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As AI automates entry-level work, the way we learn on the job is shifting. Mentorship won’t vanish, but its purpose is evolving into something far more human. I won’t be out of a job, probably.
AI won’t replace mentorship, but it will redefine it
There’s a lot of talk about how AI will reshape entry-level work. But one thing feels clear to me: the more AI we use, the more human mentorship will matter.
If automation takes over much of the ‘grunt work’ — the slide decks, data cleaning, and report writing — then the early years of a career will look very different. Those repetitive tasks used to be where people learned the fundamentals: how to spot errors, what ‘good’ looks like, and how to read the room in meetings. Without that apprenticeship-style learning, we’ll need a new way to build judgment. That’s where mentorship comes in.
From task-based training to mindset mentoring
Early-career professionals won’t just need feedback on their output; they’ll need guidance on how to think. How to frame a problem, how to challenge AI outputs responsibly, how to decide what matters most. These are the skills that don’t come from prompts: they come from people.
AI can generate a solid first draft of almost anything. But deciding whether it’s right, ethical, or worth pursuing is still a human call. Mentorship will increasingly be about developing that discernment.
AI will accelerate learning, but also expose gaps
If AI speeds up basic tasks, juniors will move to higher-order work faster. That’s exciting, but also risky. You can’t absorb leadership instincts, client diplomacy, or strategic prioritisation from a chatbot. Those lessons come from watching people make tough calls in real time.
In hybrid and remote work environments, that kind of observation is already limited. If automation removes even more “on-the-job” learning moments, organisations will have to be intentional about recreating them. That might mean job shadowing programs, structured debriefs, or more frequent feedback loops.
