From Adoption to Impact: A Life-Cycle Monitoring Framework for Scalable and Meaningful Digital Agriculture in India

India's pursuit of Viksit Bharat@2047 has placed digital agriculture at the centre of agricultural policy through initiatives such as the Digital Agriculture Mission, AgriStack, the Soil Health Card scheme, the electronic National Agriculture Market (e-NAM) and a rapidly growing agri-tech start-up ecosystem. Yet the success of digital programmes is still reported largely through enrolment and adoption counts: farmers registered, devices distributed or applications downloaded. Such figures reveal little about whether a technology remains in use, why farmers discontinue it, or whether it delivers measurable benefit on the farm. In a country where most operational holdings are small and marginal, this gap between adoption and outcome is a central implementation risk. This chapter proposes the Agri-Tech Lifecycle Monitor (ALCM), a conceptual and design-oriented framework that follows an agricultural technology from introduction through adoption, usage, continued usage, actual benefit and impact. A parallel recovery pathway, comprising abandonment, reason identification, problem analysis, corrective action and re-tracking, treats discontinuation as diagnostic information rather than as failure. The framework defines stage-wise indicators, including the continuation rate, abandonment rate, recovery rate and a proposed Meaningful Digital Transformation Conversion (MDTC) ratio, which expresses the share of adopters who reach a defined measurable-impact stage. A multilingual farmer interface (Marathi, Hindi and English) and a stakeholder dashboard for extension officers, Krishi Vigyan Kendras, farmer producer organisations, technology providers and policymakers form the operational layer. Using an illustrative smart-irrigation scenario, the chapter shows how lifecycle monitoring exposes attrition and unrealised benefit that adoption statistics conceal. It then derives policy lessons and implementation pathways for embedding lifecycle monitoring in programme design, extension systems and digital public infrastructure. The chapter argues that scalable digital agriculture should be judged not by how many farmers adopt a technology, but by how many continue to use it and gain from it.