Is AI Really Replacing Entry-Level Jobs At Scale?
The question of whether AI replaces entry-level jobs has been making its rounds on LinkedIn and in the media over the last few months. The default rhetorical claim is that entry-level jobs are being displaced by AI, and that the market is in danger of a near-future lack of qualified resources because these people never had the chance to earn the work experience required to transition from junior to more experienced roles.
The data does not support that conclusion.
The numbers are actually not telling a clear-cut story, and the differences between the US and Europe may in fact suggest much more about societal structures, education systems, and social benefits than about the role of AI as such. In addition, the adoption of AI is not anywhere near as high as projected by the hypers.
Complex market dynamics
A quick dive into the numbers suggests that the big picture is diverse and filled with complex patterns. Some of the factors accounting for reduced graduate hires in the US are:
Collapse of VC funding, which implicitly eradicated many entry-level tech positions.
A decade-long surge in computer science degrees flooding the market around the same time as demand contracted.
Interest rate shock as The Fed moved from 0% to 5.25–5.5% interest in roughly 18 months.
Post-COVID demand normalisation in the tech industry.
In Europe, the characteristics of northern versus southern countries are quite different, with certain shared patterns:
The ECB raised rates from –0.5% to 4.0% in approximately 14 months (July 2022–September 2023), freezing business investment and reducing hiring across the eurozone, hitting Germany and southern Europe hardest.
Politically driven graduate oversupply without matching job creation, causing a significant mismatch between the skills needed, available roles, and graduate competence.
Russia's invasion of Ukraine caused ripple effects in the form of high energy prices and economic stagnation, cascading through European supply chains and suppressing private-sector hiring.
The closing of the Strait of Hormuz has caused a surge in logistics costs, impacting many industries across Europe.
A majority of the articles on entry-level unemployment are based on US data. The structural factors driving the US situation are largely specific to that market. Conclusions and causal claims derived from US data are therefore not directly applicable to other markets, such as Europe.
All in all, the numbers do not tell an unequivocal story about AI replacing junior resources in the workplace. Still, it is impossible to ignore the reality that traditional junior-level tasks are, to some extent, gradually being solved by computers in general and AI in particular. No matter the scale of the numbers, a key challenge remains: how do we provide the "learning by doing" experience required for juniors to turn into senior resources when the juniors are not recruited in the first place?
Many of the articles I have read lately put the blame on AI and implicitly indicate either that companies should stop adopting AI to avoid this apparent lack of entry-level jobs, or that they should still hire juniors, even if they neither need them nor have the budgets for them, in order to ensure the curation of experienced resources. Both options amount to a kind of regressive collective social charity that is unlikely to gain significant traction.
Wasting the clients' money
I graduated from my first master's degree (in biophysics) in 2000. I had spent the previous two summers as a summer intern at Accenture and was offered a position as an analyst upon graduation. Over the next two years, I was assigned to different projects, all within the same industry.
The common thread was that all my tasks were entry-level, incredibly dull, and could have been solved by anybody with minimal computer skills. A master's degree was complete overkill. The workload was also so light that I could probably have worked 50% and still had time for long lunches.
When I tried to explain this to my superiors, I was told that all juniors had to endure this type of work. The work continued to feel incredibly boring, pointless (in my eyes), and like a waste of the clients' money. Eventually, after complaining too much, the superiors of my superiors told me to shut up, do as I was told, continue to bill client hours - or leave the company. I left.
What does an entry-level role actually entail?
Be honest with yourself: how often have you given your junior resources daft no-brainer tasks? And did you do that because they "have to learn the hard way", like you did? Every time I hear arguments about AI taking over entry-level jobs, I catch myself wondering whether these entry-level jobs were really value-creating, a way to continue billing the client, or revenge for one’s own tedious junior workload.
When tools change, jobs to be done change. When jobs to be done change, roles change. That includes both entry-level and more experienced positions. Future junior resources will expect to use the same tools as experienced resources, and they will learn what they need in new ways.
The board chair of a company I work with recently asked me whether the company should specifically employ entry-level juniors to bring new skills and perspectives into the organisation. The intention was not to push these entry-level juniors through the internal A4 grind of "learning by doing", but rather to acknowledge that the company would benefit from onboarding resources with different skill sets and perspectives.
His perspective was wholeheartedly that entry-level resources would contribute with new ways of thinking, solving, and working. That is a fundamentally different hiring logic.
Redefine entry-level, don't eliminate it
The traditional model assigned juniors low-complexity tasks on the assumption that volume and repetition built competence. When computers in general and AI in particular take over a fair share of these tasks, the assumption is no longer valid.
A redefined entry-level role looks different. Juniors will not produce first drafts manually if a tool can do it equally well. They will not create Excel spreadsheets from scratch just for the sake of it if there are faster ways. They will apply domain knowledge to validate, challenge, and improve outputs, requiring critical thinking from day one. "Learning by doing" thus becomes a steeper curve with a faster onset.
Companies that understand this will not ask, "Do we need juniors?", but rather challenge what kind of judgement is needed.
Rethinking education
Regarding automation of entry-level tasks, the question is not whether computers are displacing juniors, but rather what students need to learn during college or university to acquire the skills required to be useful at a higher level of complexity than before. Companies should hire for reasoning skills, domain curiosity, and tool literacy. Through structured onboarding that exposes juniors to complex problems early, combined with senior oversight that teaches judgement rather than merely task completion, those juniors will gain the required experience. And they will probably do that faster than you did.
What was historically good enough is no longer sufficient.
Education can also no longer be something you do until age 25 and then consider complete. On the contrary, to throw out a challenge: perhaps an admission requirement for future law students should be a bachelor's degree in computer science, business, or humanities combined with five years of work experience?
What should your company do?
When tools change, jobs to be done change. When jobs to be done change, roles change. This means that the format and content of entry-level tasks also need to be redefined.
The next time someone tells you that you should continue doing things the same way as before in order to keep juniors in their old place, don't just agree.
Rethink.
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About the author
Elin Hauge is a keynote speaker, AI strategist, and trusted advisor to business leaders and boards. She specialises in helping organisations make sense of artificial intelligence beyond the hype, connecting technology to strategy, governance, and real-world value. With a multidisciplinary background in physics, mathematics, business, and law, Elin brings both analytical rigour and practical perspective. Her talks and advisory work empower leaders to ask better questions, make wiser decisions, and navigate AI with confidence.
Frequently Asked Questions
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Not in a simple or universal way. While AI is automating some low-complexity tasks traditionally assigned to junior employees, the broader labour market dynamics are far more complex. Economic conditions, interest rates, hiring freezes, graduate oversupply, and structural changes all contribute to reduced junior hiring.
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Several factors are affecting graduate hiring simultaneously. In the US, reduced venture capital funding, post-pandemic market corrections, and interest rate increases have significantly impacted hiring. In Europe, energy costs, economic stagnation, and structural mismatches between education systems and labour market needs also play major roles.
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No. Entry-level roles are more likely to evolve than disappear. The repetitive and administrative tasks traditionally assigned to juniors are increasingly automated, but companies still need new employees who can reason, validate outputs, challenge assumptions, and contribute fresh perspectives.
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Reasoning ability, domain understanding, adaptability, communication skills, and tool literacy are becoming increasingly important. Companies will place greater value on people who can work effectively with AI-enabled systems rather than perform repetitive manual tasks.
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Companies should redesign onboarding and junior roles around exposure to real complexity earlier in the career journey. Instead of using juniors primarily for repetitive low-value tasks, organisations should focus on developing judgement, contextual understanding, and collaborative problem-solving capabilities.
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Yes, but the nature of learning by doing is changing. Junior employees will likely face steeper learning curves and engage with more complex work earlier than previous generations, supported by AI tools and stronger senior guidance.