Kenya is conducting its first comprehensive census of agriculture since independence, seeking to establish a detailed picture of land use, farm ownership, crop and livestock production, fisheries and agricultural labour that could influence how public resources, climate finance and private investment reach farming communities. The 2025/26 Kenya Census of Agriculture, led by the Kenya National Bureau of Statistics (KNBS) in collaboration with the Ministry of Agriculture and Livestock Development, is intended to address longstanding gaps in the data used to plan support for one of the country’s most economically significant sectors.
According to KNBS, agriculture directly contributes about 24% of Kenya’s gross domestic product, while approximately 72% of the population derives its livelihood directly or indirectly from the sector. The quality of agricultural statistics therefore has implications beyond farm productivity, affecting food security, rural employment, county development planning, infrastructure investment and the government’s ability to respond to climate-related shocks.
Kenya has lacked a comprehensive agricultural census covering the full structure of the sector since independence. KNBS says annual censuses of large farms continued until the early 1990s before being discontinued because of funding constraints. The 2019 population census included an agricultural module, but its coverage was limited to household farming and excluded commercial and institutional agricultural holdings.
The current exercise is designed to provide a more complete account of agricultural activity, including the characteristics of holdings, land tenure, production systems, livestock, labour and the inputs used in farming. By producing information at lower administrative levels, the census could help policymakers distinguish between the needs of different farming communities rather than relying primarily on national totals or broad county averages.
That distinction is important in a country where agricultural production ranges from commercial horticulture and irrigated farming to rain-fed smallholder agriculture and pastoral livestock systems. Land tenure and crop-area data could help identify areas where fragmented holdings constrain production, while information on livestock, fisheries and aquaculture could improve planning for livelihoods that are not adequately captured by crop-focused programmes.
For county governments, more detailed data could support decisions on where to allocate extension officers, improve rural roads, invest in irrigation and water infrastructure, or expand access to agricultural inputs. It could also help identify communities facing shortages of finance, technology and advisory services. The census will not resolve those constraints by itself, but it could provide a stronger evidence base for deciding which interventions are needed and where they are most likely to be effective.
Climate exposure makes the exercise particularly relevant. Farmers in drought-prone areas, flood-affected regions and water-stressed production zones face different risks depending on their crops, livestock, access to irrigation and dependence on seasonal rainfall. More detailed information on those production systems could help government agencies design agricultural insurance, drought assistance and recovery programmes around the circumstances of affected communities.
The implications extend to climate and development finance. Lenders, insurers and development partners need credible baseline data to identify beneficiaries, assess exposure and measure whether investments improve productivity or resilience. A more complete record of agricultural holdings could help institutions establish where financing is needed, which groups remain underserved and whether programmes are reaching their intended beneficiaries.
Without reliable data, however, funding decisions risk favouring areas where projects are easier to document rather than those facing the greatest constraints. For investors considering agricultural value chains, better statistics could also reduce uncertainty about production volumes, the distribution of farming activity and the potential reach of services such as insurance, storage, processing and digital advisory platforms. The extent of that benefit will depend on the quality, accessibility and continued relevance of the information collected.
Kenya’s draft Agricultural Data, Information and Digital Agriculture Policy identifies fragmented data systems, limited interoperability and the absence of a coherent national architecture as barriers to the effective use of agricultural information. Farmer registries, digital advisory platforms, market information systems and climate services have expanded, but their value is constrained when information cannot be reliably exchanged across institutions.
The census could provide a common statistical foundation for these systems. However, a one-off count cannot substitute for regular updates in a sector where land use, market conditions, weather patterns and farm ownership can change quickly. Linking census findings to administrative records and future surveys, while maintaining consistent definitions and methods, will be important if the information is to remain useful for planning and investment.
Data governance will also shape the census’s long-term value. Agricultural information can influence farmers’ access to credit, public support, insurance and markets. Authorities will therefore need safeguards governing how individual records are collected, stored, shared and used, alongside clear distinctions between confidential information and statistics that can be published for public planning. Weak protections or limited transparency could undermine participation and create risks for farmers whose information is used in decisions affecting their livelihoods.
According to KNBS, the census is expected to establish benchmarks for crop and livestock statistics, provide sampling frames for future surveys, inform resource allocation and support monitoring of agricultural programmes and the Sustainable Development Goals. Its approach aligns with the Food and Agriculture Organization’s World Programme for the Census of Agriculture, which promotes standardised concepts and methods to improve the quality and comparability of agricultural statistics across countries.
The wider development challenge is familiar across Africa, where gaps in agricultural data can complicate food security planning, climate adaptation and efforts to attract investment into rural economies. Reliable information is particularly important as governments face competing demands on public budgets and seek to demonstrate that agricultural subsidies, infrastructure spending and climate-related funding are reaching the intended beneficiaries.
For Kenya, the decisive stage will follow data collection. The results will need to be published in accessible formats and translated into decisions that county planners, cooperatives, financial institutions, insurers and agricultural extension services can use. If the findings remain concentrated in national reports, their practical effect on farming communities may be limited.
The census offers an opportunity to improve how Kenya understands and finances its agricultural economy. Whether it changes farm policy and climate investment will depend less on the volume of information collected than on how consistently public institutions and private sector actors use it to direct resources, manage risk and respond to the needs of different farming systems.
