DesarrolloInnovaciónTecnología

Siete consejos clave para construir una empresa AI future-ready.

  • MIOTI Tech & Business School presenta una guía para construir empresas “AI future-ready”, con siete principios para integrar la inteligencia artificial en la gestión diaria de forma práctica y sostenible.
  • En la actualidad, apenas el 7% de las empresas consigue integrar la IA en su estrategia global y convertirse en una organización AI future–ready, según el MIT.
  • Fabiola Pérez, CEO de MIOTI, subraya que “la IA no puede escalar sin una estrategia que combine datos bien gestionados, equipos formados y una dirección con visión de futuro”.

Madrid, 20 de octubre de 2025.- La mayoría de las empresas hablan de innovación, pero pocas consiguen integrarla en su día a día. Con esa mirada crítica y constructiva, MIOTI Tech&Business School, la escuela de tecnología aplicada a los negocios líder en Inteligencia Artificial y Data Science, presenta una guía que busca poner orden en el debate sobre cómo incorporar la inteligencia artificial a la gestión empresarial.

Basada en el estudio elaborado por la propia escuela,» El nuevo talento a explorar: los agentes de IA» , la iniciativa analiza por qué, pese a reconocer su valor, muchas compañías avanzan todavía con cautela. La guía propone un recorrido realista para que la innovación deje de ser un propósito y se convierta en una práctica capaz de transformar la toma de decisiones en las organizaciones.

Los cuatro niveles de madurez de las empresas ante la IA

Según un estudio del MIT, las organizaciones se distribuyen hoy en cuatro niveles de madurez que reflejan su grado de avance en la incorporación de la IA Generativa:

  • Experiment and prepare (fase exploratoria): el 28% de las compañías se encuentra en esta etapa inicial, centrada en la formación, la definición de políticas de uso y el acceso ordenado a los datos.
  • Build pilots and capabilities (fase de pruebas): en este segundo nivel, que alcanza al 34% de las organizaciones, las empresas comienzan a realizar pilotos, consolidan capacidades internas y simplifican procesos mediante el intercambio de datos y el uso de APIs.
  • Develop AI ways of working (fase de incorporación): un 31% de las compañías ha empezado ya a integrar la IA en su operativa diaria, automatizando tareas, optimizando flujos y construyendo arquitecturas reutilizables con agentes inteligentes.
  • Become AI future-ready (fase de integración): solo un 7% ha logrado dar el paso definitivo: integrar la IA en su estrategia global, creando servicios aumentados y combinando modelos generativos, agentes autónomos y sistemas robóticos.

En este sentido, el salto diferencial está en institucionalizar la IA como una forma de trabajar, no como una colección de experimentos.

Cómo construir una organización AI future–ready

Durante años, la inteligencia artificial fue terreno exclusivo de técnicos y grandes corporaciones. Hoy comienza a ocupar, de forma más democrática, el corazón de cualquier organización. Pero no puede asentarse sin objetivos alineados con el propósito de la compañía, disciplina en el uso de los datos y una mirada que combine el corto y el largo plazo.

Con esta premisa, MIOTI Tech & Business School ha reunido en esta guía siete principios sencillos, y al mismo tiempo esenciales, para pasar de las palabras a los hechos: integrar la inteligencia artificial en la gestión diaria, obtener resultados tangibles y preparar a los equipos para un uso natural y sostenido de estas herramientas.

  • Tratar la inteligencia artificial como parte de la estrategia. No es un experimento, sino una herramienta que exige propósito, método y una visión sostenida en el tiempo.
  • Empezar por lo concreto. Los avances reales no ocurren en el laboratorio, sino en los procesos cotidianos. Probar en tareas específicas permite aprender y ajustar sobre la marcha.
  • Elegir herramientas útiles. Aplicaciones como Copilot, Claude, ChatGPT o Gemini pueden incorporarse a funciones concretas y ofrecer resultados visibles sin grandes despliegues técnicos.
  • Detectar el trabajo que puede mejorarse. Identificar tareas repetitivas o ineficientes ayuda a liberar tiempo y concentrar el talento donde más aporta.
  • Conectar áreas que antes trabajaban separadas. La colaboración entre equipos de datos, negocio y tecnología es la base para que la innovación tenga recorrido.
  • Formar personas que impulsen el cambio. No se trata solo de aprender a usar nuevas herramientas, sino de generar referentes internos que integren su uso en la rutina diaria.
  • Medir los resultados con criterio. Analizar el tiempo ganado, la calidad de las decisiones y la implicación de los equipos permite comprobar si el cambio está funcionando.

Fabiola Pérez, CEO de MIOTI Tech & Business School, señala que industrializar la inteligencia artificial exige contar con datos accesibles y bien gestionados, formar a los equipos en seguridad y gobierno de la IA, auditar su uso para optimizar costes, mantener expectativas realistas para evitar frustraciones internas y, sobre todo, impulsar una visión estratégica desde la dirección que guíe la transformación real de productos y servicios.

“La Inteligencia Artificial no puede escalar si no existe una estrategia que combine datos bien gestionados, equipos formados y una dirección con visión de futuro”, subraya Pérez.

Sin embargo, su impacto real está lejos de ser ilimitado. Los casi 60 expertos que han participado en el estudio advierten que la IA no debe asumir decisiones críticas sin supervisión humana, ni sustituir la empatía en contextos sensibles, ni reemplazar la intención creativa o el método científico. La idea inicial de que la IA sirve para todo se ha ido disolviendo a medida que la gobernanza, la ética y la evaluación sistemática del impacto ganan terreno.

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