An Ai-driven Livestock Communication Model for Enhancing Farmer Engagement: A Field Study from Sirsa, Haryana

Daya Nand Kadian; Hardeep Kalkal

doi:10.48165/jvls.2026.2.01.01

Abstract

The adoption of digital technologies in livestock farming is often limited by gaps in farmer engagement and ineffective communication systems. This study evaluates an AI-driven communication model designed to enhance livestock management practices through improved interaction and behavioral motivation among farmers in Sirsa district of Haryana. A field survey was conducted among 59 livestock farmers using structured questionnaires and personal interaction. The study assessed digital access, livestock practices, and farmer responsiveness to AI-based tools. Results revealed that while 95% of farmers used mobile communication platforms, only 18% had experience with livestock applications. A majority (88%) preferred voice-based communication, and 76% showed increased motivation through performance-based engagement features. Farmers also showed willingness to adopt simple data recording practices such as milk yield and animal weight tracking. The findings indicate that effective communication design, simplicity, and engagement mechanisms play a critical role in technology adoption. The study concludes that integrating artificial intelligence with participatory communication strategies can significantly improve farmer engagement and decision-making. The proposed model offers a scalable solution for strengthening digital livestock extension services in rural areas.

KeywordsArtificial IntelligenceLivestockCommunicationFarmersDigital ExtensionSirsa

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