One System, Three Lenses
How AI capabilities, economic mechanism design, and climate science converge as a single integrated system — aligned with the UN Sustainable Development Goals.
The Integrated System
Climate change is fundamentally an economic coordination problem. AI offers unprecedented tools to solve it. But these aren't three separate domains we combine — they're three lenses on one interconnected system, where progress in each domain creates feedback loops that accelerate the others.
AI Capabilities
The Accelerator
Enhanced modeling, verification, prediction, and optimization. AI doesn't just process climate data — it reveals patterns invisible to traditional analysis and enables real-time market responses.
Economic Mechanism Design
The Architecture
Market structures, incentive systems, pricing mechanisms, and capital allocation frameworks. Economics provides the architecture through which AI insights become real-world action.
Climate Outcomes
The Imperative
Physical climate systems, emissions trajectories, tipping points, and adaptation needs. Climate science defines the constraints and urgency that shape every economic and AI decision.
The Feedback Loop
AI improves climate models → Better models reveal economic opportunities → Market signals guide AI development priorities →
AI verifies carbon credits at scale → Verification enables market trust → Market growth funds further AI development →
AI detects tipping point risks → Risk pricing reshapes capital flows → Capital funds climate solutions AI can optimize →
This is why we don't have three "pillars." We study one system through three lenses.
Mapped to Global Goals
Every research track at Economics & AI for Earth maps to specific UN Sustainable Development Goal targets. This isn't retroactive framing — the SDGs define the problem space our work addresses.
Primary SDG Alignment
Affordable and Clean Energy
AI grid optimization, renewable deployment economics, storage market design
Decent Work and Economic Growth
Just transition modeling, green workforce economics, AI labor market impacts
Industry, Innovation and Infrastructure
AI as innovation driver for climate infrastructure, smart grid economics
Responsible Consumption and Production
Carbon market design, circular economy frameworks, supply chain verification
Climate Action
Core mission — AI-enhanced climate-economic modeling, policy design, risk assessment
Secondary SDG Alignment
No Poverty
Ensuring AI-climate solutions don't harm vulnerable populations or widen inequality
Reduced Inequalities
Global North/South equity in AI access, technology transfer frameworks
Partnerships for the Goals
Multi-stakeholder research ecosystem, open collaboration model
"Leave No One Behind"
Adopted from the SDG framework's moral core. We commit that AI-augmented climate economics must not widen the Global North/South gap. Our research explicitly examines whether AI verification tools, optimization systems, and market mechanisms entrench advantages for well-resourced participants.
What We Measure
Inspired by the SDGs' cascading indicator architecture (17 goals → 169 targets → 232 indicators), we define specific metrics that make our research agenda empirically credible and our progress legible.
Model Accuracy Gap
Accuracy differential between AI-enhanced and traditional integrated assessment models (IAMs) for climate-economic projections
SDG 13.3Verification Cost Ratio
Cost of AI-powered carbon credit verification vs. manual verification methods across major registries
SDG 12.6Capital Deployment Velocity
Time from green finance commitment to deployment, comparing AI-screened vs. traditional due diligence pipelines
SDG 7.aAI Energy-Benefit Ratio
Computational energy consumed by AI climate tools relative to the emissions reductions they enable
SDG 9.4Equity Access Index
Ratio of AI climate tool availability and usability in Global South vs. Global North research institutions
SDG 10.bPolicy Uptake Rate
Number of policy recommendations from our research cited or adopted by governmental and multilateral bodies
SDG 17.14First annual benchmarks will be published in our inaugural State of AI in Climate Economics report.
Working Backward from the Deadline
The Paris Agreement targets demand unprecedented economic transformation by 2030. Only 17% of SDG targets are currently on track. We ask: what specific AI-augmented economic tools must be operational by 2030 for carbon markets, energy grids, and green finance to function at Paris Agreement scale?
Baseline Assessment
Benchmark current state of AI in climate economics. Map gaps between existing tools and Paris-aligned requirements. Publish inaugural indicators report.
Tool Readiness
AI-enhanced IAMs validated for policy use. Carbon verification costs reduced 60%+ via automation. Green finance screening tools operational across major markets.
System Integration
AI climate tools integrated into multilateral policy processes. Equity access metrics showing convergence. Cross-border carbon market interoperability enabled by AI verification.
Paris-Scale Operation
AI-augmented economic infrastructure operational at the speed and scale the Paris Agreement demands. Annual progress transparent through our indicator framework.
The SDG framework made the gap visible. Our job is to close the gap where AI, economics, and climate converge.
Explore Our Work
See how our strategic framework translates into active research and programs.