Digitalisation in agriculture is often discussed as a global transition, as if farms everywhere are moving along the same technological paths. My own experience suggests something more nuanced. Having grown up in the Dominican Republic and now living and studying in Switzerland, I have come to realise that agricultural digitalisation is not simply about adopting new tools. It is about the systems that make those tools usable in the first place.

In the Dominican Republic, agriculture is part of everyday life, but it is rarely mediated through digital technology. This is not a matter of preference. In many rural areas, access to reliable electricity is inconsistent, power outages are common, and internet connectivity is limited or unavailable altogether. Wi-Fi is far from guaranteed, and mobile data can be slow or expensive. Under these conditions, digital tools that depend on constant connectivity, cloud platforms, or real-time data streams are simply not practical. Farming decisions therefore rely on observation, local knowledge, and experience passed through families and communities.

Living in Switzerland has exposed me to a very different agricultural reality. Here, digitalisation feels almost seamless because the basics are already in place. Electricity is stable, internet access is reliable, and rural connectivity is an expectation rather than an exception. Precision farming tools, data-driven decision-making, and traceability systems fit naturally into an environment defined by strong regulation. Predictive analytics can be trusted because the underlying system is consistent enough for predictions to hold.

A clear example of this contrast appears in the beef industry. In Switzerland, cattle farming is increasingly supported by digital systems that track animal health, movement, and traceability. RFID ear tags, digital herd-management platforms, and automated feeding systems allow farmers to monitor weight gain, detect illness early, and meet strict animal-welfare and traceability standards. These systems rely on continuous electricity, stable connectivity, and integration with national databases. Digitalisation here reduces uncertainty and supports efficiency.

In the Dominican Republic, cattle farming operates very differently, especially in small rural farms. Many farms lack reliable electricity and have no permanent internet connection. Herd tracking is done visually or through paper records, and decisions about feeding, breeding, and veterinary care are based on experience rather than continuous data. When power or connectivity drops, which happens regularly, digital monitoring systems would simply stop working. In this context, the priority is keeping animals healthy and safe under variable conditions, not optimising performance through real-time analytics.

This contrast has shaped how I think about digital transformation in food systems. Predictive analytics and digital platforms assume stability: historical data, continuous measurement, and reliable infrastructure. In environments where uncertainty is constant, digital tools must support flexibility. Comparing Switzerland and the Dominican Republic has also changed how I think about progress in agricultural digitalisation. In highly developed systems, progress often means higher efficiency and tighter optimisation. In lower-income contexts, progress may mean securing reliable electricity, improving connectivity, and strengthening resilience. Both goals are valid, but they require fundamentally different digital approaches.

Ultimately, agricultural digitalisation cannot be designed as a one-size-fits-all solution. Technology alone does not create transformation; systems do. Meaningful digital food systems must be grounded in local realities, support resilience as much as efficiency, and expand opportunity rather than risk.

Vasquez Ana Sofia

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