Climate change remains one of the most pressing global challenges, with far-reaching impacts on ecosystems, economies, and communities worldwide. Africa is disproportionately affected by these impacts despite contributing minimally to global greenhouse gas (GHG) emissions (AfDB, 2019). This heightened vulnerability is attributed to the continent’s over-dependence on climate-sensitive sectors, coupled with limited institutional, technological, and financial capacities to reduce emissions and build climate resilience (Doku et al., 2021a, 2021b; Mekonnen et al., 2021; Phiri & Doku, 2024).
As climate risks intensify, there is a growing urgency for innovative, data-driven solutions. Artificial intelligence (AI) has emerged as a critical tool for developing and implementing climate resilience strategies (Ferrari, 2024). AI supports the design of models, forecasts, and decision-making systems essential for understanding, predicting, and mitigating climate risks. It strengthens climate information systems and predictive capabilities, enabling more effective resilience planning (Amiri et al., 2024).
AI’s capacity for data analysis, prediction, and decision support underpins the development of early warning systems that alert communities to impending climate-related disasters. By analyzing large datasets from satellites, weather stations, and other sources, AI-powered systems can detect patterns and identify early signs of extreme weather events. This includes predicting changes in temperature and precipitation patterns, which are vital for planning in key sectors such as agriculture. The ability to deliver timely and accurate information supports critical planning efforts for farmers, communities, and governments (Jain et al., 2023; Weaver et al., 2022).
However, significant challenges hinder the potential of AI in climate resilience. Chief among them is the lack of adequate skills to deploy and interpret AI-driven climate modeling tools for resilience planning and resource allocation. This skills gap is driven by two main factors:
- Limited training opportunities in AI-related Science, Technology, Engineering, and Mathematics (STEM) subjects within Africa.
- Persistent gender disparities in AI fields, with a significantly low representation of women in academia and the AI workforce.
Addressing this capacity gap is critical, especially for early-career researchers and policymakers who play a vital role in climate action across Africa. Governments and stakeholders face challenges in adopting adequate and inclusive reporting frameworks for climate action. Enhancing AI expertise would improve Africa’s capacity to strengthen resilience and facilitate evidence-based reporting on climate progress.
To address these challenges and harness the transformative potential of AI, the Africa Research and Impact Network (ARIN) hosted a sensitization webinar to bring together key stakeholders, including academics, policymakers, and industry experts. The webinar aimed to explore how AI and mathematical sciences could strengthen climate resilience across Africa.
The Director of ARIN opened the session by underscoring Africa’s disproportionate vulnerability to climate change despite its minimal contribution to GHG emissions. He highlighted AI’s transformative potential in enhancing resilience through improved financing mechanisms, early warning systems, and data-driven policy innovations. The Director also emphasized ARIN’s ongoing efforts to support locally driven adaptation strategies, which are key to building climate resilience.
ARIN’s initiatives in this area include the development of Africa-led resilience programs, the creation of locally led adaptation metrics, and policy fellowships designed to foster evidence based climate resilience policies and practices. The webinar also featured findings from a landscape scoping of AI initiatives across Africa, which revealed the need for stronger institutional capacity, gender equity, and sustainable funding to develop and scale AI-driven climate solutions.
