Introduction: Viticulture is undergoing rapid technological change, from harvest mechanization to data-driven precision practices. In DOCa Rioja (Spain), sectoral innovation increasingly incorporates digital tools and artificial intelligence (AI) initiatives (e.g., the DATADOC project promoted by the regulatory council). While these innovations promise efficiency gains, they may also reshape rural labor markets and reinforce inequalities among producers and workers. This study examines how technologisation is transforming labor demand and workforce profiles in DOCa Rioja.
Methods: We conducted an exploratory mixed-methods case study. Quantitatively, we synthesized secondary evidence on agrarian employment dynamics and mechanization, including an official series of agricultural Social Security affiliations in La Rioja (Jan 2009–Jul 2025) and sectoral indicators related to machinery adoption. We also compared indicative harvesting costs (manual vs. mechanical) using cost estimates reported for the region. Qualitatively, we conducted three semi-structured interviews with local stakeholders (a small vineyard owner, a seasonal worker, and an enology student) to capture perceptions of adoption drivers, constraints, and social impacts. A documentary analysis of institutional materials describing DATADOC and AI-enabled precision tools was used to contextualize the regional innovation agenda.
Results: Findings indicate labor reorganization consistent with "creative destruction". Mechanical harvesting reduces operational costs (about EUR 260/ha vs. about EUR 480/ha for manual harvesting; approximately a 40% difference) and helps address seasonal labor scarcity, but it also displaces low-skilled manual tasks. At the same time, new profiles emerge (e.g., specialized machinery operators, agricultural remote-sensing technicians, and vitivinicultural data analysts), with unequal access shaped by age, education, and training opportunities. Adoption capacity is uneven: better-capitalized actors invest more easily, while smaller operators rely on external service providers.
Conclusions: Technological innovation in DOCa Rioja is not socially neutral. To avoid widening rural inequalities, innovation strategies should be coupled with workforce transition policies, including targeted training and inclusive access to precision-agriculture tools.
