La inteligencia artificial se ha convertido en la fuerza dominante en los mercados bursátiles. Aunque todavía es pronto para medir el alcance real de sus aplicaciones —y mucho más para anticipar la trayectoria futura de la tecnología— los mercados son máquinas anticipatorias, y ya han votado a favor de su capacidad para impulsar los beneficios. Pero más allá de esta lectura inmediata surge una cuestión más profunda: cómo la IA transformará las grandes variables macroeconómicas, en particular los tipos de interés, el ancla que fija la valoración de todos los activos.
Al cambiar la forma en que las economías invierten, producen y ahorran, la IA puede redefinir el tipo de interés natural, el tipo real R* compatible con pleno empleo e inflación estable. Durante más de una década, este tipo natural ha permanecido deprimido por factores estructurales: envejecimiento demográfico, exceso de ahorro, eficiencia tecnológica y un fuerte apetito global por activos seguros. La IA amenaza con alterar ese equilibrio.
El primer impacto surge del mundo físico. Desplegar IA requiere chips avanzados, centros de datos, refrigeración intensiva y, sobre todo, electricidad. La Agencia Internacional de la Energía estima que el consumo energético de los centros de datos podría casi duplicarse para 2030. La inversión vinculada a la IA podría superar el 2% del PIB mundial. Este “superciclo” de infraestructuras incrementa la demanda de inversión y, con ella, el tipo natural de equilibrio. Es una reedición digital de los grandes procesos de industrialización del pasado, aunque esta vez las materias primas son energía y capacidad de cómputo en lugar de acero y mano de obra.
El segundo canal es la productividad. La IA promete automatizar tareas cognitivas, reducir costes y multiplicar la producción humana. Si esa promesa se materializa, un mayor crecimiento tendencial sostendría un R* más alto. Pero la adopción no es inmediata. Como en todas las tecnologías de propósito general, los primeros años suelen combinar inversión galopante y ganancias de eficiencia modestas. Además, su impacto sobre el empleo es ambiguo: cuando complementa a los trabajadores cualificados, impulsa la renta y el ahorro; cuando sustituye tareas rutinarias, presiona salarios y aumenta la desigualdad. El efecto neto sobre el tipo natural dependerá de cuál de estas fuerzas domine.
La inflación probablemente evolucionará en dos fases. En la fase inicial, el despliegue de infraestructuras choca con cuellos de botella en energía, equipamiento y mano de obra especializada, generando inflación de costes. Más adelante, a medida que la automatización se generalice, prevalecerá la desinflación. Podríamos entrar así en un mundo de tipos reales más altos y precios más estables, similar al equilibrio de los “Goldilocks” de finales de los noventa. Los tipos nominales serían más altos que en la última década, pero seguirían bien anclados por expectativas de inflación contenida.
Más allá de este horizonte aparece una cuestión mayor: ¿qué ocurre si la IA evoluciona hacia una Inteligencia Artificial General (AGI), capaz de aprender y mejorarse a sí misma? En ese escenario, el comportamiento del R* podría fracturarse. Si la AGI provoca hipercrecimiento, mayor demanda energética y profunda acumulación de capital, los tipos reales podrían dispararse. Pero si, por el contrario, convierte el trabajo y el capital digital en bienes infinitamente replicables, los costes marginales caerían y la necesidad de inversión tradicional se reduciría. En ese mundo, los tipos reales seguros podrían hundirse aún más, pese al avance tecnológico.
Esto nos llevaría a un equilibrio dual: un RS* “seguro” bajo, alimentado por el exceso de ahorro, y un RP* “productivo” alto, ligado a activos físicos escasos —suelo, capacidad de cómputo, materiales críticos— que seguirán siendo limitados incluso en un contexto de inteligencia abundante. El arbitraje que normalmente unifica los retornos dejaría de funcionar: los bancos centrales operarían sobre un tipo mientras los mercados responderían a otro.
Esta divergencia ya empieza a percibirse: rentabilidades extraordinarias de las acciones líderes en tecnología frente al resto, y a unos tipos de interés aún moderados. La AGI convertiría esta brecha en algo estructural. Los bancos centrales, que manejan la política monetaria por medio del tipo nominal seguro, verían cómo sus herramientas dejan de influir en los sectores que impulsan el crecimiento real. La política fiscal, por su parte, podría verse obligada a emitir más deuda y a gestionar las consecuencias sociales de la automatización. Incluso la Renta Básica Universal podría dejar de ser un experimento teórico.
Para los inversores, las implicaciones son asimétricas. Un mundo de R* más alto y precios estables favorece a las acciones de las compañías que se beneficien de la transformación y a ciertos activos reales vinculados a cuellos de botella físicos. Los bonos recuperarían su papel defensivo. Pero si la AGI genera abundancia digital y desinflación, los retornos podrían concentrarse exclusivamente en los activos ligados a escaseces materiales. La construcción de carteras tendrá que navegar ambas realidades: la liquidez fijada por un R* seguro bajo y el crecimiento fijado por un R* productivo alto.
Todo esto puede parecer especulativo —y, de hecho, aún no está en el radar de la mayoría de los inversores ni de las discusiones de política monetaria—. Hasta ahora, surfear la ola de la IA ha sido sencillo. Pero conforme la tecnología madure y su adopción se generalice, el panorama será mucho más complejo. La historia puede orientarnos, pero solo hasta cierto punto. Hemos vivido grandes booms de inversión, pero nunca uno con un potencial transformador tan profundo.
Tribuna de opinión firmada por Fernando de Frutos, director de inversiones en Boreal Capital Management.
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