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Field
Abstract
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Before
This study evaluates the impact of an AI-powered agricultural advisory chatbot, Farmer.Chat, developed by Digital Green to enhance knowledge, technology adoption, productivity, and income among smallholder farmers in Kenya. Traditional agricultural extension systems in many low- and middle-income countries face persistent capacity and reach constraints, leaving farmers with limited access to timely, tailored information. Digital advisory tools have begun to bridge this gap, yet rigorous evidence on the effectiveness of AI-enabled solutions remains limited. We will implement a cluster-randomized controlled trial (RCT) in 600 villages in Nakuru County, Kenya, to assess the causal effects of access to Farmer.Chat on farmers’ knowledge, uptake of recommended agronomic practices, yields, and household income. The experiment will also include a cross-randomized video intervention designed to stimulate learning and behavioral change. The trial will be conducted across two agricultural seasons. Findings will provide some of the first causal evidence on the role of generative AI in agricultural extension, informing future efforts to integrate AI tools into scalable, farmer-centered advisory services.
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After
This study evaluates the impact of an AI-powered agricultural advisory chatbot, Farmer.Chat, developed by Digital Green to enhance knowledge, technology adoption, productivity, and income among smallholder farmers in Kenya. Traditional agricultural extension systems in many low- and middle-income countries face persistent capacity and reach constraints, leaving farmers with limited access to timely, tailored information. Digital advisory tools have begun to bridge this gap, yet rigorous evidence on the effectiveness of AI-enabled solutions remains limited. We will implement a cluster-randomized controlled trial (RCT) in 600 villages in Nakuru County, Kenya, to assess the causal effects of access to Farmer.Chat on farmers’ knowledge, uptake of recommended agronomic practices, yields, and household income. The experiment will also include a cross-randomized video intervention designed to stimulate learning and behavioral change. Within villages treated with FarmerChat onboarding, we embed two additional randomized, exploratory treatments: an expanded onboarding for other farmers in the village, and an experience sharing/feedback session with Digital Green. The trial will be conducted across two agricultural seasons. Findings will provide some of the first causal evidence on the role of generative AI in agricultural extension, informing future efforts to integrate AI tools into scalable, farmer-centered advisory services.
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Last Published
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Before
October 27, 2025 09:15 AM
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After
April 01, 2026 12:41 PM
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Intervention (Public)
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Before
There are two cross-randomized interventions:
(1) Farmers in the Farmer.Chat treatment will have the application installed on their phone.
(2) Farmers in the video treatment will be shown videos to increase aspirations and spark thinking of new ways of doing things, possibly supplemented with text messages and/or phone calls.
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After
There are two cross-randomized interventions:
(1) Farmers in the Farmer.Chat treatment will have the application installed on their phone.
(2) Farmers in the video treatment will be shown videos to increase aspirations and spark thinking of new ways of doing things, possibly supplemented with text messages and/or phone calls.
Within villages randomized to receive the FarmerChat treatment, we randomize and embed two additional exploratory treatments, alongside a group with no additional interventions. These interventions will be conducted several months after the sampled farmers were onboarded.
(a) Expanded onboarding: Digital Green will conduct expanded village-level onboarding sessions to FarmerChat, in line with their usual in-person expansion strategy
(b) Experience sharing and feedback: we will organize sessions for sample farmers and other FarmerChat users in the village to share their experiences with each other, and provide feedback to Digital Green
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Experimental Design (Public)
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Before
We use a cluster randomized controlled trial (RCT) with a 2x2 factorial design, assigning treatments at the village level to minimize potential spillover effects. The first intervention, Farmer.Chat, involves guiding farm households in treatment villages to download the app and giving some advice to craft queries. The second intervention is a video nudge: a subset of both treatment and control villages will be randomly assigned to receive a short video featuring a local farmer, aimed at lowering cognitive barriers, increasing aspirations, and promoting innovative thinking. Pending additional budget, we may reinforce the video nudge treatment with text messages and/or phone calls.
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After
We use a cluster randomized controlled trial (RCT) with a 2x2 factorial design, assigning treatments at the village level to minimize potential spillover effects. The first intervention, Farmer.Chat, involves guiding farm households in treatment villages to download the app and giving some advice to craft queries. The second intervention is a video nudge: a subset of both treatment and control villages will be randomly assigned to receive a short video featuring a local farmer, aimed at lowering cognitive barriers, increasing aspirations, and promoting innovative thinking. Pending additional budget, we may reinforce the video nudge treatment with text messages and/or phone calls.
Within villages randomized to receive the FarmerChat treatment, we layer two additional embedded, exploratory treatments, alongside a group with no additional interventions: expanded onboarding, and experience sharing/feedback sessions. 100 villages are randomized to each of these two embedded treatments, with an additional 100 villages held out to receive no additional intervention. These exploratory treatments will be conducted several months after the initial onboarding of sampled farmers in treatment villages.
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Sample size (or number of clusters) by treatment arms
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Before
150 villages control, 150 villages Farmer.Chat, 150 villages video nudge, and 150 villages both treatments
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After
150 villages control, 150 villages Farmer.Chat, 150 villages video nudge, and 150 villages both treatments.
Within the 300 villages randomized to receive FarmerChat, we randomize 100 to receive expanded onboarding, 100 to receive an experience sharing/feedback session, and 100 to receive no further intervention.
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