AI is replacing entry-level jobs

AI is replacing traditional junior roles, making it harder than ever for those starting out in their careers to enter the workforce.

Robot employees are replacing human workers in office-based computer roles.

Starting a career used to be a predictable process: training, studying, getting a first job, and then climbing the career ladder. But this logic is faltering. Artificial intelligence (AI) is increasingly automating tasks traditionally performed by career starters, such as research, data preparation, simple programming, standard design, and routine administrative and accounting work. Companies that streamline their processes using AI tools specifically reduce entry-level positions. This lowers costs and fundamentally changes the personnel structure.

Young talent is currently facing unprecedented difficulties. According to an exclusive analysis by the StepStone job platform, the proportion of job advertisements for career starters in Germany has fallen to a record low. In the first quarter of 2025, this figure was 45 per cent below the five-year average – the lowest since records began. In addition to economic uncertainty, one particular structural driver is artificial intelligence (AI).

AI offers efficiency gains for companies, but also results in a loss of learning opportunities.

The use of generative AI is often beneficial for companies, as projects can be implemented faster, more precisely and more cost-effectively. However, for career starters, this means fewer opportunities to learn through practical work. Many traditional 'learning jobs' are disappearing. In the creative industries, AI systems are already taking over aspects of text creation, such as initial layouts and headlines in journalism, and contract drafting in the legal industry. The problem is that those who cannot get started do not gain experience and remain stuck in the application loop.

AI tools are rapidly taking over the activities that have long formed the core of junior roles, from checking programme code in IT to conducting market and legal research in consultancies and law firms, and creating presentations. Text-based, clearly structured, repetitive tasks in industries such as IT, law, and management consultancy are particularly affected. 'AI now delivers 60 to 80 per cent of the quality of a human result in a matter of minutes,' says Harald Fortmann, Vice President of the Federal Association of German Management Consultants (BDU). This is equivalent to the output of a junior employee, who would require 'hours or days' to produce the same results.

The labour market is under pressure to adapt.

Further studies show that, by 2030, millions of jobs worldwide will disappear as a result of automation, while new fields of work will simultaneously emerge. However, these new jobs often require higher qualifications and technical understanding — skills that are difficult for career starters without practical experience to develop. This makes access to well-paid positions more difficult. Paradoxically, companies complain of a shortage of skilled workers in higher-qualified areas while entry-level applicants are overlooked.

This contradiction is nowhere more apparent than in the tech industry. Although the industry association Bitkom predicts a shortage of approximately 660,000 IT specialists by 2040, the number of vacancies in the IT sector has been falling for two years, dropping from 149,000 to 109,000. According to Bitkom, 27 per cent of companies expect job cuts due to AI. Junior software development roles have been particularly affected, with job postings in this area declining by 54 per cent since 2020, according to Indeed. This is due to tools such as GitHub Copilot and Lovable, which automate classic entry-level tasks.

Rethinking entry-level roles

Labour market researchers are therefore calling for entry-level roles to be redesigned so that they are hybrid, with AI acting as a routine assistant and with a focus on value creation, creativity and customer contact. Companies such as McKinsey are already adopting these models: AI writes drafts, while consultants focus more on coaching and strategic advice.

According to a joint study by McKinsey and the Stifterverband, critical thinking, judgement, communication skills and emotional intelligence will be key differentiators from algorithms in the future. AI competence is becoming an increasingly basic requirement.

Conclusion:

The disappearance of entry-level jobs is not a marginal phenomenon, but rather a warning sign for the future viability of companies. While AI can reduce costs in the short term, there is a risk of losses in productivity and innovation in the long term if knowledge is not passed on. While AI may be able to replace many things, it cannot train talent. Companies must start this process now, or they will face a competitive disadvantage in a few years.

Fact box

Current situation:

• Proportion of job advertisements for career starters in Germany in Q1/2025: -45% compared to the five-year average (StepStone).
• Particularly affected sectors: IT, management consulting, legal services and the creative industries.
• Typical tasks being eliminated include research, data preparation, simple programming, standard design and routine accounting/administrative work.
• Technological driver:
• AI tools such as GitHub Copilot, Lovable, and generative text systems can perform 60–80% of junior-level tasks in minutes.
• Automation primarily affects structured, repetitive, text- or data-based tasks.

Labour market trend:

• Forecast: By 2030, millions of jobs worldwide will have been lost due to automation, and new roles will require higher qualifications.
• Paradox: a shortage of skilled workers in highly qualified positions, coupled with a decline in traditional entry-level roles.
• In IT: Vacancies have fallen from 149,000 in 2023 to 109,000 in 2025, with junior developer roles declining by 54% since 2020 (Indeed).

Strategies for companies:

• Hybrid entry-level profiles: A combination of AI-supported routine work and practice-oriented projects.
• Focus on soft skills such as critical thinking, judgement, communication and empathy.
• AI competence as a basis: training junior staff in the use and evaluation of AI results.
• Mentoring and knowledge transfer ensure that expertise is not 'lost to automation'.