The evolving field of disruptive technologies has recently gained significant interest in various
industries, including agriculture. The fourth industrial revolution has reshaped the context of
Agricultural Technology (AgriTech) with applications of Artificial Intelligence (AI) and a strong
focus on data-driven analytical techniques. Motivated by the advances in AgriTech for
agrarian operations, the study presents a state-of-the-art review of the research advances
which are, evolving in a fast pace over the last decades (due to the disruptive potential of the
technological context). Following a systematic literature approach, we develop a
categorisation of the various types of AgriTech, as well as the associated AI-driven techniques
which form the continuously shifting definition of AgriTech. The contribution primarily draws
on the conceptualisation and awareness about AI-driven AgriTech context relevant to the
agricultural operations for smart, efficient, and sustainable farming. The study provides a
single normative reference for the definition, context and future directions of the field for
further research towards the operational context of AgriTech. Our findings indicate that
AgriTech research and the disruptive potential of AI in the agricultural sector are still in infancy
in Operations Research. Through the systematic review, we also intend to inform a wide range
of agricultural stakeholders (farmers, agripreneurs, scholars and practitioners) and to provide
research agenda for a growing field with multiple potentialities for the future of the
agricultural operations.
This is an Open Access Article. It is published by Springer under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/