We train companies in Artificial Intelligence

It's a natural reaction. That's why our first session is specifically designed to manage that fear: we explain what AI does better, what humans do better, and how the team becomes more valuable by exercising judgment over AI, not competing against it.

What generates real anxiety is not AI — it's the uncertainty of seeing everyone talk about it without knowing how it applies to your role. Fear is not reduced by protecting the team from AI, but by giving them control over it. It's the same pattern we experienced with Excel or the internet: new technologies create new skills, they do not eliminate people.

Lo que ofrecemos siempre: una sesión de 30 minutos para que tú valides el enfoque de nuestra primera sesión antes de presentárselo al equipo. Si el tono no encaja con vuestra cultura, no avanzamos.

The rule we teach in the first session is simple: AI does not decide in critical processes — it assists and proposes; the person validates and signs off. What AI accelerates is the mechanical part: drafts, searches, summaries, first versions of reports.

The decision and validation part remains with the team, with judgment that is now faster because it doesn't start from a blank page. The risk of error does not increase — it decreases, because the team dedicates its attention to reviewing and improving instead of producing from scratch.

The cost depends on the size of the team and the depth of the program. To help you justify it, we prepare a one-page financial model with three variables: gross investment, applicable FUNDAE bonus (if you are in Spain, that credit is already paid via contributions — if you don't use it before December 31, it is lost), and real net cost with payback in months.

The reference calculation: a team of 5 people recovering 8 hours a week at a cost/hour of 25€ generates a return of 1,000€/week. Estimated payback: 2 months. McKinsey reports an average ROI of 35% in mid-sized companies that train their teams in AI.

If the initial amount is difficult to defend all at once, we can also divide the investment into phases: we start with a pilot area and scale when the results are on the table.

We measure four specific indicators you can take to your CEO or CFO: hours recovered per employee and week, real adoption rate (daily use of tools, not session attendance), number of documented use cases per area, and AI maturity level of the team before and after.

We deliver it in a one-page executive summary at the close of the training, with recommendations for next steps. It is not a pedagogical report — it's a document you can take directly to a management meeting.

Payback is calculated with three variables: net post-FUNDAE cost, hours recovered per employee and week (the conservative range is 2 to 5 hours according to Microsoft data on Copilot), and the loaded cost/hour of the trained team.

In companies with a profile similar to yours, the typical payback is between 2 and 6 months from the end of the training. Microsoft estimates that AI generates an additional workweek per employee per year with consistent adoption. We don't come to a meeting with generic ranges: we arrive with the calculation customized to your case.

Para calcular tu ROI: compártenos tamaño de plantilla, coste/hora medio y comunidad autónoma — y en 48 horas tienes el modelo financiero con escenarios conservador, base y optimista.

If you need to take a proposal to management, we make it simple. Give us the staff size and autonomous community, and in 48 hours we prepare the document with measurable ROI, net post-FUNDAE cost, and use cases for your sector — ready to present.

If you prefer, we directly schedule an executive meeting with you and your CEO or CFO where we present the competitive potential of AI in your sector, the return model, and the bonus options. Without technical jargon, with numbers on the table.