This paper tries to capture the evolution of Digital Agriculture based on the foundations of precision agriculture. The review of literature around the development of precision agriculture reveals that the data captured in the precision agriculture processes, if effectively used, can support extensive agronomic decision making. With the advent of artificial intelligence and machine learning (AI/ML), predictive and prescriptive analysis of even huge amounts of data is now possible. Digital Agriculture seeks to combine the power of AI/ML and data from precision agriculture to deliver decision support systems to farmers and in other aspects of the agricultural value chain. The prerequisites for Digital Agriculture to realise its full potential are business models that demonstrate clear economic benefits for the farmers and user-friendly design.