I’ve been thinking about something lately, and I don’t have a clear answer to it.
We spend a lot of time discussing how AI is changing the way we work. How much more productive we can become. How many tasks can be automated. How much more a smaller team can accomplish.
All very exciting, and I see enormous potential in it.
But there’s another question that keeps coming back to me.
If AI is increasingly doing the work that young professionals traditionally learned from, how will they develop the experience to become tomorrow’s leaders?
It’s a question that feels particularly relevant to me, having spent much of my career building businesses and developing teams across different markets.
The work we complained about may have taught us more than we realised
When I look back at the early years of my career, a lot of the work wasn’t particularly glamorous.
Preparing presentations. Pulling together reports. Researching clients. Working through numbers. Sitting in meetings where you were mostly expected to listen.
I suspect many of us wondered why we were spending so much time doing things that seemed so repetitive.
But something interesting was happening along the way.
You started understanding how a business really worked.
You watched an experienced colleague handle a difficult customer conversation. You learned why a particular argument worked in one meeting but failed in another. You began recognising when something didn’t quite add up, even when the numbers looked perfectly fine.
And sometimes you got things wrong.
I certainly did.
Looking back, I wonder whether those experiences were doing something far more important than simply getting the work done.
They were helping us develop judgment.
Not through a formal training programme, but through exposure, repetition, mistakes and watching people who knew more than we did.
Now imagine starting your career today
AI can already do much of that early work remarkably well.
It can produce a first draft of a presentation, analyse data, research a client, summarise a market and prepare a reasonably sophisticated business recommendation.
In many cases, faster and more comprehensively than a junior professional could.
And that’s genuinely exciting.
But here’s where I find myself conflicted.
If someone can produce an excellent client presentation in twenty minutes using AI, that’s a wonderful productivity gain.
But do they understand why the recommendation makes sense?
Can they defend the assumptions?
Can they recognise when the analysis is technically correct but commercially wrong?
Or are we potentially creating a situation where the quality of the output is improving faster than the judgment of the person producing it?
I don’t know whether that’s happening at scale yet.
But I think it’s worth exploring.
This is becoming a wider conversation
I’m clearly not the only one thinking about this.
A recent McKinsey article, Building Expertise in the Age of AI: Who Trains the Next Generation?, explores how automation is changing the traditional apprenticeship model through which young professionals develop expertise.
José Parra Moyano, writing for IMD in How to Build Judgment When AI Does the Work, raises a similar concern about the experience young professionals may lose as routine work becomes automated.
And recent reporting by TechTarget examines how AI may be changing the early stages of the corporate career ladder.
What I find interesting is that these conversations are no longer simply about whether AI will eliminate jobs.
They’re increasingly about what happens to the development of people when the nature of those jobs changes.
And I think that’s a much more complicated question.
I’ve seen what it takes for people to grow
One of the most rewarding parts of my career has been watching people develop.
I’ve worked with teams across different countries, cultures and levels of experience. Some people joined with very little commercial exposure and went on to become exceptional business leaders.
What made that transformation possible?
It wasn’t always the training programmes.
Often, it was the experience of being in the room.
Watching a difficult negotiation unfold. Understanding why a client said no. Learning when to push an argument and when to let it go.
And, importantly, having someone more experienced explain what had just happened.
Over time, people developed instincts that no presentation or training manual could fully teach.
Now I wonder how much of that experience will be available to someone starting out today.
If AI handles the preparation, the research and increasingly parts of the execution, will young professionals get closer to the interesting decisions?
Or will organisations simply decide they need fewer people?
Those are two very different futures.
Perhaps we’re looking at this the wrong way
There’s another possibility that I find equally interesting.
What if AI helps young professionals become better, faster?
What if someone starting their career today can access insights, research and analysis that took my generation years to learn?
What if they spend less time building presentations and more time understanding customers?
Less time collecting information and more time questioning it?
Less time doing repetitive work and more time participating in decisions?
That could be a remarkable shift.
In fact, perhaps some of the traditional ways we developed people were unnecessarily slow.
We shouldn’t romanticise inefficient work simply because that’s how we learned.
But I do wonder whether we’re assuming that removing the work automatically creates better opportunities to learn.
It might. But who is making sure it does?
The leadership question nobody can afford to ignore
There is something else that concerns me.
In most businesses I’ve led, the pressure to deliver results has always been immediate.
Quarterly targets. Revenue growth. Margins. Productivity.
If AI allows a team of ten to accomplish what previously required fifteen, that’s a compelling business proposition.
But what if some of those five roles were also where the organisation’s future leaders were learning?
The productivity benefit shows up today.
The potential cost of lost experience may not show up for another five or ten years.
And by then, it may be much harder to correct.
Interestingly, not every company appears to be responding by reducing its junior workforce. IMD has highlighted IBM’s plans to expand graduate recruitment while redesigning early-career roles around new responsibilities.
That suggests another possibility: perhaps AI doesn’t have to weaken the talent pipeline. It could change how we build it.
But that takes a different kind of thinking about productivity and investment in people.
I keep coming back to judgment
In an earlier article in this series, I wrote about why I believe judgment may become one of the most valuable human capabilities in an AI-driven world.
The more I think about it, the more I realise there’s another side to that argument.
If judgment becomes more valuable, how do we make sure the next generation gets the opportunity to develop it?
I don’t think the answer is to keep young people doing work that AI can perform better.
And I certainly don’t believe that the next generation needs to follow the same path that mine did.
They will probably develop skills and ways of thinking that we haven’t even imagined yet.
But I do think we should be careful about confusing access to knowledge with the development of experience.
The two aren’t quite the same thing.
Perhaps AI will make the next generation of leaders far more capable than ours.
I genuinely hope it does.
But perhaps we also need to rethink what learning on the job means when so much of the job can be done by a machine.
Because while we’re busy teaching AI to do more of our work, I wonder whether we’re spending enough time thinking about who’s teaching the people who will eventually lead our businesses.
And perhaps the bigger question is this: are we using AI to accelerate the development of the next generation, or simply to reduce our dependence on them?
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