DIGITAL LIFE

AI could create new jobs while leaving millions of workers unable to access them

Much of the debate surrounding artificial intelligence centers on a seemingly simple question: how many jobs will disappear, and how many will be created? But there is another, far more complex possibility. What if new jobs do emerge, but are located in the wrong places for the people who need them? New projections for the U.S. labor market show that technology, an aging population, and workforce skills may move in different directions, creating a sort of labor puzzle.

The problem begins even before considering what artificial intelligence will be capable of doing.

Based on current immigration levels, projections from the Indeed Hiring Lab indicate that the U.S. workforce could shrink by about 1.2 million people by 2040.

However, the impact could be even more pronounced before then.

By 2032, the reduction could reach approximately 5.9 million workers—or 3.7% of the workforce—driven primarily by an aging population and retirements.

It is tempting to imagine that artificial intelligence would automatically fill this void.

After all, if fewer people are available to work and machines can take over an increasing number of tasks, the two phenomena might simply offset each other.

The problem is that they are not necessarily occurring in the same places.

Sectors most exposed to the impact of AI include information, financial activities, and professional and business services.

Meanwhile, the greatest need for workers is expected to arise in very different areas.

And this mismatch completely changes the conversation.

AI is advancing in areas where the labor shortage may not be most acute... Construction, healthcare, and public administration are among the sectors projected to have a significant need for labor.

These are precisely the areas where artificial intelligence offers less potential for direct replacement.

An AI can analyze medical records, for example, but that does not mean it can take over all the physical and human tasks performed by a nurse. Similarly, generative systems can assist architects and engineers, but they do not automatically replace the workers needed to build a house.

A curious scenario emerges.

While certain administrative and professional roles may see an increasing number of tasks automated, other areas continue to seek workers.

In theory, simply shifting workers from one sector to another should suffice.

In practice, changing professions is far more complex than moving a piece across a game board.

The key question becomes: how much of a person's existing skillset can be leveraged in a different occupation?

Some skills are transferable across professions, while others require years of preparation; certain competencies appear across various sectors.

Communication and business management are prime examples.

According to data cited by the Indeed Hiring Lab, basic skills related to business operations appear in over 70% of job postings in the United States.

This means workers can carry over part of their experience when switching careers.

The expansion of AI itself demonstrates that these boundaries are becoming more fluid.

In the United States, 63% of AI-related job openings fall outside traditional technology occupations.

Across the six countries analyzed, five show at least half of these openings outside the traditional tech core.

However, there is a significant obstacle.

Not every competency can simply be transferred.

Working in healthcare, for instance, often requires specific education, professional certifications, and experience that cannot be gained merely by using a chatbot.

At the same time, companies are demanding more from candidates.

Job postings now require two more skills than they did before the pandemic; the average job listing currently calls for two additional competencies compared to pre-pandemic levels.

There is also a growing number of non-tech sector jobs requiring at least one technical skill.

This creates two vastly different realities.

For workers with access to training who can quickly update their skills, this transformation may open up new possibilities.

For those lacking the time, money, or access to training, this same shift may raise the barrier to entry even higher. That is where one of the most interesting paradoxes of artificial intelligence arises.

The very technology that contributes to changing professional requirements could also help workers navigate this transition.

AI systems can analyze existing skills, identify similarities with other professions, and indicate the knowledge required to switch fields.

They can also serve as learning tools during career transitions.

But this is far from solving the entire problem.

Even with AI’s help, the numbers still don’t add up. According to the projections presented, even in a scenario where artificial intelligence complements workers, boosts productivity, and helps generate new opportunities, these effects would offset only about 11% of the workforce losses associated with the demographic shifts considered in the study.

This figure reveals why focusing solely on how many jobs AI might destroy may be insufficient.

There may be job openings.

There may be workers seeking opportunities.

And yet, the two sides might simply fail to connect.

An administrative professional does not instantly transform into a nurse. A marketing worker cannot step into a specialized construction role overnight. And someone with decades of experience may struggle to compete for positions that now require digital skills that did not exist when they began their career.

Therefore, the future of employment may depend as much on education, training, professional mobility, and the recognition of transferable skills as it does on artificial intelligence itself.

The paradox is striking.

For years, the question was whether machines would leave people jobless.

The scenario now emerging is different—and perhaps more difficult to resolve: we could end up with an economy full of job openings and, at the same time, full of workers who lack the necessary pathway to fill them.

AI can create new jobs while leaving millions behind because the new roles require advanced technical skills that current workers do not have and cannot easily learn in time.This problem is called the skills mismatch. It means the type of work being created does not match the skills of the people who lose their jobs.

What new jobs does AI create?

-AI trainers: People who teach AI models by labeling data or writing prompts

-Data analysts: Workers who clean and study large sets of information

-Ethics and policy experts: Professionals who make sure AI is used safely and legally

-Maintenance engineers: Technicians who repair and update AI hardware and servers

Why millions cannot access them:

-The skills gap: New jobs need high-level computer science, math, or engineering knowledge. Factory workers, cashiers, or office clerks cannot switch to these roles overnight

-High cost of training: Going back to school or taking specialized courses costs a lot of money and time. Many workers live paycheck to paycheck and cannot afford to stop working to study

-Fast speed of change: AI technology improves much faster than schools and training programs can update their classes

-Location and access: Most high-paying tech jobs are in big cities or wealthy countries. Workers in rural areas or developing regions often lack good internet and local training centers

The displacement problem:

-Old jobs disappear fast: AI can replace routine tasks in customer service, writing, and coding very quickly

-New jobs grow slowly: Companies take time to build new departments and hire new teams

-The gap widens: People who lose routine jobs face long periods of unemployment before they can find a way back into the workforce

mundophone