. AI for climate action is plural and can broaden what innovation means

Throughout the making of Code Green, we have learnt that AI in climate action is not confined to large-scale mitigation tools. It includes low-resource language models for community advisories, AI-enabled monitoring of local ecosystems, as well as small-scale predictive tools for agriculture. These plural innovations highlight the role of smaller, localised climate-AI innovations in delivering effective climate solutions to vulnerable populations, challenging the popular perception of “climate AI” as only high-tech.

3. Equity and participation must guide AI development

AI-powered climate tools risk reinforcing inequities if designed without community participation. Who decides how datasets are collected? Whose languages and geographies get represented? Our research shows that climate AI solutions must be evaluated not only for efficiency or accuracy, but for who they empower and who they leave behind and whose knowledge they centre.

4. Visibility enables opportunity

In Asia, many grassroots experiments with data, AI and climate need to be made more visible to policymakers and funders. Mapping them is not just documentation but recognition: a reminder that AI-driven climate innovation is happening outside big labs and corporations. Visibility expands the imagination of what is possible — who counts as an innovator, and what climate action can look like.

5. AI is not a silver bullet — it must be embedded in systems

AI can model risks, optimise resources, and enable new forms of participation. But technology alone cannot solve climate challenges. Both projects remind us that AI must be embedded in broader ecological, social, and political systems — where unintended consequences (bias, lock-ins, new dependencies, climate costs) are anticipated, and justice is foregrounded.

At DFL, we believe that AI is not a silver bullet, but a space for responsible experimentation, participation, and futures-thinking. Through our work, we invite policymakers, developers, funders, and researchers to see beyond narrow imaginaries — and to support diverse, grounded approaches that can make just technology and climate futures tangible.

For deeper insights, take a look at our flagship projects on AI and climate:

• Code Green: A newsletter and podcast series showcasing the latest interdisciplinary research and initiatives at the intersection of AI and climate action in Asia. Separating the heat from the hype around AI and climate action, this first season of the series was published by Digital Futures Lab, in partnership with Earth Venture Foundation.
• AI+Climate Futures in Asia: Commissioned by The Rockefeller Foundation, AI+Climate Futures used foresight methodologies to examine the opportunities, challenges and risks at the intersection of AI and Climate Action across nine countries and three sectors.
• Nature-based Solutions - Fostering an Inclusive Approach to Technological Innovations by Marginalised Voices: A policy brief co-authored by Dona Mathew and Pyrou Chung where they address the risks associated with technology-enabled NbS solutions, and urge a nuanced understanding of technology's potential within the context of preserving and restoring our natural environment. Read more for their recommendations for a cautious approach informed by self-determination and reciprocity.

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