Mercedes Iborra, lead interview in Savia Rural: rural AI is not about data, it is about interpreting it

Artificial intelligence in rural areas is no longer a concept for the future: it is the central theme of the summer issue of Savia Rural, the magazine of the Red PAC network, which chose Mercedes Iborra, co-founder and Strategy Director of VisualNACert, for its lead interview. This is no passing mention: it is the piece that opens the special, and in it Mercedes explains how AI is applied today to fertilisation, irrigation and pest control, with one idea running through the whole conversation: what matters is not the data, it is how the data is read.

Why Red PAC devotes an entire issue to rural AI

Savia Rural no. 11 does not treat artificial intelligence as a concept for the future, but as a tool already entering the daily life of rural areas: efficiency, sustainability and agrifood quality are the pillars of the issue, alongside other content such as the Enonatur project and a visual feature on young art across the territory. That an institutional magazine devoted to the Common Agricultural Policy should choose AI as its central theme says a great deal about how far the conversation has come: it is no longer a purely technological question, it is a management question.

Data, yes — but interpreted: the difference that shows in the result

The central argument of the interview is easy to state and hard to apply well: any farm can accumulate data — from sensors, from satellites, from field notebooks — but accumulating data is not the same as making better decisions with it. Artificial intelligence delivers real value when it turns that volume of information into a concrete recommendation about when to fertilise, how much to irrigate or when to intervene against a pest. It delivers nothing when it merely adds one more dashboard that nobody gets round to looking at.

Fertilisation, irrigation and pests: the three fronts where it already shows

In the interview, Mercedes Iborra pins down where that interpretation is already being applied with measurable results: fertilisation, matching doses to what the crop needs at each stage instead of applying generic plans; irrigation, cross-referencing soil and climate data to decide when and how much to water; and pest control, anticipating the moment to intervene before the damage is visible to the naked eye. The pattern is the same in all three cases: the technology does not replace the judgement of the agronomist or the grower, it feeds that judgement with better information at the moment it is needed.

An issue that also speaks to generational renewal and depopulation

What sets this issue of Savia Rural apart is that it does not treat AI as a purely productive matter: it frames it within the future of rural areas at large, alongside subjects such as generational renewal or keeping people living on the land. It is a framing that connects directly with VisualNACert's reason for being, and with the reflection Mercedes Iborra developed shortly afterwards on the KM ZERO podcast: this is not only about technology reaching the countryside, it is about helping that countryside keep someone to work it, and about offering real reasons for a young person to choose to stay.

What Enonatur is and why it shares an issue with AI

The Enonatur project, which Savia Rural covers in the same issue alongside the Mercedes Iborra interview, works on conserving native vine varieties and on their relationship with the rural landscape. At first glance it has little to do with artificial intelligence, but it shares the same underlying idea: the value of rural areas lies not only in producing more, it lies in conserving and making better use of what already exists — varieties, knowledge, territory — with the right tools for each case, whether genetic or digital.

The challenge of explaining technology without losing touch

One of the strengths of this interview, judging by Savia Rural's own approach, is that it explains artificial intelligence without unnecessary jargon, something that does not always happen in institutional publications. Mercedes Iborra insists on talking about fertilisation, irrigation and pests — problems anyone in a rural area recognises — before talking about models or algorithms, because the point of the interview is not to explain how the technology works inside, it is to explain which concrete decision it helps you make better.

There is also a generational reading of all this that connects with other pieces in this same editorial calendar: if the agrifood industry wants to attract young professionals, it needs to show that it offers intellectually interesting work, not only physical work. An interview like this one, placing the interpretation of data at the centre of the agricultural conversation, contributes to precisely that: it normalises the idea that working in a rural area can mean analysing irrigation patterns with artificial intelligence, and not only operating machinery.

For VisualNACert, seeing this message reflected in an institutional publication such as Savia Rural confirms something we observe day to day with real clients, on farms and in cooperatives across Spain: resistance to technology in rural areas is rarely resistance to change itself, it is resistance to unnecessary complexity. When a tool is explained in terms of fertilisation, irrigation or pests rather than data architecture, adoption stops being a barrier, and the conversation with the client gets considerably shorter.

What an agronomist or a cooperative manager takes away from this interview

For anyone running a cooperative or advising farms, the practical message of the interview is concrete: before investing in more sensors or more platforms, it is worth asking whether the data already being collected is being interpreted and used at the right moment. Very often the information needed to decide better already exists on the farm; what is missing is the intermediate step that turns it into an applicable recommendation, and that is where artificial intelligence delivers the biggest leap in value.

Sources

• Red PAC — Savia Rural no. 11, summer 2026 — full issue (in Spanish)