r/LearningDevelopment

One of those changes that made a bigger difference than I thought was using more real-world scenarios instead of explaining everything in detail.

When the learners were asked to make decisions, to think about situations and to see the result of those choices, the conversations became much more meaningful. They also looked to be more confident to use what they had learnt after the training.

It made me realise that knowing information and being able to use it are often two different things.

For those of you using Scenario-Based Learning, what change has made the most difference in learner confidence or participation?

I’m interested to hear what has worked in your own projects too.

Hi all,

I am part of an enterprise Learning & Development team at a global organization, and we're designing an AI upskilling strategy for our IT workforce... . I am m curious to learn what other L&D teams are doing.

Some questions I'd love your thoughts on:

How have you structured your AI learning journey (foundational vs. role-based)?

Are you focusing only on AI tools like ChatGPT, or also on topics like AI governance, prompt engineering, agentic AI, workflow redesign, and responsible AI?

How do you identify which skills different roles need?

Are you measuring success beyond course completion? If so, what metrics are you using?

What has worked well, and what would you do differently if you were starting again?

Would appreciate hearing about your experiences regardless of your sector

Hi! I’m a preschool teacher looking to transition into L&D but my problem is, idk where my skills would fit.

Some back story: I volunteer with an ATD chapter, but most of them own their own businesses so I don’t have a connection into a corporation. I’ve been applying for jobs for a while and haven’t gotten any interview requests. When I first started looking 2 years ago I was interested in instructional design or e-learning design. I was told that’s very hard to get into with AI now. I even tried applying some corporate training and learning specialist jobs and haven’t heard anything there. It’s hard trying to convince corporations on paper that I have skills to do the job. Or maybe I have to upskill more which I’m also okay with.

Can anyone lead me in the right direction? Maybe I’m unaware of some other aspects of L&D where I can use my skills to break into the industry. Is there a certification I can do? Entry level jobs that I’m not aware of?

I’ve spent most of my career working in fast-paced environments.
I genuinely love them.

But… they’ve also been exhausting.

I’m neurodivergent, and over the years I’ve realized my brain simply isn’t wired the same way.

What I’ve struggled with most hasn’t been the work itself.

It’s been the systems around the work.

The documentation.
The training.

The constant assumption that everyone processes information the same way.

I often find myself thinking, “Things don’t have to be this hard.”

Sometimes, I simply feel like things aren’t… well… clear.

Am I alone in feeling that way?

If you’ve had a similar experience, I’d genuinely love to connect and exchange perspectives.

I have a feeling I’m not the only one navigating this, and I’m curious to hear what has actually helped, especially when organizations adapted the way they designed their operations, documentation, or training.

Thanks.

AI can now help people write, summarize, research, organize ideas, create presentations, draft emails, and even prepare for interviews.

That is useful. But it also raises a question I keep thinking about:

If AI can help with many technical tasks, will life skills become even more important?

I’m talking about skills like:

clear communication
discipline
critical thinking
emotional control
decision-making
adaptability
common sense
professional behavior
knowing how to ask good questions
knowing how to work with people

A person may know how to use AI tools, but still struggle with deadlines, teamwork, honesty, confidence, responsibility, or judgment. On the other hand, someone with strong life skills may learn new tools faster because they already know how to think, adjust, and solve problems.

So maybe the real advantage in the AI era is not just knowing how to prompt a tool. Maybe it is knowing what to do with the answer, when to trust it, when to question it, and how to use it responsibly.

I’m curious what others think.

Should schools and workplaces focus more on life skills now that AI is becoming part of study and work?

And which life skill do you think will matter the most in the next few years?

The research clearly shows that sitting through sales and coaching training workshops and e-learning is highly ineffective. Learners only retain 10% of the content. The best solution is to ditch overly complex IP driven traditional solutions for Deliberate Practice with a combination of human and AI roleplayer coaches. Practica Learning is a great example of this approach.

Maybe I am being cynical here. But every LMS has slapped AI on the homepage this year, and when you actually click in, it is the same little chat bubble that summarises a paragraph for you. That is it. That is the AI.

I look at these platforms a fair bit for work, so I have sat through more of these demos than I would like to admit. A few honest impressions, take them or leave them.

Docebo has actually been at the AI thing for a while. The tagging and skills stuff is real, not just a gimmick. The core AI is bundled into the base plan now too, the authoring, the copilot, the search. It is the flashier bits, the roleplay sims and the AI video, that quietly run on extra credits you buy on top. So the bill still creeps. Funny how that goes.

Absorb is fine. The AI course creation does speed up the boring setup part. It is an assist though, you are still doing all the actual thinking.

360Learning leans into the collaborative side, which is nice if that suits how your team works. Less so if you are stuck doing dry compliance training, which a lot of us are.

Then there is Blend-ed. What they went after was AI running through the whole flow rather than one button, so generating the actual content, a tutor the learners can lean on, the admin side as well. It is built on Open edX though, so it is not the five minute, plug it in and go kind of setup. Fair warning on that.

Full disclosure, I work at Blend-ed, so I am not going to pretend I am neutral on that last one. I have tried to keep the rest fair though.

Anyway. My real question is... has anyone actually found AI in their LMS that they use every week? Not the shiny launch-day thing. The bit that genuinely stuck. Because I keep hearing huge claims, and then it feels like nobody touches it after month one.

I have learned one thing over the years, and that is that a well-written learning objective can affect the entire training process. In the past, I was often preoccupied with what information I wanted to include. Now I think more about what the learners should be able to do after the training.

That small change has made it easier to decide what content to keep and what to throw away, and what activities to add. It has also made course review and updating much simpler.

Thinking back, was there one thing you changed in the way you write learning objectives that made a big difference in your training or course design?

I’d love to hear what worked for you and how it changed your approach.

Over the last year, AI has become a major topic in nearly every learning conversation. We've started experimenting with it internally, but I'm still trying to separate genuine opportunities from hype. How are you incorporating AI into your workflows, and where do you think it's having the biggest impact?

I build a lot of content in Articulate, and I've noticed that it's easy to keep tweaking courses forever. At some point, the improvements become smaller and smaller while the time investment keeps growing. How do you decide when a course is good enough to launch?

I've been thinking about something lately that feels a bit counterintuitive. We've spent years evaluating AI voices by asking one question: "Does it sound human?" But I'm starting to wonder if that's even the right metric, especially for educational content. Human narrators add personality, emotion and variation, and we automatically assume that's better. But when I think about the technical courses I consume regularly, I'm not entirely convinced that's actually what I need.

If I'm learning about APIs, spreadsheets, cybersecurity or some other technical topic, I don't necessarily need a charismatic narrator. What I need is consistency. I need technical terms pronounced the same way every time, a predictable pace and explanations that don't suddenly speed up, slow down or emphasize random words. The weird thing is that AI voices are often surprisingly good at exactly that, not because they're more natural, but because they're less variable.

And that made me wonder if we've been optimizing for the wrong thing all along. Most conversations around AI narration are about realism. People compare voices and debate whether listeners can tell the difference between AI and humans. But maybe that's not the question we should be asking in the first place. Maybe we should be measuring comprehension instead.

After someone finishes a lesson, did they actually understand the material better? Did they retain more information? Did consistency end up being more useful than personality? The more I think about it, the more I suspect educational content might be one of those rare categories where being perfectly human isn't necessarily an advantage. Has anyone seen actual studies or run experiments around comprehension rather than naturalness?