The ubiquity, portability and mobility of digital technologies are transforming agriculture. Although this is one of the slowest sectors to adopt digital technologies, the transformation towards the numerical treatment of data is universally identified as the third great revolution in agriculture, preceded in the last hundred years by mechanization and the introduction of biotechnology. The business strategy and even the organizational structure will change over time as more digital data will be available through the dissemination of sensors capable of detecting soil and crop condition. In general, the joint proliferation of widespread sensors and distributed computing has already triggered the development of new numerical technologies used to transform assimilated data into usable knowledge. Algorithms and software for machine learning and artificial intelligence, adequately specialized for monitoring and agricultural production, will offer users, including small farms, answers and decision support to increase crop yield, improve profitability and enhance sustainability in a competitive market that estimates the world population at 9 billion by 2050. To feed this dramatically increasing population, the agricultural industry will need to produce 70% more food using only 5% more land. This, coupled with increasing environmental pressures and regulatory constraints, represents a challenge of enormous proportions. It is now widely recognized that digital agriculture will undoubtedly be necessary to meet these needs.