Categories
L&D Tools Learning Strategy

How To Build a Modern Learning and Development Team

Many corporate L&D teams are slow to evolve their philosophies.

The world’s getting psyched about AI, but 90% of L&D functions still use e-learning as their revolutionary delivery method.

We’re in the middle of a transformation that could make or break what we know as the L&D function.

This means we have to rewire not only what we do, but how we do it. That’ll lead to a new look for our local L&D teams. One shaped around providing the best service to your workforce (aka your customers).

Perhaps, the first question should be if we even call it an L&D team anymore? But I’ll leave that debate for another day.


1/ Define the Goals of a high-performing learning team

We start with our ‘why’.

Why are we doing all this and what for? Deep stuff, I know, but we need this clarity before we can continue.

Let’s keep this simple, my take is:

  1. Enable performance and build organisational capability
  2. Provide return on investment to the business
  3. Support the organisational strategy with the right skills at the right time

The ultimate goal of any workplace learning function is to enable and support people in performing at work.

We serve our audience by improving their performance.

They feel good. We feel good, and the company feels good. Plus, better performance should = more business revenue and access to improved career opportunities.

But…for the business…

Corporate L&D is about making an impact on the bottom line. There is no getting away from that. No matter how much it sucks to say.

And that can be achieved by focusing on performance.


2/ Explore the tasks and skills your L&D team needs

Before we explore roles, you need to get clear on the tasks your team does and the skills needed to do these.

To get clear on the tasks and skills you need, try out this exercise.

Tasks vs Skills assessment

Create a table like the one below.

Spend time with your team to analyse the tasks they do today and cross-reference this with the skills the team needs to do these.

TasksSkills
What tasks will your team deliver?What skills will they require to do this?
The Task + Skill pre-assessment

Use this data to shape how and what your team delivers.

If you have no clue where to start, fret not. I have a wealth of industry data to help you get clarity on the skills side.

The modern L&D professionals must-have skills

Here’s what we see from industry analysts in 2025.

1/ Redthread Research

First up is Redthread Research with their Future-proofing L&D: Developing the Right Skills report.

They asked 400 L&D pros: What skills will L&D functions need in the future? Their comments were grouped into 30 skills across the 6 skill categories you see below.

Source: Redthread Research

They revealed the 5 main skills L&D teams self-identified as:

  1. Using and applying AI
  2. Data and analysis
  3. Learning design
  4. Tech literacy (or what I call Digital Intelligence)
  5. Human skills

2/ The Josh Bersin Company

In addition, HR research analyst, Josh Bersin, offers this perspective on the evolution of L&D teams role up to the modern day.

Source: It’s Time For an AI Revolution Report 2025 | Bersin

3/ The Learning and Performance Institute

Then we have this collection of 30 skills that the Learning and Performance Institute positions as a marker of need for teams.

Source: LPI Capability Map

Where RedThread, Bersin and the LPI have a far more polished corporate approach.

I couldn’t round-up this section without including my analysis, which is more minimalistic in its tone.

Every year, I review and distil the latest industry data to identify the 7 essential skills for modern L&D pros. I use data points from industry bodies and research houses (like the above), plus I map this to data that the 5,000+ readers of my weekly newsletter share with me through annual surveys.

These, coupled with my direct work with organisation’s gives me a constant view of ‘what is actually needed’ for L&D teams to survive and thrive.

The image below shows the focus for 2024.

Fret not, the 2025 edition is coming in a few months 👀.

an image of the 7 skills modern learning and development professionals need.

Despite what you read in this section, context is king.

Your org, its culture and business goals will vary. So you need the skills that support this environment.

No matter where you land, I hope we can all agree that the modern L&D team should focus on performance instead of pushing education.


3/ How to identify the most critical roles for your L&D team

Now this, my friend, is much harder to align on in 2025.

I wrote the first edition of this guide in 2018. The only decent tool to surface content back then was Google, yet the times have changed.

We both see how all forms of artificial intelligence are reshaping how we work.

Although tasks and skills can be identified.

Who (or what) actually delivers on the tasks is not so clear-cut anymore. We’re using LLMs and AI assistants to support us with many tasks in a collaborative approach, while AI agents are quickly coming into the discussion as “do it for me” solutions.

Now, identifying who does what is going to come down to:

  • What can only a human do well to the level required
  • What can a human and AI do well together
  • Where is AI more efficient than a human

This is not set in stone as a framework.

It’s how I’m currently assessing roles that could exist in an L&D team in 2025, and I do expect that they will not all be done by a human.

What could L&D look like in 2027?

2027 is an arbitrary number, yet I don’t like to look too far into the future.

To help frame how we can think about a modern L&D team, let’s look at the makeup of workplace teams at large with the help of Microsoft.

Microsoft Work Trend Index Report 2025

I think we’ll see a mix of these over the years.

Probably not a linear progression, especially how tech moves so fast.

Taking all this into account, this is my bet on roles within the L&D team. They could be fulfilled by a human, a human with AI or just AI.

The answer all depends on the tech, tasks and the context of what you do.

And yes, you might lead a team of AI and humans, too.

Bonus: Get a 3 minute overview of that Microsoft research

The anatomy of a modern L&D function

Let’s unpack what modern learning and development could be.

While this section would historically be classified as “roles”, I think of them more as categories where several roles can exist. Maybe we should treat them as mini-departments.

Note that as we’re reshaping what an L&D function looks like in a world of AI, this will not include many traditional roles that are currently accepted as the standard.

Our goal is not to bolt on AI to the existing model.

We’re transforming!

I get that this is very anti-traditional.

While today the function focuses too much on creation, I don’t think that will be the case as we look beyond 2027. Our industry is always slow to adapt, yet in those years from now, I believe we’ll have figured out how to operate creation and curation with AI, mostly.

That’s not to say human oversight won’t be needed, because it will.

But I don’t see as many design or creator roles on the scene when 1-2 people, powered with the right tools, can do the work of a much larger team.

We’re production-focused today, yet I see that balance swinging to the more meaningful side of enablement in the long term.

This isn’t about bolting on AI but rather redesigning what you deliver, and performance enablement is the more human-centred approach to workplace learning (or whatever we call it in 2027).

3 powerful modern L&D roles to invest in

Let’s pretend you put a gun to my head and demand an answer to “what are the most impactful roles?” These would be my answers

1/ The Learning Strategist

A slight bias to this title as it’s the one I’ve given myself in my business.

When you run the show, you can do crazy stuff like this. Anyway, the strategist function is what it says on the tin, it helps define and refine the strategy for the L&D department.

It’s too easy for L&D teams to wander around doing anything and everything, while pretending it’s ‘all part of the plan’, only to have nothing to show for it all come year’s end.

That’s why you need this role.

It may not be one person, but it needs to exist.

Your strategist will:

  • Define the team’s performance and capability strategy (with some sort of CLO)
  • Determine what needs to be done, why and define the return on investment
  • Direct your team throughout the year to focus on the right things, not more things, to achieve the shared strategy.

This is the core of the role, and you can make it as big or as small as you’d like.

2/ The Learning Experience Architect

These aren’t instructional designers, and they won’t focus on building stuff in authoring tools.

Learning Experience Architects (LXA’s) focus on building the right experiences to solve real problems. Forget about creating paint by number delivery experiences.

These people will be front-facing into the business, so they’ll be focused on performance consulting to design and deliver both digital and physical experiences across the organisation (with and without AI).

Your Learning Experience Architect will:

  • Build strong relationships, trust and bring credibility to the L&D team’s work
  • Map out the real problems with stakeholders to design and deploy the best solution (and maybe that’s not an L&D one)
  • Develop the philosophy and design architecture for performance
  • Lead human experiences across physical and digital spaces

L&D is still a business of people.

No matter how much AI integrates across our workflow, people still buy from people, and your LXA’s will be a key part in influencing behaviour change.

3/ Product Manager/ Tech Architect

Naming conventions aside, you can’t have an L&D function without a dedicated focus on technology.

To do that well, you need people who have no clue about learning design, methodologies and all that noise, yet they can work with those who do to craft the best tech stack.

This role spearheads the technology stack that supports both your team and performance across the business.

Your Product Manager/Tech Architect will:

  • Research, test and identify the most useful technology for company performance initiatives
  • Craft the user experience and interface of all L&D technology across your organisation
  • Support for the design and deployment of in-house and external tools
  • Advise the L&D team on tools and infrastructure to support all team performance projects

4 shared skills every L&D team needs to have

I know the world likes to put people in boxes, but I’m not a fan of that.

Your L&D team will be full of specialists and generalists, yet they do need a shared language of skills across the function.

Let’s focus on some of the core shared skills needed:

🤖 AI Fluency

As I update this post in 2025, the last 3 years have been dominated by one word: “AI”.

We say ‘AI’, but what we mean is generative AI, which has kicked off this wider AI arms race. AI itself has been around a long time, yet generative AI, deployed in particular through Large Language Models like ChatGPT, has sparked mass attention across the space.

It would be foolish of me not to recognise this impact and how the skill of intelligently leveraging it is a must, no matter your industry.

AI in itself is not a skill, but knowing how to use it is.

A diagram illustrating how to build AI skills at work, showing a Venn diagram with two overlapping circles labeled 'Experiment & explore' and 'Structured experiences,' with 'Good Enough' in the intersection.

The term “AI Literacy” has been thrown around to describe the collection of skills and behaviours humans need to expertly leverage tools in this category. I’ve recently come to appreciate the term “AI Fluency”, introduced by the Anthropic team, instead. It sounds less education-ish, in my opinion.

No matter what you call it, we all need it.

AI Fluency looks like this:

  • Foundational understanding of how AI works (all types, not just generative)
  • The ability to determine when AI could be a useful part of a solution, and with this, when it should be used and where.
  • The capability to collaborate with AI tools to deliver an outcome (the how).
  • Understanding the opportunities and limitations of AI systems from a technical and ethical perspective

Back when I worked in a team, I was always the ‘tech’ guy.

Everyone would come to me with anything related to tech. That can’t happen with AI, it never should have with tech in general. It’s everyone’s shared responsibility to know how to use AI intelligently.

Plus, it’s a must have set of skills and behaviours for the modern day workplace.

It seems we’ll all need to be AI-native.

Resources:

  1. The AI for L&D Crash Course
  2. AI in L&D resources, frameworks and system playbooks
  3. AI tool and system tutorials

📣 Storytelling (inc marketing and sales)

I’m cheating here a bit because I’m grouping a few categories under one banner.

We’re in the business of people, which means we must be able to connect with them and influence them through change.

That means you have to be a good storyteller.

People don’t change for no reason, and I’m a big believer that good stories entertain peoplebut great stories change people.

Marketing and sales are both forms of storytelling as they serve the purpose of telling the stories of your work, people and the results.

What I’m not saying is you need to learn to be an expert marketer and salesman, but you’d be wise to understand a few techniques.

Our industry falls too often into the trap of build and they will come. Sadly, they don’t.

You can have the most amazing learning content in human existence, but if no one knows it exists, what it does and why it’s important for them ,  you’re pretty much digging your own grave.

You need the whole team to buy into this way of thinking.

It’s something we each do every day, in many ways.

You market/sell your skills to a potential employer, you market ideas to business leaders, and you even use marketing techniques to convince your crush to go on a date with you.

Resources:

  1. What L&D gets wrong about marketing, and how to do the stuff that works
  2. How to use the power of content marketing to amplify your L&D products
  3. The ultimate mini-guide to positioning your L&D products for success
  4. How to master the art of storytelling for business
  5. The rare skills L&D pros need to thrive and survive in the modern workplace

🤝 Performance consulting

Think of Performance Consulting as being the workplace detective of the L&D world.

It’s not just about throwing a training program at a problem and hoping it sticks (or not spraying and praying as I was once told).

NopeYou dig deeper.

You chat with the team, look at the data, and figure out what’s really happening. Then, you come up with a game plan that might be training, but could also be other stuff like better tools, process changes, or even a simple conversation.

The end game is making sure everyone performs better and the business scores a win.

The art of consulting seems lost in L&D teams.

We take a lot of questions, but ask few questions. Sometimes, you have to do this. The nature of your organisation can be tough to change.

Your mission is to partner with the workforce to understand their needs and propose the best solution. That might. not even be an L&D solution 😨.

Resources:

  1. Unpack why performance consulting is so important for the modern L&D pro here.
  2. Craft your skills in this area with The Art of Performance Consulting Masterclass for L&D Teams

🖥️ Digital Intelligence

We’re biological beings living in an increasingly digital world.

This skill isn’t exclusive to our industry. It’s a must for every human.

I’ve spent too much of my career watching people shy away from tech. You cannot do that anymore. I hate to sound like one of those morons on social media who say, “Do this or be left behind”. But I’m going to make an exception here.

If you don’t invest in your digital intelligence, you will be left behind.

Defining Digital Intelligence

Let’s keep this simple.

It’s about being savvy, aware and adaptable with new digital technologies. You don’t need to be an expert but you must be aware of what’s available. Be curious, always.

Our world needs more digital-savvy pros.

As the world of learning continues to be eaten up by tech. You would be wise to become fluent in the language of technology to become a valued strategic business partner.

Graphic displaying the concept of Digital Intelligence, emphasizing skills such as Tech Ability, Digital Literacy, Ethical Awareness, and Agility & Experimentation.

Even outside of L&D, a basic level of understanding of how different technologies work, connect and support one another is essential.

Not every member of your team needs to be an expert in this field, but they should have a shared understanding.

Again, some of you reading this might be resistant and suggest that a technology team should do this.

Your team will know the application for any learning tech better than anyone. They will understand how it works in practice, so keeping up to date with modern technology will always be an enhancer

This knowledge will separate your team from the industry.

If you keep up with trends, absorb what is useful, avoid what is not and apply what works for your audience. You will create a high-performing learning function.


The L&D leader

You may know it as the Head of Learning, Director of Learning, Chief Learning Officer or whatever flavour of the month title is today.

Maybe this is you right now, or it’s one of your aspirations.

Nonetheless, let’s unpack what it means to be an L&D leader in the modern era.

What does a L&D leader do?

The learning leadership role for me is one of a strategist, coach and enabler.

What I learnt quite quickly when heading up a department myself is that 80% of my tasks move to nurturing people.

I still got involved in projects from a strategic standpoint, but doing the actual project build wasn’t part of the gig. This was difficult to get my head around at first.

You’re now in charge of the compass and the map, plus your crew of L&D pros.

That doesn’t mean you stop learning.

Like your team, you will be on top of evolving trends, insights and practices which allow you to nurture a clear vision for the team to work towards.

You enable your people to do what they need to.

A modern learning leader should provide the freedom to experiment, propose new ideas, test stuff and ultimately innovate the way you work.

Of course, context, culture and organisational constraints play a big part in what you can achieve. So don’t be too hard on yourself about this.


This will evolve

As I said from the get-go, this is just how I would build a team today.

Your working

These will evolve as the world changes and the dynamics of the workplace with it. So, don’t take what I’ve shared as set in stone.

I’m sure a year from now my recommendation could look different.

Instead, use these as the foundational building blocks to the function you want to shape.


Final thoughts

When you look at your L&D team today, ask yourself:

  1. Are they providing the service your audience needs?

  2. If not, why not?

  3. Has your team been set up to deliver the service your workplace requires?

I hope this helps.

If you have any questions or comments, you can leave them below, message me directly, or find me for a chat on LinkedIn.


Before you go… 👋

If you like my writing and think “Hey, I’d like to hear more of what this guy has to say” then you’re in luck.

You can join me every Tuesday morning for more tools, templates and insights for the modern L&D pro in my weekly newsletter.

Categories
Skills

The 7 Skills L&D Teams Need For Today’s World

Updated: Aug 2024

Practising what we preach in the L&D industry is not as common as you might think.

We always talk about the latest learning philosophies, skills and experiences other people need. Rarely do I see or hear anyone talk about the modern L&D skills needed to navigate today’s world.

In a world increasingly shaped by remote work and digital platforms, the challenges for L&D teams are mounting.

Categories
Artificial intelligence

The 4 best (and free) AI courses for L&D teams

Whenever someone asks me, “How do I learn AI?” I have to pause because it feels like it’s a double-loaded question.

I understand why people want to ask me that, especially in my line of work and visibility in showcasing different use cases of artificial intelligence specifically in the realm of learning and development.

Despite this, it’s still really hard for me to give a concrete and clear answer.

It’s difficult because there are so many courses, resources, and experiences that are available to you. For the most part, they all sound the same, look the same, and tell us that they’re gonna give us the same outcome.

I’m always of the belief that there isn’t one tool, one method, or one strategy to rule them all.

And… to top it all off, the term “learn AI” is pretty ambiguous.

What I assume they mean is to understand how a generative tool, like an LLM, works and how they can work with it to get their desired results. That’s how I’ll frame this for today’s advice.

How do I know which AI course is right for me?

To help someone, you need to understand:

  • What is the context of the individual and organisation?
  • What are the constraints they may be experiencing?
  • What is their current starting point?

Without understanding all of these key inputs, it’s very hard for anyone to give you a clear answer to the question I’m constantly posed.

Now I know you’re probably reading this and thinking “oh God please stop writing so much and just tell me what I should do.”

So that is exactly what we are going to do today.

While I’m not gonna give you a clear 100% “this is the course to rule them all”, what I will do is share a selection of choices.

How I assessed these zero-cost AI courses

Okay, here’s the method to my madness with this assessment.

I’ve looked across the market at all of the courses which are tagged with ‘AI fluency’.

There are a lot of free resources on YouTube with a varying degree of quality to consider, but I’ve not included these here because that’s really based on your own taste.

This led me to focus my testing on the leading AI and tech companies building the tools we know. The idea is since they’re building these tools, they might just be a good place to learn about their capabilities.

With that focus, I spent the last six weeks completing courses from the following companies:

  • Google
  • DeepLearning.ai
  • Anthropic
  • Microsoft

That gives us four courses in total.

You’ll notice one big omission here from OpenAI.

I did visit OpenAI’s Academy to try and find some resources and courses for the general population. But I found the Academy very difficult to navigate. I didn’t really find anything beyond the ability to sign up to webinars, and rather outdated looking help articles.

That’s not to say that I dislike OpenAI at all.

I would be more than happy to add them into this once I see an improved offer and can feel confident in recommending that to you.

My recommendations for each course will include:

  1. What does the course cover?
  2. Who would it benefit the most?
  3. What will you tangibly walk away with that you can use the next day?

Now, a disclaimer for you…

The right choice for you is contextual, and depends on the 3 questions I posed in the opening section. I’ll give you my recommendations on which courses are truly worth your time in the sea of hundreds currently available.

Yet, your choice on which of the 4 is most useful to you is…well, down to you.

You can use these options for your company, too

Long-time readers will know I’m all about the value!

Since I’m not part of the AI bros club (let’s be honest my hair is far too fabulous and fashion sense too cool for that), where you get literally nothing outside of “This changes everything” comments, I’m making these recommendations not only for your development, but that of the teams you support too.

A lot of organisations are asking you to lead or play a big support role in adoption of AI.

The good news is once you’re confident with the content, you can then use it to your advantage to enable your org to be just as smart with AI (if you want to, of course).

A table summarizing the best free AI courses, including course names, levels, target audience, key takeaways, and verdicts.
The 10 second answer

The 4 AI fluency courses I’d recommend for L&D pros

Let’s get this show on the road.

This will be the only playbook you need, and I’ll do my best to keep it updated as the years roll or until my battery dies (hopefully, not anytime soon).

AI For Everyone by Deeplearning.AI

Funny name for this one because I don’t believe it’s for everyone.

Of all the courses I share today, this one is the most advanced-ish, so I’d reserve this for those who are farther down the yellow brick road of AI awareness.

Who it’s for:

This was one of the first AI courses I came across in mid-2023, although it covers much more than Generative AI. It’s taught by Andrew Ng, Founder of Coursera and Google Brain (a deep learning predecessor to the more well known Google DeepMind), and an actual computer scientist.

So yes, this guy legit knows what he’s talking about.

While I found this experience great for my inner nerd, it’s certainly only for those who want a broader understanding of everything AI, not just LLMs and everything under the generative umbrella.

Maybe one best placed for my fellow learning tech folks.

What it does well:

The course gives you everything you’d need to know about AI without being an engineer.

Talking head videos and resources are clearly explained, and easy to download for your future viewing pleasure.

Where it falls short:

Now, this only falls short depending on your context.

If you’re not an engineer or don’t care about getting deeper into an AI specialised role, then it will probably fall short for you in many areas with its overwhelm. It is stuffed with lots of info, and most is non-relevant if you just use a standard LLM every day.

I mean, it has no hands-on use of AI tools but I find it hard to see where this could be weaved in with all the Matrix level explanations.

Verdict:

  • ❌ Skip, if you’re 95% of average AI users.
  • ✅ Dive in if you’re an engineer, curious nerd or want to make a career pivot to AI as a broader category.

Google AI Essentials

Ok, let’s see what the big G has to offer.

While they came late to the useful LLM party, it can’t be denied they’re certainly a frontrunner with their abundance of tools and Godzilla-sized ecosystem.

Who it’s for:

This is pitched at the pure beginner. If you or your teams look at an LLM and have no clue what’s going on, this is the place to start.

Google’s team give you an overview of the basics that’ll give you a better standing in those workplace conversations.

What it does well:

Like I said, it’s framed perfectly for beginners, and in the traditional online course delivery we all know, but maybe don’t love. There’s plenty of focus on low-level tasks where you can collaborate with AI, and a surprisingly good overview of prompting too.

Where it falls short:

Like most choices on this list, the videos are super corny.

Even more so with these Google ones. I feel like the real humans could be avatars because the delivery is so scripted and robotic which breaks any form of immersion.

If you know the basics and are confident with generic LLM activities, you won’t get much from this.

Note: If you want to go to the next level, Google offers a paid professional certificate which bolts on a “How to build with AI” category, which is missing from all of the above. Free to access tools like Google AI Studio are criminally underrated because they’re pitched as “developer” tools but are very easy to use once you’re set up with some basic knowledge. This course provides that next step in your AI fluency journey.

Verdict:

  • ❌ Skip if you’ve been using LLMs for a few years and know the basics.
  • ✅ Dive in if you’re at beginner territory and need to build the foundations with understanding and working with LLMs

AI Fluency: Framework and Foundations by Anthropic

I know I said “this isn’t a competition with one winner”…but…

This one is my most highly recommended for everyone.

I like this one because it’s focused on “how to work and think with Gen AI and LLMs as a category”, rather than, “here’s how to use our tool”. It does a good job on prompting you (pun intended) to think about how you engage with AI and its outputs.

This is more valuable for the long game with AI. The tools will change, but investing in how you think and work with AI won’t.

Who it’s for:

It’s for anyone ready to move beyond tools and templates and start thinking with AI.

So, basically, everyone reading this.

Simply having access to AI doesn’t make you competent and fluent with AI.

Anthropic

What it does well:

The course gives you a clear fluency framework you can pick up and implement with a few tweaks. The exercises (when you find them) are practical, immersive, and teach you to think about how you’re working with AI, not just what you’re asking it.

There’s a strong breakdown of techniques that improve both AI outputs and your own thinking in the process, and I liked the encouragement to work alongside a LLM to solve the problems the course unpacks.

Where it falls short:

The UX needs work.

Exercises are buried below the fold with no direction to scroll down. I was surprised an instance of Claude wasn’t embedded for these. Why not include live demo exercises in the videos to actually model thinking with AI?

There’s also a section covering transformers, compute, and tokens. Nice to know, but for most people this isn’t the advantage the course frames it as.

Verdict:

 Take it. 

It teaches you how to work with AI, not just how to use a tool. That alone sets it apart from 90% of AI courses out there right now.

I can’t think of someone who wouldn’t benefit from it.


AI Fluency by Microsoft

I know a lot of companies are using Microsoft infrastructure, so it was a no brainer to include this one.

The ultimate assessment of ‘if this is right for you and your teams’, is if you’re using Copilot as your go-to company LLM.

Who it’s for:

The easy answer is if your organisation’s LLM of choice is Copilot and you want to make the most of it across all the popular MS apps.

What it does well:

A comprehensive walkthrough of Copilot that’s perfect for any MS powered organisation. If you’re using Microsoft tools, you can’t go wrong here.

You also get a good overview of AI Fluency (according to Microsoft) and ideas on how to amplify its principles across a team, department and org level.

Where it falls short:

It’s painfully long, and stuffed with too much unnecessary content.

When you look at it, it’s just poor design. There’s some good stuff here but it’s buried by mountains of content. It felt like the brief was ‘how much can we stuff in?’. This is the biggest problem for this one. If you’re a copilot user, it’s made for you but you’ll be going through a lot of ‘nice to know’, not ‘this is actually gonna help me do better work’ content.

I don’t like the gamified angle with experience points either.

That might be just me, yet I felt like I was in some 90’s retro game at points, and I didn’t want to be there.

Verdict:

  • ❌ Skip if you’re not using Copilot
  • ✅ Dive in if you’re using Microsoft across your organisation with Copilot but select the parts that make most sense for your work, as you don’t need everything on offer here

The elephant in the room

There is a rather oxymoronic angle to all these courses.

We’re being told as an industry that AI will change learning and education forever.

Yet, each of these companies decided to build courses around the traditional module structure with speaker videos and text based exercises.

I would have loved to see more application of AI in teaching AI.

Keep an eye out on my YouTube channel because I’m going to share how some of these could have incorporated the tools they’ve built.

You can start with this AI coach I built for one of my courses.

How I would learn about AI if I did it all over again

Graphic featuring free AI fluency resources for learning and development, including 'AI Foundations', 'Think with AI', and 'Practice with AI', with associated courses from Google and Coursera.

The biggest takeaway today might be this.

If I was starting all over again as an L&D pro with little understanding of AI, I’d:

1. Take the Google AI Essentials course to build your tech foundation

2. Take the Anthropic AI Fluency Frameworks course to build your “thinking with AI” foundation

3. Create a free Google account to access Google AI Studio, where you can test prompts, build apps and learn about agents in one place.

That’s it.

Google’s AI Essentials gives you everything you need to know about generative AI, and Anthropic’s fluency course builds on this by teaching you how to work and talk to AI without degrading your power of thought. Google’s AI Studio is the cherry on top as it lets you practice everything in one space with free access to top models.

That’s my zero-cost learning plan for you 😉.

Final thoughts

There you have it, friend.

These are my picks of the most impactful zero-cost AI courses worth checking out. Like I said, there’s no overall winner, just what works best based on your context, experience level, and goals.

I hope this helps you build your skills and enable those around you with AI too.

Let me know your thoughts on these courses, and any I missed that you think I should check out.

See you next time, human.


Before you go… 👋

If you like my writing and think “Hey, I’d like to hear more of what this guy has to say” then you’re in luck.

You can join me every Tuesday morning for more tools, templates and insights for the modern L&D pro in my weekly newsletter.

Categories
Learning Strategy

These 3 Frameworks Make Me a Better L&D Pro (and Human)

God damn AI, am I right?

It’s everything, everywhere, all at once, and kinda feels like a chokehold at times, or maybe that’s just me.

Yes, I have contributed to this myself in my domain of learning. I love to endlessly explore how modern technology can enhance and amplify human learning, but these AI bros on social media are making it hard for me to keep enjoying that.

Nonetheless, while AI is cool, sexy and is an integral part of the infrastructure of how work and learning are done, we have more to life than those two little letters.

So, I thought what better way to bring some balance to AI everything than by sharing some good old-fashioned analogue tools that any human can plug and play.

1/ How to find your purpose in the noise of life

A diagram illustrating the Japanese concept of Ikigai, depicting four overlapping circles labeled 'What you love,' 'What you are good at,' 'What the world needs,' and 'What you can be paid for,' with 'Ikigai' at the center, representing a reason for being.

There’s a lot of noise in the world.

We compare ourselves to others we shouldn’t, fear the tech takeover and continue to be glued to sensationalist headlines curated by outlets that position themselves as ‘news’.

It’s tough, and I feel it too.

Before the tidal wave of AI, ‘purpose at work’ used to be one of the top drivers in both L&D and employee engagement strategies. It’s fallen to the side in the rush to jump on the AI bandwagon, yet, it feels like a crisis of purpose could be on the rise.

If AI is threatening to do everything that we do, where does that leave me and you?

It’s for that reason that purpose both at work and in real life is having more of a moment.

A 2025 Deloitte survey across 44 countries with 24,000 participants uncovered that 89% of Gen Z and 92% of Millennial respondents class purpose as paramount to job satisfaction. We see this backed up in research from Gallup, where they discovered that employees with a strong sense of purpose are 5.6x more engaged with work than those with low purpose.

So, bottom line…purpose, meaning, or whatever you label it, is incredibly important in work and life.

The natural question becomes: ‘How do I define my purpose?’, a big question, but one only you can answer. I shared a few strategies that have worked for me in this pursuit in a recent edition of my newsletter. I’m not saying they’re ‘the way’, but they’re ‘a way’.

2/ Would you pay to use your own L&D product?

Graphic outlining five key questions for evaluating a learning and development (L&D) product as a subscription service, including topics like market fit, customer discovery, retention, human-centered design, and a reality check.

DRAMA…

But I feel like it has to be said, as it is the ultimate test in my opinion.

If you’re not prepared to cough up, let’s say, $100 a year to use your L&D product, then don’t expect your workforce to do it.

This is the same question I ask when crafting my products and services. We each vote with our time, attention and money. It’s the ultimate compliment for someone to say ‘yes’ to all three.

I can sleep at night knowing I say YES to these.

I encourage you to reflect on the same at the start of every year when everyone talks about ‘Learning Strategy’.

Don’t just focus on strategy, understand the value.

Ask your whole team, if this was a paid product, would we all pay to use it?

The answer to this is everything you need to know.

Dropbox, the cloud storage provider, was created in this way. Drew Houston, the CEO, was so frustrated with existing solutions that he built his own. He pays for it, and it turns out millions would pay for it too.

If you wouldn’t buy your own product, why should anyone else?

P.S. Get more on this and my 8 counter-intuitive questions to ask at your next L&D team strategy meeting in the members-only edition of my newsletter.

3/ The simple skill-building strategy to stay relevant

Graphic with the title 'A No-BS Approach to Skills' and three questions about skill relevance, including 'What skills are expiring?', 'What skills do I need to evolve?', and 'What are the emerging skills I can get ahead of?'

Ahh skills…why do we insist on making it so hard?

Our industry is built to support best in class skills, yet we find so many ways to make it complicated with complex terminology like oncologies, taxonomies and the latest ‘skill-based systems’, whatever that means.

I feel exhausted just reading that last sentence.

It can be simpler, it should be simpler.

Part of my rituals at the beginning of the year involves analysing my skillset, but with none of the complex tools our industry chucks at us. Instead, I use something much simpler to ensure I have the most cutting-edge skills to do what I do, and keep ahead of the pack.

This is what I do.

I grab a notebook or open a doc and do the following:

  • List my current high-level skills
  • The emerging technology, trends and challenges in my industry

Then, I ask these questions:

  1. What skills are expiring and no longer serve me and/or the world today?
  2. What skills do I need to evolve to meet the demands of today?
  3. What are the emerging skills I can get ahead of?

Yes, it’s that simple.

You can call me crazy, but I believe you could graft this onto a much larger population of a workforce, too. We’re often convinced that it all needs to be complex to be valuable, but that’s not right.

Sometimes the simple things can have the biggest impact.

Final thoughts

Ok, that’s it for this one, friend.

Expect more analogue and digital tools to keep coming your way. At the end of the day, we all know that any tool is only good in the hands of a competent human.

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


Before you go… 👋

If you like my writing and think “Hey, I’d like to hear more of what this guy has to say” then you’re in luck.

You can join me every Tuesday morning for more tools, templates and insights for the modern L&D pro in my weekly newsletter.

Categories
Skills

When did we lose the love of doing the work?

I have a confession…I like to work.

Yet, I find myself in rare company these days as so many seek to use AI to ‘do the work’ instead of collaborating to do ‘your best work’.

I think that’s gonna be a big problem and I have some thoughts on that.

Before GPT

The first time I used a generative AI tool was back in early 2023 when a colleague introduced me to a platform called GPT 2.5 from, at the time, a little known company called OpenAI.

ChatGPT didn’t exist yet.

This was it’s basic form before we experienced life through a prompt bar. The only people who were playing around at this point were nerds like me. After I got around the not so friendly interface, I saw the impact of this tech’s early potential.

At that time, I kept thinking this would be a great way to collaborate with technology to do better work.

What I couldn’t see at that point, or perhaps didn’t want to recognise, is humanities desire for instant gratification and the obsession to outsource/delegate every piece of work. The current AI marketing from all corners of the industry leans on this sense of ‘work is bad, so let AI do it for you’. I know that sounds like some weird slogan from a commercial in the 60’s.

The purpose of work

I get a great deal of value from my AI tool stack.

Perhaps I’m the weird one but my focus with AI is to help me to my best work, not outsource it.

The work, very much like learning, is where the hard stuff happens.

The ‘aha’ moments you would never have conceived without the focused effort, the seemingly unrelated events that craft a connective bridge of ideas which lead to something incredible.

My industry of workplace learning has/had a saying “Learning is the work and the work is learning” – its something like that.

It seems like too many of us have fallen out of love with doing the work.

Again, the problem isn’t AI, it’s us.

Our intentions have become skewed in the promise of an era where an artificial intelligence will do anything and everything for you. Yet, we rarely sit back to ask “Just because we can, does it mean we should?”, and even if we can, do we really want to?

Doing ‘the work’ is a big part of purpose for many.

Purpose, meaning and fulfilment is a dumpster on fire that is quickly rolling across society as we race to delegate, automate and outsource everything in the pursuit of “reclaiming time” or “Being efficient”.

We may not see it now, but its coming.

A bit of effort, struggle and focus is not bad for you, so don’t discount “Doing the work”.

“If you don’t make mistakes, you’re not working on hard enough problems and that’s a big mistake.” – Frank Wilczek


Before you go… 👋

If you like my writing and think “Hey, I’d like to hear more of what this guy has to say” then you’re in luck.

You can join me every Tuesday morning for more tools, templates and insights for the modern L&D pro in my weekly newsletter.

Categories
Artificial intelligence

3 Ways L&D Actually Adds Value In AI Adoption

L&D teams trying to and/or being responsible for total company AI adoption is a fools errand.

We both know this is stupid, yet I see too many instances of companies trying to “train” their way into successful AI adoption.

Of course, L&D teams alone aren’t going to make any organisation achieve meaningful AI adoption (however you measure that). Yet, we do have a part to play, and recognising where we can best support is critical.

So, lets explore Where L&D Can Support Meaningful AI Adoption.

There’s a ton of talk about AI adoption.

It’s odd because the validation of “adoption” has many definitions, dependent on the context and environment. The common pitfall is to measure adoption as ‘use of AI tools’ alone.

As we know, with previous technology, usage alone doesn’t mean meaningful adoption.

Setting what adoption looks like in your organisation is not a task for the L&D team.

Yet, we have an opportunity to contribute to long-term and meaningful adoption of AI across workforces as part of a wider collaboration in a community.

Let’s talk about that…

It takes more than access

Let’s go beyond the veil of bullshit we see online.

Access to an AI tool alone means nothing, and putting on one hour lunch and learns to “make people learn AI” is a comical up-skilling strategy.

If you’re a long-time reader, you’ve heard me become a broken record when I talk about what it takes to nurture meaningful and long-term change. We have much to consider with context, culture and constraints in each environment. No two workplaces are the same, that’s why the cookie-cutter “adoption frameworks” make me laugh.

They’re a good point of inspiration, but you shouldn’t follow them like a strict set of instructions.

Saying that, what is it we need to consider beyond tools?

People, Systems and Tools

As you’ve probably guessed, launching new technology and tools alone rarely leads to meaningful adoption.

There’s a bigger ecosystem at play.

We have to consider:

1/ People

Where are people at today, and how do we meet them?

Everyone will have a different understanding, maturity and receptiveness to something new and unknown. In AI’s case, we have a mix of emotions from “will this take my job” to “I want it to do all this stuff I hate doing”.

The most difficult part of a change process is people, because we’re all so unpredictable.

2/ Systems

Quite simply, how we work today.

What are the tried, tested and trusted conscious and unconscious systems we have in place? This covers both how we execute tasks and how we think about executing those tasks (deep, I know).

We each follow different types of systems in our day to day.

Understanding what these are and how AI will impact those is key to this change.

3/ Tools

The part you’re most likely more familiar with.

Here, we should consider the tools in use today alongside new ones being deployed, and how to bridge the gap in both understanding and knowing when and where to deploy them.

Too many forget the ‘when and where’ part at their own peril.

Where you can add value

For us to recognise where we can provide support and drive value, we must recognise what’s changing.

I think this framework from BCG can help recognise the moments where performance support is most needed with AI transformation.

They propose it for navigating AI transformation at scale, and through an L&D lens, I see this as a conversation point of what to map against when focusing on how best to support workforces.

It’s built on two key dimensions:

1️⃣ AI Maturity

It progresses from tool-based adoption by individuals to workflow transformation, to full, agent-led orchestration. Most organisations, and even teams within them, operate across multiple stages at once, not in a linear path.

2️⃣ Workforce Impact

This spans how tasks are executed, to what skills are needed, to how teams are structured, to how organisational culture must evolve to support new ways of working.

While this covers the wider transformation AI brings across businesses, it acts as a roadmap for L&D.

A roadmap is often what we need because it’s not uncommon for senior leaders to treat “training” (as they call it) as a boomerang that’s thrown at will when they decide people need to know stuff.

The framework above provides a view of where the friction/pain points/ problems exist in the cycle of change. That’s where we should focus.

Map it out

I mentioned before not to blindly follow frameworks, and that advice is the same here.

This view from BCG is a useful foundation for each of us to think about “where can we add value”, but it will look different for each environment.

So, I’d recommend you map out what your organisational journey looks like today.

Explore the 3 pillars of tasks, talent and teams across your business and how/where AI is starting to and might impact these. It’s here that you will uncover the friction and pain points where we can be of most service.

Some of that will be through tooling, no doubt. Yet, I feel pretty safe in saying you’ll be spending a good deal of your time navigating changes within people and systems.

Final thoughts

I’m going to leave it here for now, folks.

There’s much to say, of course, but only so much attention span I can ask you to give.

I’m thinking of expanding some of this thought into a long-form video. If that sounds like something you’d like to see, let me know.

In the meantime, some additional resources to explore on this include:


Before you go… 👋

If you like my writing and think “Hey, I’d like to hear more of what this guy has to say” then you’re in luck.

You can join me every Tuesday morning for more tools, templates and insights for the modern L&D pro in my weekly newsletter.

Categories
Artificial intelligence

How High-Performing L&D Teams Are Crafting Value With AI

I’m sure you see the endless talk at events, conferences and on social media about AI use in L&D.

Yet, there feels like very little substance to it all.

It mostly focuses on tool hype and showcasing the latest gimmicky trend infecting our feeds, which we both know has little to no value.

So, this led me down a rabbit hole of questions.

  • What are L&D teams doing with AI?
  • What are the trusted AI-powered tools?
  • Why?
  • How are they meaningfully supporting L&D work?

Since I have over 5,000 reading my Steal These Thoughts newsletter, I have the best-placed audience to answer these questions.

What follows is a high-level highlight of the findings from this audience.

About this research

Yes, it is another report about AI, and about AI in L&D.

I know there have been lots over the years already, and I’m not here to try and replicate those because that would be boring for both of us.

I’m no KPMG, PWC, BCG or any other 3 word consultancy with an army of consultants and flowing cash. What I am armed with is nearly 20 years in learning tech as both a practitioner and consultant, a large audience of L&D professionals who share their stories with me and a curious mind that wants to craft that altogether.

My mission with this report is help our industry understand the habits, behaviours and choices that L&D teams are making with AI.

Specifically we’ll unpack:

  • The tried and trusted AI tools teams are using today
  • Why they choose to use these tools
  • How they’re using these tools to meaningfully drive value

Through all of this we’ll understand a little more about how AI is being used as a co-worker across global L&D teams.

TL;DR

A quick snapshot of everything you need to know:

  • 85% of L&D professionals use AI daily
  • ChatGPT is the most popular tool among L&D teams in 2026
  • 80% of AI tools used are paid or enterprise licenses, but practitioners fill the 20% with personal AI tools, aka the “shadow stack”
  • NotebookLM is part of many practitioners “Shadow AI Stack”
  • AI provides 5 big value drivers for most L&D teams
  • There are 3 levels of AI value in L&D: Efficiency, Quality and Strategy
  • Practitioners are ditching the content factory mentality in favour of thought partnering with AI

What L&D teams are actually doing with AI today

Ok, here’s what we’re going to do.

We have 3 main questions to explore:

  1. Which AI tools do L&D pros use most often in their work?
  2. Why do they find these tools useful vs others?
  3. What value are these tools delivering for teams?

We’ll unpack each in more detail, of course, with some standout comments, use cases and surprising insights.

Then I’ll finish off our time together by exploring how all of this impacts our habits, behaviours and choices as we integrate AI as a co-worker.

1/ These are the AI tools L&D pros are using

So, who is actually using what behind both the walls of corporations and in their personal ecosystem? Perhaps few surprises here, but let’s see how we go.

For the sake of simplicity, I’ve broken the tools down into these 4 categories:

  • Large Language Models (LLMs)
  • Research & Knowledge Management
  • Content Creation
  • Specialised Tools & Integrations

👑 Who is the King/Queen of LLMs for L&D?

Ok, no surprises… it’s ChatGPT.

I mean, were you expecting anything else?

This OG tool from OpenAI took the top spot with both its enterprise and free plans for teams and practitioners. Alongside this, we had the usual competitors in Copilot from Microsoft, Gemini from Google and Claude from Anthropic.

Over 80% of responses specified using enterprise or paid versions of these tools, so read into that what you will.

🧐 Research & Knowledge Management

While LLMs are cool, they’re also a very jack of all trades or all in one solution, which isn’t bad but can sometimes mean they don’t perform as well for your niche use cases.

This came through a lot in the data.

When it comes to research, analysis and crafting a place to store all of that for evergreen access, two tools kept coming up.

They were NotebookLM and Perplexity.

Again, no surprise given they’re built specifically for these use cases, and as long-time readers of this newsletter will know, I must talk about NotebookLM every other week.

📝 Content Creation

While I loathe to focus on this use, I can’t deny it is still the number one use case for the industry in its current state.

I have nothing against that as we stand, because context is everything, and until the system is rebuilt, you can’t blame teams for trying to do more with less. That’s a much wider discussion to have outside of today.

So, outside of the LLMs we’ve covered, the tools that kept being mentioned on the content front were:

  • Synthesia
  • Elevenlabs
  • HeyGen
  • Canva

Seems like you’re all loving those AI avatars and voiceovers, and who can blame you.

They can be powerful in the right hands.

📼 Specialised Tools & Integrations

This is the area for tools that didn’t quite fit into one category or could span them all.

There was a real mix here, so I’m not going to list everything.

What I can share is on the image generation front, it seems a lot of you are loving Midjourney, and I can see a lot of use with bolted on AI-powered features in Articulate Rise, Adobe Creative Cloud and, of course, the mighty Microsoft 365.

Curious Insight: Shadow AI Stacks

While most respondents have access to a suite of AI tools at work, they’re not huge fans of them.

Many respondents reported poor performance due to instances of approved company AI tools not being on the level of the widely available paid models that many use personally. It might be no surprise that Microsoft Copilot took most of this hate.

It seems many have access to Microsofts flagship AI product, yet they’d rather not.

This has created a lot of friction, and I’m sure its not exclusive to L&D. What I found in the data is that teams will use their mandated company AI tools for very little, and instead, engage with external tools as they provide much better quality.

These external tools can be classed as “shadow stacks”, aka tools being used in secret to complete work.

Look, I’m not the police, so its not for me to tell you what to do.

Its just fascinating that some people are willing to take risks with company data with these tools in the pursuit of doing stuff faster. so, if you’re doing this, it seems you’re not alone.

2/ Why L&D Pros choose these AI tools

I’m sure you can imagine that the most obvious answer here will be: “Because these are my company-approved tools”, which is mostly spot on.

You know, I hope common sense screams don’t go leaking data to AI tools that aren’t approved by your company. Besides this main factor, we see a few more variables that affect both our purchase of tools and their use.

Ease of Use & Accessibility

Many of you use these tools because they are easy to use, accessible, and often (but not always) the only tools approved or available on work devices due to company IT/security restrictions.

Speed, Efficiency, and Time Savings

These chosen tools are highly valued for their ability to generate content, ideas, and complete tasks faster, leading to quicker work and significant time savings in summarising, analysing, and content creation.

Quality of Output and Niche Functionality

Many of you mentioned the preference for tools that provide high-quality, precise, and relevant outputs.

Specific tools were highlighted for their distinct strengths, such as Claude for high-quality writing, NotebookLM for deep content analysis and knowledge base creation, Midjourney for consistent image generation, and ElevenLabs for natural-sounding voiceovers.

Easy Integration

Integration with existing ecosystems (like MS365 or Google Workspace) and the ability to maintain context across conversations (e.g., ChatGPT’s continuous context or custom GPTs connected to company data/SharePoint) make them more effective and relevant to personal/organisational needs.

Yes, that’s a no brainer, but still good to see in writing.

Trusted and Reliable

Trust is a complicated word in the workplace AI game.

A lot of you chose tools because they are company-sanctioned, allowing for the safe use of confidential data, or because you trust the accuracy and reliability of the sources they pull from.

3/ The value these AI tools really deliver

This is the killer question, and in my eyes, the more important one than “How much money did this make us?”

Without value, we have very little, if nothing to show for all these investments. Safe to say this is the part of the data I spent most of my time scrolling through.

⏰ Reclaiming time

The most valued benefit mentioned is saving significant time by speeding up content creation (first drafts, outlines, storyboards, copy), administration, analysis, and summarising large volumes of content, freeing up time for higher-value activities.

That makes sense. After all, time is our most precious non-renewable resource; just don’t sacrifice quality for speed!

🤔 Developing ideas and structuring thoughts

AI tools serve many of you as a valuable ‘thought partner’, ‘sounding board’, and ‘sparring partner’ for brainstorming, generating new ideas, challenging assumptions, validating concepts, and looking at topics from different angles.

📈 Improving quality

The important one, if I may say so.

Many of you highly value your trusted tools for increasing the quality of work through better writing/copy, editing, adapting content for specific audiences, restructuring, and simplifying complex topics into understandable snippets.

🔎 Better Research & Analysis

Everyone goes on about being data savvy in L&D, but it ain’t easy.

AI excels here, and it seems many of you agreed. I had so many comments on the quality of support with research, data analysis, synthesising information, extracting key themes, and summarising content from multiple sources.

⚒️ Crafting New Skills

So many examples here, including creating websites, learning to code (HTML, Python, APIs), building Q&A bots, developing specialised agents, and being coached through difficult conversations with AI.

More on this, but you don’t need them right now. I’ll be sharing more as the weeks and months go on, so fret not.

“These tools save me significant time.

They help me quickly summarise content from multiple sources, recall and organise information, and search back through large transcripts, websites, and white papers. They also allow me to iterate on ideas and refine wording multiple times until the message is clear and impactful. Call note-taking and action-item extraction have been game changers, enabling me to capture details I’d never have been able to track manually.

Overall, the ability to pull together diverse perspectives, distill them, and adapt content for specific audiences has elevated the quality and effectiveness of my work vs. the level of effort and time spent.”

Survey Respondent

What this tells us about L&D teams habits, choices and behaviours to derive value from AI

Ok, so what can we learn from all this data?

This is where I see many research reports die.

They share lots of valuable data, yet provide no simplified insights on what we can take action on. Fret not, friend, I’m not going to leave you hanging.

To answer the obvious, what we do know is that most teams/pros are heavily LLM-based when it comes to AI tool usage, and the tool of choice is dominated by what’s approved in the workplace. That makes sense.

The bigger piece to talk about is what we can note from the way teams and individual pros get value from these tools.

What’s most revealing is that understanding the value proposition also provides a framework for adoption (stick with me). I see the value of AI for L&D teams as 3 levers. Some sit in one level, while others move freely across all 3 as new tools emerge. There is no one right way, and you might make a first point of entry into any of these.

From a high level, the value AI can bring to your work as of 2026 is with efficiency, quality and strategy.

Let’s unpack each of these.

Level 1: The Efficiency Engine

From an adoption standpoint, this is what I class as the gateway drug to AI for L&D teams.

Its the most common and immediate value driver for most.

It’s about speed, not necessarily quality (see next level). The tantalising prospect of saving time on the most mundane of tasks is so incredibly alluring that even the biggest AI haters will struggle not to turn their head.

This is where we sit in what I class as “The Efficiency Engine”.

Here we see the benefits of freeing up time and automating our routine tasks. Once people experience this, they often want to know what else these tools can do.

It’s both a value driver and the entry point for creating behaviour change.

And I should point out that this was not with content creation alone. Many of you mentioned the speed to summarise, analyse and find niche research.

Level 2: The Quality Amplifier

I’ve always believed that any tool is only useful in the hands of a competent user, and this is no different with AI.

AI helping you to make your best work even better is highly admirable.

I know so many are obsessed with delegating work to sit on some mythical beach somewhere. Those people aren’t going to do much in life. Instead, those who use AI to amplify what they do today will be the winners.

This is why I’ve become rather obsessed with tools like NotebookLM.

I’m not a researcher or analyst by trade, so I don’t know what I don’t know. Tools like NotebookLM and Perplexity help fill some of my own capability gaps with their features. They don’t do my work for me, but they do supplement and amplify what I can do. We’ve covered this exoskeleton-type effect by borrowing skills and capabilities from AI in a previous edition.

What’s clear is that quality counts when working with AI, and knowing which niche tools can provide that is going to be your strategic advantage.

Speaking of strategic…

Level 3: The Strategic Partner

This is where I’ve always seen the real value of AI since day 1.

I do bash on teams using AI solely for content creation a lot, yet that’s only because I know how powerful LLMs can be as strategic partners.

Even 3 years removed from the launch of ChatGPT, I still see many LLMs vastly underutilised by L&D teams in this way.

The ability to pull together diverse perspectives, distill them, and adapt content for specific audiences has elevated the quality and effectiveness of my work vs. the level of effort and time spent.

Respondent

I see strategic partnering as bringing human thought/intelligence together with AI to uncover insights, points of view and develop ideas to do our best work. This comes through clearly from the survey responses.

Many of you referenced looking beyond AI for content creation and enhancing your cognitive processes by unpacking collaborative and critical thinking tasks with AI.

Use cases that surfaced included:

  • Acting as a sounding board, especially for solo pros
  • Challenging assumptions and expanding current perspectives
  • Refining and sense-making of thoughts
  • Facilitating critical analysis of data and scenarios

So, when we talk about value and helping teams recognise this, and supporting adoption journeys, this is a useful framing to consider.

The Most Interesting Case Study: Building a New Workshop Booking Engine

We’ve covered a lot of ground with AI assisting many of you as a thought partner and automation machine, but not so much as a builder.

In the past 18 months, the market has been flooded with more AI-powered coding apps than any one person can keep up with. They come with mixed results, and as always, heavily rely on the expertise of the user.

Perhaps one of the most remarkable stories shared in the survey came from a manager who needed to build a new booking engine for their company but lacked expertise in the required coding language.

Using Cursor, an AI-powered coding tool, they were able to accomplish this task, which would have otherwise been impossible for them. This wasn’t the only mention of coding-based tools, either.

What this tells me is that more L&D pros are experimenting firsthand to uncover “How does this thing work?” They might not always achieve their goal, yet there is a lot we can each learn from these experiences.

“Cursor has aided me in coding in a language I didn’t know beforehand, in doing so developing a new booking engine for the company from scratch.”

Respondent

Final thoughts

That’s your highlights of the top insights on how high-performing L&D teams are crafting value with AI today.

Here’s a few more ways for you to get into this data:

  • customised AI assistant trained on all the survey data to guide you through the insightsand ask all of your questions. I thought there’s no better way to unpack L&D teams’ behaviours with AI than by using AI (be gentle with it, as it’s still in a testing phase, so it will do odd things at times). It’s built on Google’s Gemini Pro LLM, so it has all those sexy thinking capabilities too.
  • A one-page with a snapshot of headline insights
  • Short podcast on the top themes (Note: I tried to use AI for this, but it was hit and miss, so back to human-powered)

If you’re an L&D team that wants to learn more about this research and how you can leverage AI and tech intelligently in 2026reach out to me.

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