AI in Learning: A Shortcut to Knowledge or a Setback to Growth?

You’ve probably noticed it.

People asking AI to summarise books they’ll never read. Write strategies they’ll never truly understand. Even answer questions they haven’t fully thought through.

Maybe they are even asking it to describe the way they are feeling about a situation or circumstance.

And let’s be honest, they do it because it works.

It will give you that book summary in the way you requested. It will outline whatever strategies satisfy the prompt. It will answer whatever type of question you feed it in whatever it determines to be the most accurate way.

Ultimately, that’s why it is becoming more and more common.

It’s fast. It’s polished. It’s impressive.

This blog has been brewing for a while, through lots of conversations about the rise of AI in learning. But one moment that really stuck and helped shape this piece was a chat with a client.

They admitted, with total honesty, that they were scared. Not of AI itself, but of how quickly its use was becoming automatic. Habitual. And how unsure they felt about how to guide people through it.

So here’s the question we’ve been thinking about:
What is this doing to the way we learn?

And perhaps more importantly…
What might we be losing because of this instantaneous process of getting the answers we need?

Why We’re Excited About AI

Let’s just say this now… we’re not anti-AI.

Far from it. We’re excited by what it can do.

Used well, it can break down barriers, it can help people get unstuck, it can boost confidence and speed things up when time is tight.

We’ve seen it spark ideas, save hours and simplify the complex. So, this isn’t a warning blog. This is a let’s pay attention blog.

Because AI can do a lot... but it can’t replace the parts of learning that matter most.

Learning, Interrupted

We are writing this trying not to sound like someone reminiscing blurry-eyed about the 'good ol days'. This is important context.

Learning used to be a full-body experience.

You didn’t just Google an answer. You felt your way through a challenge.

You connected ideas. You reflected. You tested. You made mistakes... because who doesn't make errors?

But importantly, you owned the knowledge that came with that whole journey.

But now?

We’re skipping straight to the result, eliminating that whole journey of discovery.

And while that saves time in the short term, it’s costing us something much more important: growth.

When you rely on AI to do the thinking for you, you rob yourself of the struggle. And it’s the struggle that makes the learning stick.

Think of the last thing you truly mastered. It didn’t come from watching someone else do it. It came from trying, failing, reworking, and finally getting there.

That’s where confidence is built.

That’s where change happens.

We don’t believe AI eliminates that growth. But without the right structure around it, people might accidentally skip it.

What We Lose When We Skip the Journey

Let’s break it down. Overreliance on AI can affect the core components of deep learning:

• Critical thinking: You don’t need to analyse or interpret if the answer is handed to you
• Problem solving: If a solution is one click away, you never have to develop your own
• Resilience: Growth comes from grappling with the unfamiliar, productising our relationship with failure and not outsourcing discomfort
• Curiosity: If every question has an instant answer, why explore it further ourselves?

And over time, this does something subtle but dangerous. It shifts our mindset.

We begin to see learning as a task to complete, not a journey to grow through.

We lose patience. We avoid effort. We stop developing the very capabilities that make us adaptable, creative, and capable.

In other words, we become consumers of knowledge, not creators of it.

That doesn’t mean we need to back away from using AI. But it does mean we need to design learning environments that bring people back into the process, not push them further out.

The Hidden Risk: When Soft Skills Slip

While AI can offer rapid knowledge access, it can also quietly erode the very human capabilities that make learning effective in the first place.

We’re talking about things like:

• Curiosity – the drive to go deeper than surface-level information
• Resilience – the willingness to sit with discomfort, break through barriers and push through challenge
• Critical thinking – questioning, analysing, and evaluating rather than just accepting and trusting what we are provided with
• Confidence – built not through information, but through effort and application

These are the traits that make learners engaged, open, and ready to grow.

But if learners are becoming overly reliant on AI, skipping steps, outsourcing thinking, or rushing through pre-work, even the best-designed programme can be met with disengagement or surface-level participation.

This doesn’t mean learning programmes don’t work. It means we have to design them in a way that works with these evolving behaviours, not against them.

And crucially, it means making AI a part of the conversation so that learners are empowered to use it without disconnecting from their own development.

A Cultural Shift L&D Leaders Can’t Ignore

The rise of AI in learning isn't inherently a problem. In fact, many learners are using AI in entirely understandable ways.

They’re using it to get up to speed quickly. To help write pre-work reflections. To generate ideas. To make sense of complex topics.

In a world of limited time and growing demands, this kind of usage makes sense.

But over time, how people use AI can quietly shift the culture of learning inside an organisation.

You may start to see:

• A dip in initiative – learners wait for instructions or instant answers rather than exploring
• Decreased curiosity – engagement becomes passive, not proactive
• Surface-level completion – learning becomes a tick-box exercise rather than a tool for growth
• Less ownership – people start trusting outputs more than their own judgement or insight

Even tools that seem purely practical, like automated meeting notes, can have an unexpected impact. When learners rely too heavily on transcripts or summaries, they may stop paying attention in real time. The intent is to support productivity, but the result can be reduced focus and weaker retention.

That’s why it’s important for L&D leaders to stay curious and observant about how AI is showing up in learners' habits. Not to discourage use, but to make sure it’s enhancing learning, not quietly replacing the parts that make it meaningful.

Because ultimately, all things worth having should feel difficult to obtain.

With thoughtful programme design and open conversations, you can help learners use AI as a tool for growth, not a shortcut away from it.

The Role of AI in Learning (When Used Well)

This isn’t an AI-bashing blog.

I am not about to tell you to throw out all your electrical devices and instruct your colleagues and loved ones to do the same.

We believe AI can be a powerful learning ally when used intentionally.

It can:

• Personalise learning journeys
• Surface insights at scale
• Make content more accessible
• Save hours in content creation
• Enable faster feedback and reinforcement

At Excel, we’re already exploring ways AI can enhance the learning experience. And we’re just getting started.

We’re experimenting with how AI can help us increase impact. But with every experiment, the goal stays the same: to make learning stick and make people stronger.

AI should optimise learning. Not replace it.

It should support the process. Not become the process.

It should be a co-pilot. Not the driver.

What This Means for L&D

If we want to futureproof learning in a world where AI is everywhere, we need to double down on the human side of development.

That means:

• Creating space for challenge, exploration, and reflection
• Designing programmes that stretch people, not just inform them
• Embedding learning into real-world practice, not just theory
• Building confidence through experience, not instant answers

At the same time, we can’t design learning as if AI doesn’t exist, and we certainly shouldn’t deliver workshops as if it’s not already part of how people think, work, and learn.

Ignoring AI in the classroom risks making learning feel disconnected from the real world.
Instead, we should be open about it. Facilitate conversations about how learners are using it. Explore where it helps and where it hinders. Give people the space to think critically about its role in their development.

AI is here, and it’s shaping habits whether we acknowledge it or not.

So our job is to build learning that recognises the tools people are already using and helps them use those tools with intention.

It also means helping people develop learning agility, the ability to learn, unlearn, and relearn quickly, because that’s the skill that will matter most as the world continues to change.

AI can help us get there faster. But the destination still needs to be earned.

Human-Centred Learning That Sticks

At Excel, we’re already seeing this shift and designing learning to meet it head-on.

That means:

• Creating challenges that encourage reflection, not just retention
• Embedding real-life scenarios that demand personal input, not AI prompts
• Using human facilitation to draw out insight, connection, and behavioural change
• Helping people re-engage with their own thinking and capability

When learning is interactive, personalised and practical, it reignites the very traits that AI might be dulling.

Because no matter how advanced technology becomes, real development still needs a human spark.

The future of learning isn’t AI or humans. It’s AI and humans, each playing to their strengths.

At Excel, we design learning experiences that keep humans at the centre, where growth isn’t just about what you know, but about who you become in the process.

Because fast answers might solve today’s problem. But real learning is what prepares you for tomorrow’s challenge.

Many thanks,