[CAREER NEWS] “Deskilling” or the silent erosion of skills

“Deskilling” or the silent erosion of skills

AI speeds work, simplifies many tasks, and is already transforming skilled professions. But behind these efficiency gains lies a more discreet phenomenon: “deskilling” which is the gradual weakening of certain skills as intellectual effort is increasingly delegated to tools.

The issue extends far beyond automation. The risk is not only replacing certain tasks but also practising less frequently some essential abilities: analyzing, structuring one’s thinking, deciding, writing, synthesizing, or exercising judgment.

And this phenomenon now affects highly skilled professions: consulting, marketing, finance, law, management, strategy, and more.

Definition

The term “deskilling” refers to the gradual weakening of human skills when an increasing portion of work is automated or delegated to technological tools.

Why is “deskilling” becoming a major issue?

For a long time, this phenomenon mainly affected manual or repetitive tasks. But with the rise of generative artificial intelligence, deskilling now impacts intellectual tasks performed by skilled professionals: analyzing, writing, synthesizing, structuring one’s thinking, or preparing decisions.

Today, an AI tool can produce a strategic synthesis, draft a note, analyze data, or generate recommendations in seconds. These tools significantly enhance productivity and, as a result, the more certain tasks are delegated, the less some skills are exercised.

The risk is therefore not only the automation of work. It is the gradual weakening of essential cognitive abilities:

·         analysis;

·         critical thinking;

·         judgment;

·         the ability to synthesize;

·         strategic reasoning;

·         writing quality.

Deskilling does not necessarily mean that professionals become less useful. It mainly means that they may gradually become more dependent on tools to think, produce, or decide.

“Deskilling” is becoming a central issue in organizations today as AI now automates tasks that played a key role in professional learning. 

For a long time, the early years of a career allowed individuals to develop their expertise through research, writing, analysis, or synthesis. Yet these are precisely the activities that AI automates most easily today. 

Certain negative trends are already emerging within organizations: 

·         increasing difficulty writing without assistance, 

·         the reflex to consult AI before even thinking independently,

·         standardization of analyses and presentations,

·         a decline in vigilance toward errors produced by the tools. 

The risk is therefore less about the immediate disappearance of skilled professions and more about the gradual weakening of the learning mechanisms that helped build expertise. 

The main risks of “deskilling” 

§  A weakening of judgment

AI tools often produce quick, smooth, and convincing responses. But a well-formulated answer is not necessarily a correct one. 

The more a professional delegates their analysis to a tool, the more they may lose their ability to detect inconsistencies, biases, or errors. 

A study conducted by Harvard, MIT, and BCG[1] on consultants using GPT-4 (the AI engine used in some versions of ChatGPT) showed that performance improved when AI was used for appropriate tasks, but errors also increased when users placed excessive trust in it. 

The issue is therefore not the tool itself, but what we gradually stop exercising when we delegate our thinking to it. 

§  The standardization of thinking 

Generative tools operate based on statistical models and existing content. They excel at quickly producing coherent syntheses, but are much less effective at generating truly original, counterintuitive, or disruptive thinking. 

When everyone uses the same tools, the same prompts, and the same synthesis logic, reasoning begins to look alike. 

Yet in consulting, management, or strategy professions, differentiation often relies on the ability to ask the right questions, understand human dynamics, interpret weak signals, and make decisions amid uncertainty.

Deskilling becomes problematic when AI replaces intellectual effort instead of enhancing it. 

§  A weakening of learning 

Deskilling also raises a major question: how can we develop future experts if the tasks that used to enable learning are now automated? 

For a long time, juniors developed their skills by gradually performing analyses, syntheses, or presentations before taking on more strategic responsibilities. If AI now performs part of this work, some learning mechanisms risk gradually disappearing, and consequently, the renewal of skills and accumulated experience within organizations may be weakened. 

The opportunities of deskilling 

Deskilling is often presented solely as a threat. However, it can also have a useful effect: forcing professionals to distinguish the skills that truly create value from those that were mainly about execution. 

When certain tasks become automatable, value shifts towards capabilities that are harder to replace: discernment, judgment, relational intelligence, or the ability to manage uncertainty.

Deskilling can also accelerate certain learning processes when AI is used as a tool for advancement rather than as a substitute for thinking. For example, anyone can use it to challenge their reasoning, compare different approaches, deepen a subject, or identify blind spots in an analysis. 

Habits to prevent deskilling 

§  Think before consulting AI 

Intellectual effort remains essential to structure one’s thinking and develop judgment. Continuing to practice certain skills without assistance—writing, analyzing, synthesizing, or preparing reasoning are abilities that must still be exercised. 

§  Systematically verify 

The more AI produces credible answers, the more human value depends on the ability to detect what is inconsistent, incomplete, or approximate. 

§  Preserve original thinking 

Reading, confronting different viewpoints, and nurturing general knowledge remain essential to avoid the standardization of reasoning. 

§  Develop human skills 

Building trust, persuading, managing tensions, adapting, or making decisions under uncertainty remain skills that cannot be developed through a prompt.

Conclusion 

Deskilling is not inevitable. 

The real issue is not the existence of the tools, but how each person chooses to use them. Delegating certain tasks can be helpful. However, gradually delegating one’s reasoning, judgment, or analytical ability is much riskier. 

The professionals who will gain the most value from AI will likely be neither those who reject it nor those who fully delegate their work to it. 

They will be those able to combine natural intelligence (i.e., human!) and artificial intelligence with discernment.  In other words, those who learn to use AI as a co-pilot rather than on autopilot!😊

Elizabeth TOUCAS – Executive Strengths Coach & Career Manager – IÉSEG Network

For any personalized support in Executive Coaching or for any information requests about the Career Development Services, contact me at: e.toucas@ieseg.fr or +33.6.85.33.01.57.