For years, one of the biggest conversations around AI has been whether it will replace jobs.
But there may be another question we should be asking.
If AI starts doing more of the work traditionally given to junior employees, how do those employees gain the experience they need to eventually become senior?
Early careers have always involved learning by doing. Researching, preparing first drafts, analysing information, completing basic coding tasks, creating reports, handling admin and supporting more experienced colleagues might not always be the most exciting parts of a job, but they’re often where people develop their foundations.
You make mistakes. You see how more experienced colleagues approach problems. You learn what good looks like. Eventually, you’re trusted with more responsibility.
AI is beginning to change that process.
Many of the tasks that once formed the starting point of someone’s career can now be completed, or at least significantly accelerated, using AI. A junior developer can generate code in seconds. An analyst can summarise large amounts of information almost instantly. Research that might previously have taken hours can be completed far more quickly.
From a business perspective, that’s incredibly valuable. Teams can move faster, experienced employees can spend less time on repetitive work, and smaller groups of people can potentially achieve much more.
But there could also be a longer-term consequence.
If businesses decide they no longer need as many junior employees because AI can handle much of the work those employees traditionally performed, they risk weakening the very talent pipeline they will depend on in the future.
You can’t hire experienced people forever without someone first being given the opportunity to become experienced.
And we’re already seeing signs that expectations at entry level are changing. PwC’s 2026 Global AI Jobs Barometer analysed 2.4 million entry-level roles in the US and found that the roles most exposed to AI are now seven times more likely to require skills traditionally associated with senior employees, including leadership and strategic thinking. Interestingly, these more demanding entry-level roles have grown by 35% since 2019, while other entry-level roles declined by 10%. That creates an interesting contradiction.
Businesses increasingly want junior candidates who demonstrate judgement, adaptability, leadership and decision-making, but those are often qualities people develop through experience.
So where does that experience come from if some of the traditional learning opportunities disappear? Perhaps the answer isn’t to protect junior tasks from AI. It’s to completely rethink what a junior role looks like.
Instead of spending their first few years completing repetitive work, early-career employees could use AI to accelerate those tasks and become involved in higher-value work much sooner. They could contribute to decision-making earlier, solve more complicated problems, work more closely with customers and learn from experienced colleagues in ways that previously might not have happened until much later in their careers.
In that scenario, AI doesn’t remove the career ladder. It shortens some of the steps.
But that only works if businesses continue investing in development. Giving a junior employee access to AI isn’t the same as giving them experience. They still need mentoring, feedback, exposure to difficult situations and the opportunity to understand why a decision was made, not simply what the answer was.
This could also change what recruiters and hiring managers look for at entry level.
Experience will obviously continue to matter, but qualities such as curiosity, adaptability, communication and critical thinking may become increasingly important. Businesses may need to look beyond whether someone has completed a particular task before and consider whether they have the ability to learn quickly, challenge an AI-generated answer and make good decisions with the information they’re given.
PwC’s research points in a similar direction, finding that AI-exposed jobs are increasingly placing greater emphasis on human skills such as judgement, creativity and leadership.
There is also a bigger strategic question for businesses.
AI creates an obvious opportunity to improve productivity today. But workforce planning can’t only be about today’s efficiency. Companies also need to think about who will become their managers, specialists and leaders five or ten years from now.
If every business decides it only wants experienced talent, while simultaneously reducing opportunities for inexperienced people to learn, eventually the market has a problem.
The companies that navigate this well may therefore be the ones that don’t see AI simply as a way to reduce junior headcount. Instead, they’ll use it to change how junior employees learn and how quickly talented people can develop.
Because becoming senior has never simply been about completing enough basic tasks.
It’s about building judgement. Understanding context. Getting things wrong and learning why. Seeing how decisions play out. Taking responsibility and gradually becoming someone other people trust to make the call.
AI can help someone reach an answer faster.
It can’t give them years of experience overnight.
So perhaps the question isn’t whether AI will replace junior work.
It’s whether businesses can redesign junior careers quickly enough to make sure there are still experienced people to hire in the future.
