The article aims to contribute to the discussion and research on economic, ethical and legal aspects of digital transformation in the agri-food sector. The previous technological revolution (the so-called Green Revolution) significantly raised the efficiency indices and productivity in agriculture. At the same time, however, it led to many negative environmental consequences. It also deepened income inequalities in the sector. According to some researchers, the current digital revolution, in fact based on intensive use of knowledge, may reverse the adverse consequences of the previous revolution. On the other hand, there is growing evidence that digital technologies lead to new social divides and to greater inequalities in the world. Many digital products and services are developed with the use of data to which ownership rights remain unclear. At the same time, the ongoing digitalization processes seem to significantly increase the risk of privacy violations. The article discusses the benefits, problems and possible risks associated with the digitalization processes in the agri-food sector. Particular attention is devoted to the ethical aspects of collecting, processing, sharing and using digital data from smart farming systems. It is argued that the potential of the digital revolution in the agri-food sector is not fully realized. The influencing factors are i.a. the lack of laws and regulatory frameworks for the governance of digital data gathered in the agriculture and food sector, the structure of the market of digital products and services favoring large and very large farms, low level of trust between actors in the data value chain and insufficient cooperation between the private and the public sector with regard to using and sharing digital data. Therefore, a broad discussion engaging various stakeholders on the vision of digital transformation in the agrifood sector is necessary. The foundations for the development of the agri-food sector based on data exchange and digital innovation should take into account common values and ethical principles, as well as the need to build mutual trust between the actors in the data value chain.