• AI chatbots and assistants
• On-demand learning materials
• Personalised learning pathways
• Internal resource libraries
• Videos and other digital resources
The emphasis is increasingly on the learner.
I sometimes think of it like a professor standing in front of their class at the beginning of term and saying:
"I could teach you all of this. But instead, here are every book, video and resource you'll need. Work through them on your own and, by the end, you should know everything you need to know."
Technically, all the information is there. But the professor and your fellow students are not.
That means at the cost of having all the information in one go, you will have no discussion, no questions, no one challenging your interpretation of the information, no opportunity to hear other perspectives of the same idea, no feedback when you get something wrong and no chance to test your thinking against another person.
You might still learn a huge amount, but would you have the same learning experience?
In June 2026, Gartner reported that social learning boosts skills preparedness by 50%. Which raises an interesting question.
At a time when we have more information at our fingertips than at any other point in history, why do we still need one another to make it matter?
Whilst my analogy involved a professor and a pile of books, the reality is slightly different. Technology can now perform much of the information-delivery role, while the ‘books’ have multiplied into countless ways for us to consume knowledge.
That means learning can be faster, more accessible, more personalised and incredibly easy to scale.
These are very good things. Technology wouldn’t have become so commonplace in learning if they weren’t. But learning isn’t just about getting information. If it was, training companies could have spent the last few decades sending people enormous PowerPoint decks to read through instead of bothering with facilitators.
And trust us, we have never been tempted to do such a thing.
The information is of course, very important, but so is what happens around it. So that is why we always say that the choice is not one or the other, instead it is how technology and the power of people can best mix to create something incredible.
Information given to us becomes a whole lot more useful when we can connect the theory to our own reality.
This is a link that other people are brilliant at creating.
Here’s an example of this in action.
You use an AI platform to give you the key principles and components of giving difficult feedback. This is very helpful.
Laid out on your screen is everything you want to remember for your next feedback discussion. But then you discuss those principles with another person.
They know a little more about your situation. They can ask questions, understand the circumstances and help you work out what those principles might actually look like when you use them.
They might say:
“You mentioned that the person you need to give feedback to has been in the team much longer than you, and you’ve only recently started managing them. In that case, I’d think carefully about how you open the conversation. If you go straight into the issue, it could easily feel like you’re trying to establish authority. You might want to acknowledge their experience first and make it clear that the conversation is about working well together, rather than simply correcting them.”
The principles you started with haven’t changed but the context has.
What began as useful information has now been connected to the people, relationships and circumstances that actually exist in your working life.
And that can be the difference between understanding a piece of learning and knowing how to use it.
If you could go through every day knowing exactly what was going to happen, what everyone was thinking, feeling and going to do, and precisely how they would react to everything you said, life would be very easy.
And probably incredibly boring.
We can make educated guesses about how situations will unfold, but people introduce variables that are difficult to predict.
They misunderstand us.
Disagree with us.
Challenge us.
Hesitate.
React emotionally.
Ask questions we weren’t prepared for.
Which creates an important problem with learning something entirely in theory.
We can understand what the “right” thing to do is, but real life rarely follows the example quite so neatly.
Take the BIO Model for feedback conversations. You could read about it, understand each stage and know exactly how the framework is supposed to work.
Or you could learn the model, be guided through it, and then practise it with another person who reacts in a way you weren’t expecting. Suddenly, remembering the framework isn’t enough. You have to listen, adapt and decide what to say next. Work out whether to stick with your planned approach or change it completely.
You’re no longer practising recall, you’re practising judgement in real time. Responding to uncertainty is a huge part of becoming genuinely capable at something.
We hear all the time about how different we are from one another, and for good reason. Those differences create some incredibly rich opportunities to learn from each other.
When we read information by ourselves, it is very easy for our interpretation of it to become linear. We understand it through our own experiences, assumptions and way of thinking… and how are we supposed to consider an alternative interpretation if we don't even know one exists?
This is exactly what social learning exposes us to.
Imagine you're in a workshop and somebody says:
"That's interesting you say that, because I actually interpreted it completely differently."
Suddenly, you're about to enter a really valuable bit of learning.
Because what comes next isn't simply another deluge of information. You're being invited to reconsider your original assumptions, interpretation, habits and default approach.
You might question their perspective. They might question yours. That can create debate and, with it, some incredibly productive friction.
Neither person necessarily needs to have the definitive "right" answer.
The value comes from being exposed to another way of thinking and having to reflect on your own because of it. Often, some of our most valuable learning doesn't happen because somebody gives us another answer.
It happens because somebody gives us a reason to question our own.
Knowing is not the same as doing.
You can probably think of a time when you came across a genuinely valuable piece of information and then did absolutely nothing with it.
Maybe you watched a useful tutorial on YouTube. Maybe you read something that made you stop and think. Maybe you bookmarked a social post to revisit later, or promised yourself that while now wasn't the right time to act on it, some mysterious point in the future definitely would be.
By the time that future arrives, of course, the idea has usually been diluted by the hundreds of other pieces of information you've consumed since.
This is another area where human interaction can make a huge difference.
An environment where information and interaction work in tandem creates opportunities for practice, feedback, accountability and reinforcement.
Instead of simply learning what good looks like, we can try it. Someone can respond to it. We can adjust our approach, try again and make a commitment to what we'll actually do differently afterwards.
Because we're no longer learning simply for consumption… and in a world that has become a vast information banquet, consuming more isn't necessarily what we need.
We're learning to change the way we do things.
Ultimately, if you're a Learning Manager, isn't that what you want? People knowing more is great but people knowing what to do differently is everything.
I am keen to make one thing clear here… we are big believers in the advances being made in AI technology.
So, in no way is this an anti-AI argument.
Without being under duress, I will happily state that AI is exceptional for:
The argument here, and the one supported by Gartner's research, isn't that we need to remove AI from learning.
Quite the opposite actually.
AI can take care of a huge amount of the informational heavy lifting, giving people faster access to knowledge and more opportunities to learn independently. That creates an opportunity to use human interaction more deliberately.
For conversation, coaching, challenge, practice, reflection and connection.
In other words, the aim shouldn't be to use AI to remove people from learning.
It should be to use AI where it adds the most value, so that people can spend more time doing the things that only become richer when another person is involved.
The role of professional learning is changing.
We are becoming less like gatherers and more like sculptors.
There is, of course, still some gathering to do. People don’t arrive at learning experiences knowing everything already. But with the sheer amount of information now available, there is a much greater chance that they arrive having already read, watched, searched or asked something about the subject.
So our job becomes less about simply asking… How do we give people more knowledge?
And more about… How do we help sculpt that knowledge into genuine capability?
How do we give people opportunities to discuss it, question it, practise it, apply it to their own circumstances and ultimately do something differently because of it?
For us, that means creating the right environment for people to grow.
Thankfully, that’s something we’ve spent more than four decades doing.
Maybe the professor in our original analogy doesn’t need to spend every minute standing at the front of the room delivering information anymore.
Technology can help with that. It can give us the books, answer our questions, personalise what we see, refresh what we have forgotten and help us continue learning long after a workshop has finished.
But that doesn’t make the professor, or the other people in the room, redundant.
Because they were never only there to give us information.
They were there to question it with us, challenge us, share experiences, offer another perspective, let us practise, give us feedback, help us reflect, and ultimately help turn what we know into something we can actually do.
That is why, despite having more information available to us than ever before, Gartner’s research suggests social learning can increase skills preparedness by 50%.
The future of learning does not need to be a choice between technology and people. It should use technology brilliantly for the things technology does brilliantly, while deliberately creating space for the things that become better when another human being is involved.
Because access to knowledge has never been easier.
Making that knowledge matter is still something we do best together.
Thanks
Alex & The Excel Team