ntv.de: Youth researcher Mathias Albert, author of the Shell Youth Study, views Gen Z as a “lost generation.” This is because, due to artificial intelligence (AI), even well-educated young people are suddenly facing difficulties in the labor market. How many applicants are affected by this?
OLIVER SCHLENKER: In the US, there is indeed an employment gap in so-called AI-exposed occupations. Since late 2022, employment among 22- to 25-year-olds in these sectors has lagged nearly 20 percent behind that of areas less affected by AI. However, we do not see this trend in Europe, as studies from Scandinavia indicate; we are currently analyzing the situation for Germany. While young professionals here are certainly feeling the impact of the negative labor market trends, AI is just one of many factors—the primary driver is the recession. Another contributing factor is the prevalence of remote work in traditional professions requiring a university degree. This can hinder the mentoring and informal learning of junior staff, potentially leading employers to favor hiring experienced workers instead.
Does generative AI threaten the jobs of entry-level professionals?
Generative AI can make entering the workforce more difficult because it primarily takes over the standardized digital routine tasks through which young employees previously gained experience. Studies in the US already show an employment gap among 22- to 25-year-olds in occupations highly exposed to AI. For Germany and Europe, however, there is no clear evidence of a comparable trend so far; here, the recession, reduced hiring, and the challenges of informal learning while working from home are also weighing on the prospects of those just starting their careers.
Which professions are particularly strongly affected by generative AI?
Software development is at the forefront, but so are roles in customer service and the business-to-business sector—not just within IT, but across knowledge-intensive services and even journalism. Less affected are jobs in the construction sector and those involving a high degree of social interaction, such as in healthcare and caregiving.
What is the reason for the much larger employment gap in the US resulting from AI?
There is no definitive answer to this yet, but one possible reason lies in differences regarding employment protection. In the US, employers can adjust their workforce more easily—for instance, through layoffs. Furthermore, the US study focused on very large firms; since AI is already being deployed more extensively in large companies, this may also account for the significant disparity.
Which specific age group is most affected by the impact of AI?
The results from the US focus on 22- to 25-year-olds, as that is a typical age for university graduates entering the workforce there. In Germany, university studies are often completed at a later age.
How do middle-aged and older workers fare by comparison?
Their employment trends are more stable than those of younger workers. Older employees are far less affected by the recession, as the current economic downturn primarily manifests through reduced hiring, while existing employment relationships remain more stable. Secondly, the rise of AI actually makes their experience more valuable. They can offload routine tasks to AI and effectively verify the results, because they know what the outcome should be.
Why is professional experience becoming more valuable due to AI?
Experienced employees can delegate routine tasks to AI systems and subsequently verify the results from a professional standpoint. Their value lies less in the actual creation of content than in the ability to identify errors, implausible statements, and missing connections. Consequently, AI boosts the productivity of specialists who already understand what constitutes a sound and high-quality outcome. Experience does not become obsolete; instead, it evolves into the capacity for oversight and critical judgment.
Can you confirm a sense of deep uncertainty among young applicants, apprentices, students, and employees? Youth researcher Albert speaks of “apathy, polarization, and a lack of prospects.”
While the Sinus Youth Study conducted by the Barmer health insurance fund revealed that AI causes significant anxiety about the future for one-fifth of young people, it ranks near the bottom when compared to other sources of concern. Wars, for instance, worry three times as many young people. Fears regarding AI must be taken seriously—and they are indeed growing—but I would also highlight the opportunities. To date, the majority of AI usage has been driven by employees themselves rather than by companies. Furthermore, businesses need to remain internationally competitive; without the use of AI, entire industries could eventually be at risk. AI should therefore be introduced selectively where it offers added value. Its consequences are not a matter of fate but depend on how it is implemented.
What lessons can be drawn from the past, when other technological developments turned career prospects upside down?
In the case of robotic automation, we have seen that workplace co-determination can help mitigate negative consequences for employees without compromising productivity—quite the opposite. For instance, when routine assembly-line tasks are eliminated, affected employees—provided they receive the necessary training—can operate the robots that have taken over their original duties. However, this requires not only new skills but also the active involvement of the workforce.
In this way, negative consequences such as job losses are mitigated, though not prevented. From an employee’s perspective, what arguments still favor the introduction of AI?
A coordinated rollout can benefit employees just as much as it does companies. Digitalization can lead to pressure regarding deadlines and performance, causing an increase in sick days among certain groups of employees. If individual staff members introduce AI on their own initiative—for instance, to produce a report within hours rather than weeks that appears perfect at first glance—this may generate more additional pressure within a team than an orderly implementation managed by the employer.
Who stands to gain from the rise of generative AI?
Employees whose work is augmented by AI—and who are capable of reliably evaluating AI-generated outputs—stand to benefit the most. These are likely to be experts possessing a high level of specialized knowledge and experience; for instance, they can become significantly more productive by using AI agents and reviewing the results they produce. Conversely, standardized digital routine tasks—such as certain basic writing, programming, or image-generation jobs—could come under pressure. Yet, as with previous technologies, it is typically specific tasks rather than entire professions that are replaced. Nevertheless, some professions will undergo profound changes, and new ones will emerge.
How can those who “lose out” in this development best handle the situation?
In the future, the key question will increasingly be: what is my “unique selling point” vis-à-vis AI? What skills can I bring to the table that go beyond performing routine cognitive tasks? It certainly helps to demonstrate not only subject-matter expertise but also the ability to work effectively with AI. Professions heavily exposed to AI—such as lawyers, scientists, and journalists—can become far more productive through the right use of the technology. And, of course, complementary skills remain in demand—such as the ability to argue a case persuasively in the courtroom.
How can those just starting their careers gain experience when traditional entry-level jobs are disappearing?
Monitoring AI is becoming increasingly important—not only understanding what AI is doing but also acquiring the expertise to verify its results as quickly as possible. In my view, critical thinking is therefore becoming more important, as is social interaction. As I mentioned, we need to move away from routine cognitive tasks that are easily automated. Of course, the difficulty of this transition varies from person to person. This creates a whole new need for education and training—for employers as well. Companies must structure entry-level roles so that young employees can gain practical experience despite the presence of AI—for instance, through mentoring, regular feedback, and gradually increasing responsibility. A major obstacle is that many employees still lack the necessary digital skills.
How can career starters gain experience in the age of AI?
Companies need to structure entry-level roles in a way that allows young employees to gain practical experience, even as routine tasks become automated. Mentoring, regular feedback, supervised project work, and gradually increasing responsibility are effective approaches for this. Furthermore, those starting their careers should learn to critically evaluate AI outputs, place them in the proper professional context, and use them responsibly. Alongside digital skills, critical thinking, social competence, and professional judgment are becoming increasingly important.
Some school leavers will try to play it safe by opting for “solid vocational training”—such as in the skilled trades—to avoid being replaced by AI. Is such a trend emerging?
There is no sign of a boom in the skilled trades so far, although there is a slight shift towards that sector within the dual vocational training system. However, the construction industry has been under pressure for years, so the role AI will play remains to be seen. Anyone who has no interest in technology—and wants to avoid it in the future, including the need for lifelong learning—will be even more inclined to consider a career in the social sector or the skilled trades. That said, I wouldn’t claim that these professions won’t become more digitized or that they are entirely “safe” from AI. At the same time, AI offers a great opportunity to eliminate routine tasks that aren’t necessarily enjoyable.
In recent years, the shortage of skilled workers in “hands-on” professions has grown. Is generative AI a helpful solution here—at least for part of the gap?
Yes; in the care sector, for instance, technology can relieve staff of tasks such as documentation. There is also significant potential in the public sector to streamline processes using AI. Where there is a shortage of skilled workers, employers increasingly view AI as a major opportunity.
Employers are increasingly using AI in the recruitment process as well. How does this affect applicants’ chances?
A major concern is that AI can lead to increased bias. Such bias depends heavily on the extent to which humans are involved in the selection process. Job applications also illustrate how AI can create a continuous new demand for AI: generative AI reduces the effort required to apply for jobs, potentially leading people to apply for more positions. Companies then have to review a higher volume of applications and might, in turn, rely more frequently on AI for initial screening. A similar scenario is conceivable in the courts, where there are early signs of a sharp rise in AI-assisted lawsuits. This is paradoxical, though the situation may shift as AI usage becomes more expensive; currently, it remains inexpensive.
Christina Lohner spoke with Oliver Schlenker.
About Oliver Schlenker
Oliver Schlenker conducts research at the Institute for Employment Research (IAB) of the Federal Employment Agency and at the Ifo Institute, focusing—among other topics—on occupations undergoing transformation.
Source: capital.de
The article originally appeared on ntv.de. Like Capital, the news portal is part of RTL Deutschland.
