Back to the radar Artificial Intelligence

El próximo organigrama empresarial tendrá agentes de Inteligencia Artificial

En esta tribuna, Fabiola Pérez, CEO en MIOTI Tech & Business School, analiza cómo la integración de agentes de IA rediseña el organigrama empresarial.

En esta tribuna, Fabiola Pérez, CEO en MIOTI Tech & Business School, analiza cómo la integración de agentes de IA rediseña el organigrama empresarial.

En contexto

  • Tema: Inteligencia Artificial — IA aplicada al negocio: casos, límites, costos y gobierno.
  • Fuente: Silicon España
  • Publicado: 14/10/2026

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Why it matters

Adopting AI in a company is less like buying software and more like hiring someone. You have to teach it the context, review its work at the start, and define what it can sign off alone and what it cannot. The stories worth reading are the ones showing somebody solving that part, not the announcement part.

The first thing I look at is not model capability but the data feeding it. Almost every project I have seen fail did not fail on the algorithm. It failed because the data lived in three systems with three different definitions and nobody wanted to be the one to fix that.

What usually goes wrong

The mistake I have seen repeat most is measuring nothing before starting. It gets deployed, everybody feels things improved, and when somebody asks by how much, there is no answer. Without a baseline there is no way to defend next year's budget, and that is where good projects die.

What to watch

  • Where the data ends up and under what contract, especially when customer information is involved.
  • Whether the organisation can change provider without rebuilding everything, which is the proof it did not get locked in.
  • Which concrete process is touched and how it is measured before and after; with no baseline there is no result, only opinion.

How I read this entry

My practical advice is to fix on day one what happens when the model is wrong: who reviews, how often, and at what point it gets switched off. It sounds defensive, but it is exactly what lets you be aggressive later, because the risk stopped being an unknown.

The original story is published in another language; the excerpt is quoted as the publisher delivers it and the commentary is written in English.
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