There is a paradigm shift due to digital technology disruption in agricultural value chain. In the current context, digital agriculture is indispensable for sustainable agriculture, farmers’ livelihood and inclusive growth. Application of AI, Machine Learning, Deep Learning, IoT enabled sensors, drones and cobots are some key technologies which have vital roles in modern practices of agriculture. However, Adoption of digital agriculture in India is at a nascent stage. It is necessary to address multiple challenges to adoption of digital technology to achieve sustainable developments goals in India. The aim of the study is to decipher the challenges of digital technology adoption in India and to apply Interpretive Structural Modelling which ranks and finds out the inter dependencies among the key challenges. ISM modelling as a qualitative modelling tool develops a hierarchical structure among the key challenges. The research work limits the study in India. The study is first of its kind which applies ISM as a qualitative modelling tool to challenges to digital agriculture in Indian context.