If AI 'does it for you', what happens to your skills?

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 TODAY’S THOUGHTS ☠️

Hey there 👋,

What a strange week it’s been.

I’m not one for politics, but I must say, my investment portfolio is bringing me close to tears over the past 10 days.

So, let’s focus on something that doesn’t lead to me crying over my keyboard as I type these words!

Last week, I had the chance to show off my 80’s hair metal style haircut in front of a few thousand humans to talk about how AI is actually impacting our skills.

It’s another topic I’ve been obsessing over for the last year.

There’s a lot of research on AI’s impact on work performance, but less so on its short and long-term effects on skill building. However, there is some good stuff, and I weaved my own experiences from the past 3 years to showcase the current state of play.

Today, we explore what happens to your skills if AI ‘does it for you’ and how you can shape the future of skill-building with AI.

Get your tea or beverage of choice ready, 🍵.

We've got lots to discuss!

P.S. Your app might clip this edition due to size, if so, read the full edition in all its glory in your browser.

 IN THIS DROP 📔

• Shaping the future of skill-building with AI

• An Orwellian wake-up call with a powerful vision of the future of AI

• Growing your Human Chain of Thought in a world of AI-reliance

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 THE BIG THOUGHT 👀

If AI 'Does It For You', What Happens To Your Skills?

The talk I gave last week was aptly titled: “Does AI harm or help skill building?”

Spoiler alert: It can do both

The deciding factor in that outcome is YOU.

You’ll never get a straight answer in these discussions. Be aware of those that do preach the ‘one way’ approach, though. In reality, everything depends on context.

This remains true when assessing AI as a skill amplifier or destroyer.

Like with many areas of life, in the right hands and mind, AI can be powerful. Yet, in the wrong hands and mind, it can be a threat.

I’m troubled by the unexpected consequences of the manic pursuit of ‘AI at all costs.’

I sense that we already over-rely on certain tools, and in doing so, we both create illusions of capabilities and fail to invest in moments of intentional learning.

So, how do we shape a more positive path as the guardians of L&D?

Let’s talk about that, how you can set yourself up for success and share a few ideas and tools for amplifying skill-building with AI in your L&D work.

The Controversial Idea: Skills will be destroyed if we let AI do everything

Many people are scared that AI will take their job.

They think they’ll lose because AI tools can do the tasks better.

Yet, here’s a brain-stopper:

It’s easy to think, “That will never happen to me.” 

Maybe it won’t.

But I’d ask you to consider your use of AI tools today. My assumption is that most people use them in a ‘do this thing for me’ approach, rather than a “show me how to do this.”

Here exists a problem we aren’t paying enough attention to.

An AI-first approach will damage the capabilities and potential of skills (if you allow it).

My thinking behind this comes both from real-world experience with consulting clients on Gen AI skills programs and what I’ve seen in global research this past year.

An excellent piece of research from Boston Consulting Group has been one of my favourites on this topic. It unpacks, with an experiment involving 480 of their consultants, that Gen AI can increase productivity and expand capabilities.

That’s the headline, of course.

AI’s impact on skills: What we know today

The problem with most research and reports is that most don’t read beyond the headline.

Hence why we have so many cult-like statements about Gen AI’s endless power. It is powerful, in the right hands. But any power comes at a cost.

For those willing to go deeper, we find both a bundle of exciting opportunities and critical challenges.

Here’s some we haven’t discussed ↓

1/ Gen AI grants short-term superpowers

No surprise here, I think.

Gen AI tools grant easy access to skills we don’t possess. They can amplify the level of our current skills too. The BCG team coins this as an ‘exoskeleton’ effect.

Explained in their own words:

Being a nerd, I compare this to something like Iron Man.

For those not familiar with the never-ending Marvel films, Tony Stark is a character who has no superpowers (but is a highly intelligent human). To play in the realm of superheroes, he creates his own suit of armour that gives him access to incredible capabilities he doesn’t have as a human.

The caveat is that he needs the suit to do those things.

Essentially, using an AI tool is like being given a superpower you can use only for 20 minutes. It exponentially increases your abilities, but without it, you go back to your normal state. And everyone has the same access to this power.

BCG found the same in this research.

We could call this a somewhat false confidence dilemma.

This presents a few challenges to navigate:

• How do we combat the illusion of expertise?

• What happens when you don’t have access to AI?

• How do we stop addiction to the ‘easy option’?

Spoiler: I don’t have all the answers.

However, this temporary boost in abilities often leads to another problem – the illusion of expertise.

2/ We have to fight the illusion of expertise

This is a big challenge for us.

Getting people to look beyond AI’s illusion of expertise.

You know what I’m talking about.

Now everyone has access to creation tools, they all think they’re learning designers who can create their own amazing products. We both know how that’s going to turn out.

As an example in my work, I can build a decent website with AI, which does the heavy coding for me. But I can’t do it without it, not unless I learn how to do it.

Yes, I built x, but I’m not a software engineer.

There’s a big difference, and sadly, I see people falling into this trap already.

Now, with all this new tech, I don’t need to know the ‘why’ or ‘how’ behind something being built by AI.

But what does this mean for my skills?

A big part of skill acquisition focuses on the ‘why’ and ‘what’, in my opinion. I don’t need to know every little detail, but it helps to have a basic understanding.

I see a few unintended consequences if we don’t clearly define what a ‘short-term expansion enabled by tech’ is and what ‘true skill acquisition’ is:

• We over-rely on AI tools, and this over-reliance erodes critical thinking skills, a key element in real-world problem-solving

• We lose context, a sense of understanding

• Our human reasoning skills will erode in the face of “But AI can tell me”

Each of us will fall into different groups based on our motivations.

I’m not saying we’re all collectively going to become skill-less zombies addicted to a digital crack of Gen AI tools, but it will be a reality for some.

What happens to human skills if we over-rely on AI?

This is a real grey area for me.

I’ve seen countless examples where too much AI support leads to less flexing of human skills (most notably common sense), and I’ve seen examples where human skills have improved.

In my own practice, my critical thinking skills have improved with weekly AI use over the last two years. It’s what I class as an unexpected but welcome benefit.

This doesn’t happen for all, though.

BCG’s findings seem to affirm my thoughts that the default will be to over-rely.

I mean, why wouldn’t you?

This is why any AI skills program you’re building must focus on behaviours and mindset, not just ‘using a tool.’

You can only make smart decisions if you know when, why, and how to work with AI.

How to help humans use AI for REAL learning

Ok, we can see a potential problem if left unchecked.

Here’s a few ideas, tools and actions to do something about it:

1/ Cover AI fundamentals

Too often ignored with people going straight to tools.

Yet, knowing how and why a technology works means you become the chess player, and not a chess piece that’s moved by every new model and tool.

The world has lots of resources to help you with this.

Here’s some from my locker:

• AI Explained: What it means and what it doesn’t

• Generative AI for humans

• The 5-step ‘make me AI confident’ learning strategy

• The difference between AI agents and assistants

2/ Don’t confuse ‘do it for me’ with ‘learning to do’

While AI can enable individuals to complete tasks they wouldn't be able to do independently, this doesn't automatically translate to skill acquisition.

Help people recognise the difference.

To truly learn anything, you need a combination of:

1. Understanding key concepts

2. Engage in practice

3. Commitment to improve

3/ Nurture your Human Chain of Thought

I introduced this concept in last week’s edition.

You might have heard me say “AI is only as good as the human using it” like a broken record.

Like any tool, it only works in the hands of a competent and informed user.

I learned this fairly young when a power drill was thrust into my hands for a DIY mission. Always read the instructions, folks (another story for another time).

Anyway, all my research and real-life experience with building AI skills have shown me one clear lesson.

4/ Encourage critical thinking before and after using AI

Despite what social media gurus say, we all very much need to use our brains when working with AI.

If you want to do useful stuff, that is.

I’ve shared a system you can use to achieve this with all your AI interactions before. You’ll stand out from the digital zombies with this.

5/ Prompt an Engineer’s Mindset

BCG refers to this as the ‘engineer’s mindset’ as it originates from mostly engineering roles (both physical + digital).

I call it the ‘Builder’s mindset’, and I think this is a cheat code for life.

I would say I’m only as successful as I have been because of it. I learned it during my teenage years of coding in SQL and Java. It’s built around the principles of understanding what, why, and how of building anything.

Back in the day, I used it to build SQL-based reporting applications.

I didn’t even think about building the app before I knew more about the consumer.

Simple things like:

• Who are they?

• What problems are they having?

• Why are those problems happening?

• What would this look like if it were easier for them?

Over the years, I’ve adapted this into all my work, especially writing.

As of today, before I begin any work, I ask:

1. Why am I building this?

2. What problem is it solving?

3. The ‘So What’ test?

4. How will you build it?

I can only solve a problem or create a meaningful post/product/newsletter/video if I know the above.

Like a builder, you piece together an end goal.

When you reveal this, the next part is easy → Reverse engineer this process.

As this is such an important point, I need more than the written word to explain this.

So, here’s a short video where I explain how to use this framework:

Modern ways to reshape skill-building with AI

Last week, we spoke a lot about AI coaches.

We can throw AI tutors into that mix, too.

Here’s how I see the difference btw:

• AI Tutor = Breaks down concepts and works in more of a professor style

• AI Coach = Works with you in a live environment to solve challenges together. Basically, the new “Learning in the flow” but with AI.

Of course, these terms are interchangeable, and the capabilities can be merged.

FYI, today’s NL partner, Sana, is doing a great job in this department with their soon-to-be-released AI tutor. You should check that out.

Often, I find it’s easier to show you what I’m talking about with AI than try to describe it to you, so here’s examples of both:

Using AI as a Tutor with Google AI Studio

Using AI as a Coach with Google AI Studio

In case you’re wondering, I use Google AI Studio to show these features because it’s easy to access for most people.

It’s a sandbox where you can experiment.

But you shouldn’t use this for work, just as a place to experiment. For Tutor and Coach tools in the workplace, more are entering the market.

Like I said a few lines back, I recommend you check out what my friends at Sana are doing in that space.

Final thoughts

So, will AI destroy or amplify your skills?

Only if you let it.

This is by no means a closed book. No doubt, I’ll cover more on this as time goes on.

For now, be smart:

1. Craft your builder’s mindset

2. Borrow superpowers but build real ones through practice.

3. AI is powerful and has great potential, but don’t forget the unique human and technical skills you need to be ‘fit for life.’

BTW, get an even deeper version of today’s Big Thought with more research and real-world examples on my website.

→ If you’ve found this helpful, please consider sharing it wherever you hang out online, tag me in and share your thoughts.

Till next time, you stay classy, learning friend!

PS… If you’re enjoying the newsletter, will you take 4 seconds to forward this edition to a friend? It goes a long way in helping me grow the newsletter (and cut through our industry BS with actionable insights).

And one more thing, I’d love your input on how to make the newsletter even more useful for you!

So please leave a comment with:

1. Ideas you’d like covered in future editions

2. Your biggest takeaway from this edition

I read & reply to every single one of them!

 👀 ICYMI (In case you missed it!)

1. Probably the most powerful and crazy thing I’ve read on the future of AI this year. Part Sci-Fi, forecasting, dubious speculation and experience. I'm hoping none of it actually happens, but you never know. The article gives you a choice of an ending. Yet, if we follow a similar pattern to what the article depicts, I wonder if we will get that choice. Don't skip it with an AI summarisation. It deserves your full human focus.

   

2. What that leaked Shopify CEO email on the company’s use of AI tells us about the importance of empowering employees and learning cultures.

 VIDEO THOUGHTS 💾

How Are You Driving Value in L&D Across 2025?

I originally shared this video back in January.

We explored 3 ways you can drive value as an L&D team across 2025. Since it’s April, it feels like a good time to check in and see how you’re doing.

As always, fire your thoughts my way.

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