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Pioneering AI-Driven Climate Adaptation for Agriculture In Global South

October 15th, 2025

The Background

ClimateAi, in collaboration with NEC, has developed a conceptual model to estimate the effectiveness of climate change adaptation measures for cocoa and rice cultivation in Africa. ClimateAi’s long-term climate forecasting technology, which models both the impact of climatic factors on agricultural production and the effectiveness of adaptation measures, was combined with NEC’s expertise in agricultural technology to quantify the impact of climate change on agriculture and clarify the return on investment for adaptation strategies.

This achievement was showcased at the TICAD Business Expo & Conference, one of the thematic events of the Ninth Tokyo International Conference on African Development (TICAD 9).

Why This Matters

Globally, greenhouse gas reductions and carbon credit trading are advancing, yet adaptation measures to prevent or reduce climate damage have lagged. A key barrier has been the difficulty of assessing the cost-effectiveness of investments such as irrigation facilities or changes in crop varieties.

Agriculture, one of the industries most vulnerable to climate change, has lacked reliable ways to estimate the return on adaptation. NEC and ClimateAi’s model addresses this by analyzing climatic and agricultural factors using AI to calculate the economic value of adaptation measures. This enables governments, organizations, and businesses to implement strategies where benefits are expected, supporting agriculture more efficiently and sustainably.

The Model in Action

Some graphs showing the ROI of using adaptation in rice growing, a collaboration between ClimateAi and NEC.The conceptual model was applied to cocoa and rice cultivation across Africa, where agriculture is a vital industry and cocoa is a leading export crop. Three key adaptation measures were analyzed:

  • Introduction of irrigation facilities
  • Changing to climate-adapted varieties
  • Adjusting planting times for traditional varieties

The model quantifies how these strategies affect yields and economic value under changing climate conditions. Results can also be tested through interactive demonstrations. Potential users include international organizations and development banks, which could apply the model to assess farmland suitability and estimate the benefits of adaptation projects.

“With ClimateAi, It has become possible to predict the return on investment for climate change adaptation measures, which had previously been challenging, based on data. This conceptual model will change the flow of investment funds towards climate change, which hasn’t received adequate investment, and accelerate adaptation.”

Megumi Eto – Director, NEC Corporation

Results and future outlook

The NEC–ClimateAi model demonstrated how AI can bridge the gap between climate science and economic decision-making, offering stakeholders a practical tool to evaluate adaptation strategies with confidence.

  • Quantified ROI for adaptation measures — bridging the gap between climate science and economic decision-making.
  • Developed a decision-support tool for international organizations, development banks, and agribusinesses.
  • Highlighted cost-effective strategies to sustain cocoa and rice yields under climate change.
  • Opened doors for public-private investment by clarifying long-term value creation.

“With NEC, we’re converting climate risk into an investable adaptation roadmap for the Global South—using GenAI to pre-test adaptation so every dollar lands where it lifts yields and improves lives. By fusing NEC’s agritech with ClimateAi’s climate-intelligence, we replace guesswork in adaptation measures with ROI-grade evidence.”

Himanshu Gupta – CEO, ClimateAi

Reaction From Market

The NEC-ClimateAi model was exhibited at international conferences and received positive feedback from potential users.

International organizations during conferences reviewed:

  • It will be possible to utilize it within the HQ division responsible for investment strategy.
  • It is possible to utilize for the project evaluation.
  • You have developed a decision-support tool.
  • From now on, such AI should be utilized in development projects.
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