LEVERAGING ARTIFICIAL INTELLIGENCE FOR CLIMATE RESILIENCE AND SUSTAINABLE NATURAL RESOURCE MANAGEMENT IN KENYA

Artificial Intelligence (AI) holds significant potential in enhancing climate resilience and supporting sustainable natural resource management in East Africa. Sustainable natural resource management requires a long-term stewardship of resources in order to meet current needs without compromising future generations. This can be achieved through adoption of AI which has emerged as a transformative tool in addressing critical environmental issues. As climate-related shocks intensify, AI technologies are providing rapid and accurate insights for monitoring environmental changes, forecasting risks and informing adaptive responses. This study sought to examine how leveraging AI for climate resilience aids sustainable natural resource management in Kenya. The study was guided by one objective; to examine how AI can support sustainable natural resource management. Socio-Ecological Systems Theory guided the study. The study is adopted a desk top /secondary data research design. The study relied entirely on existing data published between 2020 and 2025. The targeted secondary data was 188government reports, academic journals and records and development partner publications relevant to the study topic. The sample was filtered down to 40 articles and reports forming the sample size. Data in this study was purposefully sampled and by methodically choosing pertinent peer-reviewed journal and articles, the inclusion criteria being publication date between 2000-2025 on AI and climate resilience and sustainable natural resource management. Data collection included structured online searches, document screening, and extraction of key variables linked to AI adoption and sustainable natural resource management. Thematic content analysis was also used to categorize findings into themes and analyzed thematically based on the research objective. The study findings indicate that AI enhances natural resource management in Kenya at the micro system level through improved monitoring, yet faces significant barriers at the exosystem and macro system levels, including inadequate infrastructure, data scarcity, and limited local expertise among others. The study further found that these structural constraints threaten and undermine the potential of AI in promoting sustainability of natural resource management. The study concluded that successful AI integration requires moving beyond isolated technological applications to foster holistic, cross-sector collaborations and robust data governance. The study makes a recommendation on laying emphasize on the need for strengthening policy ecosystems through localized, ethical data practices, increased investment, and capacity building to bridge the digital divide. As with these innovations, AI’s transformative potential will strengthen long-term climate resilience and reshape environmental governance.