Adoption and Compliance of AI-Enabled Pest Advisories: Evidence from the National Pest Surveillance System (NPSS) in Odisha, India

Artificial intelligence (AI)–enabled pest surveillance can bridge gaps between timely diagnosis and on-farm action in smallholder systems. This study assessed farmer exposure to and uptake of advisories from India’s newly launched NPSS in Odisha. An exploratory, cross-sectional inquiry was conducted during 2024–25 across 30 districts; one block and two villages per district were purposively selected based on NPSS use. Data were gathered from 1,422 participants through focus group discussions and personal interviews, and analysed. Paddy dominated the sample’s cropping pattern (66.17% of respondents), followed by brinjal (9.21%). Overall, 79.16 per cent were receiving NPSS advisories; the platform issued 851 advisories during the study, with 418 acted upon (49.11% adherence). Adherence declined as pest severity increased, especially for brown planthopper (BPH) and yellow stem borer (YSB) in paddy from 47.73 per cent (low severity) to 32.47 per cent (high severity), and YSB showed a similar drop (about 45.95% to 10%). Qualitative insights indicate lower uptake when recommendations involve costlier or more complex chemical controls, suggesting a need for clearer messaging, phased options, and enhanced last-mile support. The findings highlight substantial reach but moderate compliance, underscoring opportunities to tailor NPSS advisories to farmers’ resource realities and to strengthen capacity-building for higher-severity scenarios.