Integrating AI chatbots for advisory support in black pepper cultivation: a case study on stakeholder acceptance

Purpose Information is crucial in addressing farmers’ context-specific needs. Large Language Models (LLMs) can be used to achieve it. The study is an attempt to analyse the acceptance and effectiveness of AI chatbots in delivering advisory services and tries to address the following research questions: What factors contribute to the effective adoption of AI chatbots among agricultural stakeholders? What are the attributes required for chatbot design to maximize user acceptance?Methodology A telegram chatbot was developed to provide scientific advisory services regarding black pepper cultivation. The quantitative and qualitative evaluation of the chatbot responses was done. Data collected through an online survey was analysed using the Uses and Gratifications (U and G) model and sentiment analysis.Findings Convenience, authenticity of conversation, enjoyment, pass time, privacy concerns and immature technology emerged as the key factors responsible for high acceptance of AI chatbot among the stakeholders involved in black pepper cultivation.Practical Significance Many chatbots have been developed to support agricultural stakeholders, yet user acceptance and sentiment analysis remain underexplored. While most studies focus on chatbot development, empirical evidence is crucial to validate the benefits of AI chatbots in agricultural extension and advisory services for improving their usability and effectiveness.Theoretical Implication This research extends the application of the U and G model in digital extension services. The study provides empirical evidence on the effectiveness of chatbots in agricultural extension as perceived by farmers. The findings can help policymakers formulate hybrid advisory models integrating humans and AI and design contextually relevant extension paradigms for long-term adoption.Originality This pioneering research in India is significant in measuring the perceived effectiveness of chatbots and contributes to the growing field of AI in agriculture.