La nueva versión de la suite ofimática está disponible para dispositivos con sistema operativo Windows, macOS y Linux.
La nueva versión de la suite ofimática está disponible para dispositivos con sistema operativo Windows, macOS y Linux.
En contexto
- Tema: Inteligencia Artificial — IA aplicada al negocio: casos, límites, costos y gobierno.
- Fuente: Silicon España
- Publicado: 27/08/2026
Seguir leyendo en la fuente original →
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Why it matters
Every week there is an announcement that promises to change everything, and every week most organisations are still fighting the same battle: messy data, processes nobody documented, and expectations running faster than capability. This story reads better with that in the background.
I measure AI maturity with an uncomfortable question: can anyone explain, in one line, what decision the model makes and who answers if it gets it wrong? Where that is clear, the project moves. Where it is not, it stays in permanent pilot and gets cancelled with the excuse that the technology was not ready.
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
- Cost per query at real volume, not pilot volume: the variable that produces the most surprises.
- 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.
How I read this entry
I would use it for a talent conversation rather than a purchasing one. The capability that needs installing is not operating a tool, which changes every six months, but framing the problem well and judging the answer. That one stays in the house.
The original story is published in another language; the excerpt is quoted as the publisher delivers it and the commentary is written in English.
Living through this in your own team?
Open the chat and tell me how you're handling it. I'm interested in comparing notes.
