This chapter critically examines the ethical, legal, and socio-economic (ELSE) challenges and opportunities associated with data and AI in precision agriculture. By conducting an extensive literature review spanning publications from 2016 to 2023, the study systematically analyzes key arguments and trends, focusing on data governance issues. The review includes a meticulous analysis of over 505 distinct sources, revealing a significant shift in thematic focus towards challenges such as data ownership, security, privacy, and labor market disruptions. The findings underscore the predominance of ethical challenges, highlighting critical issues like discrimination, bias, privacy breaches, and the need for robust legal frameworks. Building on the literature review, the chapter addresses the complexities of agri-data governance, providing strategic recommendations for improving data management in the sector. The analysis emphasizes the importance of establishing a centralized European Ag-Data System to consolidate diverse datasets, enforce interoperability standards, and ensure transparent data governance. This approach aims to balance market dynamics, enhance data accessibility, and foster trust among farmers and stakeholders while ensuring adherence to the EU values in practice. Further, the chapter evaluates the European Commission’s Ethics Guidelines for Trustworthy AI using the ALTAI framework through three case studies in Spain, Finland, and Serbia/Lithuania. The assessment highlights improvements in transparency, privacy, and data governance, yet identifies ongoing challenges in technical robustness and accountability. The chapter advocates for continuous ethical evaluations and the use of tools like model cards and datasheets to enhance transparency and accountability. The findings underscore the necessity for robust data governance frameworks and ethical evaluations to ensure the responsible deployment of AI in agriculture, balancing innovation with the protection of stakeholders’ rights and interests.