2025/07/01 by Siphephisiwe Dube, Sadhana Manik · 1 voice
Agricultural and Biological Sciences · Social Sciences · #Climate change impacts on agriculture #African studies and sociopolitical issues #Agricultural Innovations and Practices
paper · pdf · doi:10.1002/geo2.70038
openalex publication_date 2025/07/01 · openalex created_date 2025/11/17 · openalex updated_date 2026/07/23
ABSTRACT Small‐scale farmers (SSFs) globally face numerous challenges, exacerbated by climate change, which severely affect their farming activities. This literature review paper reflects on poor, rural SSFs' climate‐smart strategies (CSS) providing possibilities to infuse artificial intelligence (AI) for resilience building in Zimbabwe. Currently, Zimbabwe is a country where climate change, socio‐economic and political challenges, along with power outages threaten rural livelihoods and food security. The research gaps are outlined on CSS, SSFs' challenges to respond proactively and using AI technologies for building resilience. The contribution of the article is thus to take stock of the current scholarship on CSS used by poor, rural SSFs. Recommendations deriving from this review can be used to intensify climate action for resilience building in Zimbabwe. A resilience framework guided the extraction of relevant literature. Using the AI tool ‘Ai2 paper finder’, we identified 64 relevant published articles and 13 publications of grey literature on CSS and SSFs' need to build resilience. The grey literature focused on identifying the common CSS being actioned elsewhere in Africa but relevant for Zimbabwe. Thematic content analysis was merged with storyline analysis and stories of successful resilience outcomes provide evidence on SSFs' resilience building. The findings revealed promising strategies: livelihood diversification, zero tillage, the adoption of weather‐tolerant small grains, climate smart livestock strategies and irrigation farming. Thus, micro‐, meso‐ and macro‐scale initiatives are advanced for resilience. The existing socio‐economic challenges hamper the use of CSS with advanced AI features. We argue that a combination of indigenous CSS and AI‐based weather prediction models and crop recommendation systems could empower SSFs in Zimbabwe to better adapt to climate change. However, multiple stakeholders need to commit to provide resources for Zimbabwe's SSFs given the limited investment by the country which has been plagued by decades of political and socio‐economic turmoil.