Breaking Language Barriers: Empowering Ethiopian Farmers with Multilingual Digital Agricultural Tools

In Ethiopia, a country rich in linguistic diversity with over 80 indigenous languages, language can be both a cultural treasure and a barrier. While Amharic serves as the official working language, millions of rural farmers primarily speak their native tongues, making it difficult for them to access crucial agricultural information. From weather forecasts and pest control updates to market prices and government policies, much of this knowledge is often delivered in languages they do not fully understand, leaving many farmers without the information they need to make informed decisions.

Recognizing this challenge, Digital Green is working to break down language barriers and make agricultural knowledge more inclusive. We have developed a range of solutions to ensure farmers can access vital information in the languages they speak and understand. Our video-based extension services, for example, feature local farmers sharing best practices in their native languages, making learning more practical, relatable, and easier to adopt. Our AgAdvisory Telegram bot also provides instant access to farming advice, allowing farmers to get timely and relevant information at their fingertips.  Across these platforms, we have made agricultural knowledge available in more than 20 local languages.

Taking this a step further, we have successfully developed Farmer.Chat – an AI-powered chatbot designed to communicate with farmers—in two widely spoken Ethiopian languages, Afaan Oromo and Amharic. To ensure accessibility for all, including those with limited literacy, we have integrated voice features, allowing farmers to interact with the chatbot using spoken language rather than just text, making it easier for farmers to ask questions, receive guidance, and access information in a way that feels natural to them.

However, we recognize that our work is far from complete. Developing AI-driven multilingual solutions remains a challenge, particularly because many indigenous Ethiopian languages lack extensive written documentation that AI models typically rely on for training. Despite this, we are committed to expanding our work. By collaborating with local speakers, collecting high-quality language data, and leveraging audio-based AI training, we aim to bring Farmer.Chat and other digital solutions in more Ethiopian languages. Our goal is to ensure that farmers, regardless of the language they speak, have equal access to the information they need to improve their livelihoods and strengthen Ethiopia’s agricultural sector.

Through continuous innovation and collaboration, Digital Green is paving the way for a more inclusive agricultural future—one where language is no longer a barrier to progress but a bridge to knowledge and opportunity.