EXPERT COLUMN
What next for entry-level roles in tech? by Ben Leitch – Digital Content Manager
The first rung on the career ladder has always been sacred. It’ s where bright graduates cut their teeth, where curiosity meets reality and where organisations quietly build the foundations of future leadership. But as AI seeps into every operational layer, that first rung is starting to crack, and for many young people hoping to start a career in technology, it’ s disappearing altogether.
Recent studies show what many of us have felt coming for years: AI is no longer nibbling at the edges of entry-level work; it’ s devouring the middle. Reports from the British Standards Institution suggest that 41 % of global business leaders believe AI is allowing them to reduce headcount, and a quarter think most entry-level tasks can now be automated. What used to be the proving ground is increasingly being handled by machines that don’ t sleep, don’ t make typos and don’ t need a graduate induction week.
The question isn’ t whether AI can replace entry-level roles – it already has. The question is: what’ s next for the people who would have filled them?
For decades, the tech industry has relied on a predictable rhythm. Universities produced technically trained graduates, employers hired them into junior roles and over time they grew into engineers, analysts, managers and leaders. The system worked because it had space for inexperience. It assumed that people would learn by making small mistakes, asking naïve questions and gradually earning responsibility. But now
that model is under threat. If AI systems take on the grunt work, where do humans
learn the craft?
There are a few ways this can go, and all depend on whether organisations see this as a crisis or an opportunity. The optimistic view is that AI will force us to rethink early careers entirely – not as cheap labour pipelines, but as accelerated learning environments. If machines take care of the repetitive tasks, new entrants could focus on creativity, design, strategy and problemsolving. But that requires a radical shift in how we train and support them. It means structured learning pathways, projectbased mentorship and deliberate exposure to the‘ why’ of technology, not just the‘ how’.
The less optimistic view is that many companies are quietly removing entry-level positions without building new pathways to replace them. It’ s efficient in the shortterm, but disastrous in the long-term. Every experienced developer, product manager or data scientist once had a first job that taught them not just skills, but the rhythm of work, the politics of collaboration, the muscle memory of debugging under pressure. You can’ t automate that kind of learning; you can only invest in it.
Companies need to treat early-career talent as a strategic resource, not an operational expense. That might mean expanding internships into year-long residencies, creating rotational graduate programmes that blend AI-assisted work with human-led projects or partnering with universities and bootcamps to simulate the kind of experiential learning once gained on the job. Governments, too, have a role to play here: if they want to preserve a competitive workforce, they must support transitions between education and work that acknowledge automation’ s role but still prioritise human growth.
For graduates themselves, the message is sobering but not hopeless. The entry point may no longer be‘ junior analyst’ or‘ associate developer’, but opportunity still exists. AI may write the first draft of the code, but humans still need to define the problem, interpret the data and ensure the outcome is ethical, useful and aligned to business goals. Those are skills that demand not just technical literacy, but critical thinking, communication and adaptability. The real differentiator for the next generation won’ t be how well they use the tools, but how well they can think alongside them. x
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