Data is indispensable for digital transformation of agriculture with the development of innovative information and communication technology (ICT). In order to devise and prioritize strategies for enhancing data competitiveness in the agricultural sector, we employed an Analytic Hierarchy Process (AHP) analysis. Drawing from existing research on data competitiveness indicators, we developed a three-tier decision-making structure reflecting unique characteristics of the agricultural sector such as farmers’awareness of the data industry or awareness of agriculture among data workers. AHP survey was administered to experts from both agricultural and non-agricultural sectors with a high understanding of data. The overall composite importance, derived from the respondents, was rated in the following order: ‘Employment Support’, ‘Data Standardization’, ‘R&D Support’, ‘Start-up Ecosystem Support’, ‘Relaxation of Regulations’, ‘Legislation’, and ‘Data Analytics and Utilization Technology’. In the case of experts in the agricultural sector, ‘Employment Support’ was ranked as the top priorities, and ‘Legislation’, ‘Undergrad and Grad Education’, and ‘In-house Training’ were also regarded as highly important. On the other hand, experts in the non-agricultural sector perceived ‘Data Standardization’ and ‘Relaxation of Regulations’ as the top two priorities, and ‘Data Center’ and ‘Open Public Data’ were also highly rated.