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Feasibility study on the Integration of AI and ML in weather forecasting
Procurement Process
RFP - Request for proposal
Office
UNDP-RWA - RWANDA
Deadline
25-May-25 @ 08:00 PM (New York time)
Published on
28-Apr-25 @ 12:00 AM (New York time)
Reference Number
UNDP-RWA-00253
Contact
Procurement Office - procurement.rw@undp.org
Introduction
Recruitment of a National Consulting Firm to Conduct a Feasibility study on the Integration of Artificial Intelligence (AI) and Machine Learning (ML) in weather forecasting, and climate information services in RwandaContract Type: National consulting firm
Location: Kigali
Languages Required: English
Duration of Assignment: 70 days within 3.5 months
1. BACKGROUND
As the world becomes increasingly data-driven, the integration of Artificial Intelligence (AI) and Machine Learning (ML) is transforming how meteorological and climate information is generated, analyzed, and delivered. Leading global meteorological agencies are leveraging AI/ML to enhance forecast accuracy, automate workflows, and provide tailored Climate Information Services (CIS) to diverse users.
Rwanda has made significant strides in modernizing its observation networks and forecasting systems, but the growing climate crisis and rising demand for customized CIS highlight the urgent need for a shift toward AI-powered forecasting. To address this challenge, a strategic, sustainable, and inclusive approach is needed, considering the country's existing technological, human, and institutional capacities.
The adoption of AI and ML offers significant potential to transform Meteo Rwanda's forecasting and climate information workflows, positioning Rwanda as a regional leader in climate-tech innovation. By improving weather predictions, climate analysis, and the delivery of user-centric Climate Information Services (CIS), AI and ML can enhance forecast accuracy, lead time, and risk-based decision-making.
This consultancy will assess and evaluate Rwanda's readiness to integrate AI and ML technologies and provide a strategic roadmap for responsible, inclusive, and impactful implementation. It presents a timely opportunity to strengthen national early warning systems, develop more responsive and anticipatory mechanisms, and enhance community resilience to extreme weather events. Aligned with national strategies for climate resilience, digital innovation, and early warning systems, this consultancy aims to address key challenges in forecasting accuracy, data integration, and communication reach, ultimately driving progress toward sustainable development.
2. OBJECTIVE OF THE ASSIGNMENT
The primary objective of this consultancy is to conduct a comprehensive feasibility study and develop a strategic, costed, and phased roadmap for the integration of Artificial Intelligence (AI) and Machine Learning (ML) into Meteo Rwanda’s operational forecasting and climate information services. The focus is on enhancing early warning systems, disaster preparedness, and the overall effectiveness of climate services.
This feasibility study aligns with Rwanda’s commitments to climate adaptation, digital transformation, and sustainable development. This includes:
• Benchmarking international best practices and successful models of AI/ML integration in operational forecasting systems and Climate Information Services (CIS) globally
• Identifies Rwanda-specific gaps, challenges, risks, opportunities, and enabling environments for AI/ML integration and adoption in Weather Forecasting, and Climate Information Services in Rwanda.
• Proposes a future vision for AI-driven forecasting in Rwanda and priority use cases.
• Develop a clear, costed, and sustainable phased roadmap that is inclusive, ethical, and technically viable for achieving AI/ML integration, aligned with international standards and national development goals.
• Outlines how Rwanda can position itself as a regional innovator in AI for climate services
3. SCOPE OF THE ASSIGNMENT
The study will adopt a systems-level approach across national and sub-national levels, ensuring that both technical capacities and local/community-level perspectives are incorporated. The assessment will focus on inclusivity, relevance to priority sectors, and readiness for AI/ML integration in Rwanda’s climate and risk management ecosystem.
The consulting firm will be responsible for conducting an in-depth technical, institutional, and comparative assessment focused on both global benchmarks and local contexts, culminating in a set of actionable recommendations and a roadmap.
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UNDP RWANDA COUNTRY OFFICE
PROCUREMENT UNIT