בינה מלאכותית להערכת העלויות והתועלות של הסתגלות לשינוי האקלים

From Methodology to Tool

The UN Environment Programme’s 2025 Adaptation Gap Report estimates that developing countries will require USD 310–365 billion annually for climate change adaptation by 2035, while international public adaptation finance amounted to only USD 26 billion in 2023. This gap is not only a challenge of mobilizing resources, but also, and perhaps more importantly, of allocating them effectively. When budgets are limited and needs are extensive, determining which adaptation measures justify investment becomes critical. Yet, based on our work in the field, many adaptation investment decisions by local authorities, government agencies, and businesses are still made without systematic economic analysis. Cost-benefit analysis (CBA) provides a framework for comparing alternatives by quantifying and discounting their costs and benefits over time. In Israel, a national methodology for cost-benefit analysis of adaptation measures has been developed under the leadership of the Ministry of Environmental Protection, with the involvement of the Ministry of Finance, the Prime Minister’s Office, and the Bank of Israel.

The Economic Rationale for Adaptation

The economic logic of adaptation is simple to describe but more complex to implement. Adaptation investments reduce expected climate-related damages, yet their marginal benefits decline as investment increases, and technological and other constraints place limits on adaptation. The objective is therefore to identify the optimal balance between the cost of adaptation measures and the climate damages they prevent. Applying the national methodology to 20 adaptation measures across areas such as urban heat, energy, agriculture, water, wildfires, and infrastructure showed that approximately 75% of the measures examined demonstrated clear economic viability, with benefit-cost ratios above one. Some of these findings were recently published in Ecology & Environment. Health benefits were the dominant component in many of the analyses, accounting for 60% to 85% of total benefits. “No-regret” measures, including nature-based solutions and early warning systems, also generated particularly high returns compared with capital-intensive engineering solutions. At the same time, producing each analysis can take weeks or months and requires specialized expertise, creating a potential gap between the growing demand for such analyses and the capacity to perform them.

An AI Tool for Cost-Benefit Analysis

Building on this methodology and the experience accumulated across the 20 analyses, we developed a tool based on a large language model (LLM) combined with a curated academic knowledge base. Importantly, the tool does not simply submit an open-ended question to a language model and return an answer. It uses a Retrieval-Augmented Generation (RAG) architecture and vector search to identify relevant information based on semantic similarity within a closed database of peer-reviewed articles and official reports. The tool identifies relevant adaptation measures, extracts quantitative parameters from the literature, highlights missing local data, and allows users to refine the assumptions underlying the analysis. It then produces a dynamic Excel model containing separate sheets for costs, benefits, assumptions, and sensitivity analyses, alongside calculations such as Net Present Value (NPV) and the Benefit-Cost Ratio (BCR). In a demonstration focused on urban heat in Tel Aviv, both street-tree planting and roof-related measures were found to be economically viable, while tree planting generated substantially higher benefits due to a broader range of co-benefits, including avoided heat-related mortality, energy savings, carbon sequestration, improved air quality, reduced stormwater runoff, and higher property values.

The ESG Connection

Although the tool was initially developed with governments and local authorities in mind, its relevance to the private sector and to ESG is direct. Emerging climate disclosure frameworks, including IFRS S2, require companies to identify physical climate risks, assess their financial implications, and describe how they are responding to them. Infrastructure, real estate, energy, insurance, and financial institutions therefore face many of the same questions as public authorities: which climate-resilience investments are economically justified, at what scale, and in what order of priority. A key distinction is that adaptation measures often generate both private benefits, such as energy savings or higher asset values, and public benefits, such as avoided mortality, improved air quality, and reduced urban runoff. A transparent analysis that separates these two types of benefits can help policymakers design incentives that mobilize private investment toward projects with proven social value. The tool is not intended to replace professional judgment or human review, but to significantly reduce the time and cost required to produce an initial, evidence-based analysis. In a world where the adaptation gap continues to widen, making the economics of adaptation more accessible can itself become an adaptation tool.

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Gur Angel and Dan Brodsky, economists and members of the team that developed Israel’s national methodology for cost-benefit analysis of climate change adaptation.