I kinda think of this post as a sequel to my analysis on “The Hidden Impact of AI on Your Skills”.
Somehow, it’s been a year since I hit publish on that one.
Isn’t it funny how time works? I remember so clearly spending months researching and putting all the pieces together to look deeper into the real impact of AI on skills so far, and now, here I am talking about it like some sort of ancient text.
My reminiscing aside…
The message of that piece was to think deeply about the over-reliance we will easily slip into with AI, and how easy it will be to convince ourselves we’re learning how to do something, when in reality, AI is doing it for us.
A year later, I only see more activity, which has amplified both.
That’s not to say there are not those who are rejecting total delegation to AI and those finding the balance between artificial and human intelligence.
We’ll talk about some of those later.
Consequences
It’s such a serious sounding word, isn’t it?
Like something your parents would say to you.
Our choices can lead to consequences in many forms, that’s the risk we all take, and not to keep sounding like some old stoic, but life is essentially all about risk.
Back in October last year, when I spoke about AI over-reliance and the illusion of expertise, I only covered in small detail what the consequences of those choices could mean.
A year later, it’s clear to me that’s skill erosion.
The Great Erosion of Skills
Do you remember just after the pandemic, when every headline was something like “The Great ‘x’ of blah blah?”
I’m happy to make a contribution to that movement 😂.
Jokes aside, you might be noticing some people’s skill sets are eroding through lack of use, and some aren’t even learning the skills at all. This is being driven by the change in the tasks we now deliver.
As AI gets better and better at completing a wide variety of tasks, it means we (as humans) do less in certain areas.
That is not always a bad thing.
Cognitive offloading of some tasks can amplify our ability to perform better in the workplace. A good example of this is GPS. Before we had GPS in our lives to guide us to destinations, we’d spend hours pouring over gigantic maps with tiny text, trying to figure out the best route.
Now, at the touch of a button, we’re guided without having to activate one brain cell.
There’s another side to this coin, though.
Humans, for the most part, want to take the path of least resistance and favour instant gratification over the challenge (I’m no different here).
The problem is that real learning and thus improved performance are about navigating the challenges. It’s really hard to learn how, what and why if you don’t experience the struggle.
AI doesn’t take this away all on its own, how we use AI does.
In our quest for “more time”, “creative freedom”, “improved efficiency” and every other statement that tech CEOs blurt out about AI, we’ve become obsessed with the automation of everything.
This creates the consequences I’m talking about.
What we lose and what we gain
I always remember an old colleague saying, “You can have it all, you just can’t have it at the same time”.
While it was in relation to something else, I can’t help but think it fits well in this conversation.
I’ve found life to be a series of trade-offs.
If you say yes to one thing, you’re saying no to something else. It sounds like easy math (and it is), but it’s by no means a simple equation.
I’m not the first to consider the impact of AI in this way.
The folks at Gartner have been covering this as they look towards what is putting future workforce’s at risk.
Here’s an excerpt to ponder:
Gartner predicts that by 2028, 40% of employees will be trained and coached by AI when entering new roles, up from less than 5% today.
While this shift promises faster onboarding and adaptive, scalable learning, it also means fewer chances for employees to learn from experienced peers. Junior staff, who once relied on mentorship and hands-on experience, will learn primarily from AI tools, while senior staff increasingly depend on AI to complete complex work.
This shift accelerates the loss of foundational skills and weakens expert mentorship and relationship development across the organization.
Source: Gartner
We have skills eroding through lack of practice and application, and it seems, the quick expiring of skill creation with future generations entering the workforce.
Harold Joche put it nicely when he said, “One key factor in understanding how we learn and develop skills is that experience cannot be automated”.
So, what can be done?
Are we doomed to roam the world skill-less and watch AI-powered tools suck the life out of the world itself? Of course not, there is a way, my fellow human hacker.
Strategies and tactics to prevent skill erosion
So, instead of moaning about the great wave of skill erosion, I’d rather focus on doing something about it.
The good news is there’s a lot we can all do.
If you haven’t already, you can find a ton of my guidance in these articles:
- The Hidden impact of AI on your skills
- How to stop AI from hijacking your thinking?
Saves me repeating myself like a broken record here.
Plus, the folks at Gartner offer some basic but useful actions for the workforce:
- Watch for AI mistakes and rising error costs, and keep manual checks in place where AI is used most.
- Retain your senior staff and encourage peer learning to slow skill loss.
- Focus on roles at risk and review your talent strategies regularly to keep key skills strong.
- Pair AI with human oversight and maintain manual checks as a backup for AI.
- Encourage employees to continue exercising core skills (e.g., analysis, coding, problem-solving) even when AI tools are available — through simulations, rotations and shadowing.
- Use AI simulations and adaptive training, but make sure people still learn from each other.
My question to you: What would you add?
Final thoughts
There’s much more to ponder on this.
Like with everything in this space, whether it happens or not is down to your individual choices and intentions. So, if you want to craft a career for the long haul, make smarter choices when it comes to your skills.
Before you go… 👋
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