<img height="1" width="1" src="https://www.facebook.com/tr?id=236649609280760&amp;ev=PageView &amp;noscript=1">
banner-new-one

Blog Universidad Panamericana

Ubi spiritus libertas

close

Categoría

Suscríbete

Popular Posts

Los 14 principios de la administración
¿Qué es la teoría científica de la administración?
8 de los pedagogos más importantes de la historia
Las 13 empresas mexicanas con mayor impacto global
30 frases de política que como joven sí o sí te inspirarán
Escrito por Dr. Paolo Morganti
en septiembre 11, 2025

Technologies like artificial intelligence are spreading fast across industries and every-day’s life. These tools promise great productivity gains, but their benefits are not equally accessible to everyone. Some individuals learn quickly and have success, while others struggle to adapt. This uneven adoption of technology is not just a question of personal effort. It has deep consequences for how the economy functions and how income is distributed. My research asks a simple but fundamental question: what happens to inequality when technology favors some people more than others?

 

The Knowledge Economy

To explore this question, I build on a class of theoretical economic models known as the “knowledge economy.” In this view, the main input to production is not machines or capital, but the knowledge that people bring. Firms are organized hierarchically: workers face problems of varying difficulty, and if they cannot solve them, they pass them up to more skilled managers.

Technology plays a central role in this setting. Better technology, like digital platforms or AI assistants, reduces the cost of completing task, or passing incomplete ones to the higher floors. This sounds like unambiguously good news. But the model shows that it is not so simple. The allocation of human resources depends on wages and profits balancing out across skill levels. For this balance to exist, income profiles must be “smooth” enough. If technology breaks that smoothness, the economy may fail to match workers and firms efficiently.

A contribution of my work is to provide a precise description of when this balance holds and when it collapses. I show that even if nobody loses their job directly to a machine, technological change can still push certain groups, especially mid-range workers, out of employment.

 

AI hand pointing to economics graph

 

How Inequality Evolves

The results of the model reveal a surprising pattern. The effects of technology on inequality are non-monotonic, meaning they do not move in a straight line.

  1. Early stage: When technology first improves, highly skilled workers benefit the most. They can use the new tools more effectively, and their wages rise faster than others. Inequality increases.
  2. Middle stage: As the technology spreads further, less skilled workers also gain. They benefit from being paired with stronger managers who can now supervise larger teams. Inequality temporarily decreases.
  3. Advanced stage: If technology continues to advance, the middle of the skill distribution becomes problematic. Workers with average ability become too costly compared to those just above or below them. Firms prefer to hire combinations of slightly higher- or lower-skilled individuals. This breaks the smooth allocation of workers and creates a form of structural unemployment.

This sequence shows that technology does not simply replace or complement labor. It reshapes the entire structure of the labor market.

These results have important implications. First, they show that the impact of technology on inequality is not predetermined. Depending on where an economy stands, technological progress can either worsen or improve income distribution. Second, the greatest risk lies not only in automation of routine jobs, but also in the instability that hits middle-skill workers when the economic balance breaks down.

For students and young researchers, the lesson is that economic models can help us think beyond simple slogans like “AI will take our jobs.” The real question is about timing, distribution, and equilibrium. It is often said that technology “creates winners and losers”, but it also changes the very rules that decide who falls into each group.

If societies want to take advantage of the power of digital transformation while avoiding its risks, they need to anticipate these dynamics. Training, lifelong learning, and safety nets become essential. Without them, technological innovation could create not only higher inequality but also deep inefficiencies in how the economy uses its human resources.

In short, technology is a powerful driver of growth, but it can also break the balance that keeps economies sustainable. The challenge for the coming decades is to ensure that innovation raises society as a whole, rather than leaving many stuck in the middle.

 

Dr. Paolo Morganti

         Profesor Investigador/Professor Researcher

Scripta: https://scripta.up.edu.mx/entities/person/pmorganti

Déjanos saber lo que pensaste acerca de este post

Pon tu comentario abajo.

También te puede interesar:

Administración y Finanzas Doctorado en Ciencias Empresariales Doctorado en Administración

10 revistas internacionales especializadas en finanzas

A pesar del brote en popularidad de los medios virtuales y el dominio de las publicaciones populares, las revistas acadé...

Doctorado en Ciencias Empresariales Doctorado en Administración

El estudio de caso como método de investigación administrativa

El estudio de caso es un método de investigación empírica que examina un fenómeno dentro de su contexto real cotidiano y...

Doctorado en Ciencias Empresariales Doctorado en Administración

Las competencias socioemocionales del líder empresarial

Las competencias socioemocionales son el conjunto de rasgos cognitivos y afectivos que, en el caso de un líder organizac...