Categories
Artificial intelligence

Where People ACTUALLY Find Value From AI At Work

One of the most common questions I’m asked by teams is: Where can AI REALLY help me at work?

That’s a question I like to hear.

Many people make the mistake of jumping to tools first instead of defining a problem.

I totally understand when a transformational technology like generative AI emerges, everyone wants to try it. And that’s great! One of the best ways to discover how these tools can be useful is through experimentation.

But, what we can do is apply a decision-making framework to structure that experimentation and ensure you’re using AI effectively.

The goal? Not bloody finding more use cases to create content – stop it!

Instead, I’ll focus on saving time, improving quality, and focus on more human things that matter. I like to class this as the boring and basic but HUGELY effective applications of AI in your work.

Not everything needs to be a huge multi-workflow project that takes more time to build and maintain than the ROI it provides.

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Flowchart illustrating how AI can assist with tasks at work, including Discovery Sessions, Reports & Research, and Data Analysis, with associated tools like Read, NotebookLM, and ChatGPT.

Start with tasks

Everything starts with tasks.

We use our skills to complete tasks. With AI tools, we can identify specific areas where they can provide meaningful support.

In relation to tasks, we should ask:

  • How long do they take to complete?
  • What is the output, and does it justify the effort required?
  • What does ‘x’ task enable you to do?
  • Is it repeatable and low margin for error?

This is by no means a complete list.

If we assess these and add the lens of AI assistance, we can find potential opportunities to work smarter.

Identifying opportunities

I’m certainly not the first to propose this.

LinkedIn CEO, Ryan Roslansky proposed a similar model back in early 2023.

This idea originates from Ryan’s Redefining Work article, where he explores how AI will accelerate workforce learning and amplify the importance of skills.

Ryan suggests moving away from viewing jobs as titles, and instead, seeing them as a collection of tasks. These tasks will inevitably evolve alongside AI and other technological advancements. He recommends breaking your job down into its primary daily tasks.

You can bucket those tasks in this format:

  1. Tasks AI can fully take on for you, like summarising meeting notes or email chains.
  2. Tasks AI can help improve your work and efficiency, like help writing code or content.
  3. Tasks that require your unique skills – your people skills – like creativity and collaboration.

This sets the stage for how I currently recommend working with AI.

You could say my framework is the process before Ryan’s.

Without understanding your tasks, it’s hard to say if/how AI can support.

Let’s unpack three real-world examples from my own work where I’ve identified tasks that fall into this category, how I use AI to support me and why.

1/ AI in Meetings

I spend a significant part of my week talking to different teams and individuals about how AI and technology can solve their problems, especially in learning and development (L&D).

Many teams still think of AI primarily in terms of content creation, but there’s so much more it can do.

Most of my meetings range from 15 to 45 minutes. Like many of us, I scribble quick notes in a doc or on a notepad, but they’re often fragmented and hard to revisit later.

But I really want to focus on the conversation rather than taking detailed notes.

It’s super distracting for me when I’m like “I should write down what they just said” yet, that means breaking off mid-convo, too unnatural for me. By the time there is a break, I’ve usually forgotten what I was supposed to write down.

To solve this, I use an AI meeting assistant to join calls, record transcripts, and summarise key insights (if participants are cool with that of course – always ask!). This might seem basic, but as I always say, boring and basic is sexy because it’s efficient.

We all go to meetings, we all need notes and we all forget important insights and useful ideas.

It’s a shared pain.

Instead of spending hours sifting through notes, I can quickly review key takeaways and action points compield by my AI friend. Nothing gets lost too because I can see the original transcript if I sense AI is off base with anything. Like that one time it thought I recommended unicorns as a solution – another story for another time.

This allows me to focus on human conversations without worrying about missing important details.

It genuinely improves my life.

A few tools to explore:

  • Read AI
  • SANA (as part of their AI platform)
  • Granola (a new one I’ve been testing)

If your organisation already has approved AI tools, use those. Microsoft Teams and Google Workspace both have built-in meeting assistant functionalities. Never use anything outside your companies infrastructure.

TL;DR:

Not only does this save time, but it enables better human connection and helps keep track of discussions from weeks or months ago without relying on memory or notebook doodles (why do I always draw skulls? Question for a therapist 🤔).

You won’t find a billboard that reads “My AI meeting assistant saves me time, enables greater social connection and improves my work” but maybe it should.

2/ AI for Insights & Summaries

For most of us, reports are part of our jobs.

You might read short articles, while others (like me) deal with 250+ page research papers.

But let’s be honest – who has time to read all that in depth?

What we actually need is a way to synthesis key insights quickly while maintaining depth where it matters. Kinda like being your own Harvard Business Review.

A lot reports and research are a lot of fluff, an underrated skill is to distill, humanise and share the best bits for action with your audience. No one needs you to regurgitate what the report said.

Always ask, how do I serve my team/audience with this info?

One tool I really like for analysis is Notebook LM, I have a separate ‘How to’ video of NotebookLM, which you can check out if you’re interested.

It allows me to upload multiple documents (up to 300 🤯), analyse them together, and extract meaningful summaries.

Other AI tools help provide quick summaries, surface key insights, and even answer questions about reports and research too. NotebookLM is just my preference.

To be clear this isn’t about replacing critical thinking.

Instead, AI helps get that first layer of understanding:

  • What is this report about?
  • Why is it important?
  • How can it help me?

This approach allows me to decide which sections deserve deeper human analysis rather than blindly committing hours to reading everything.

Something I find incredibly useful as these tasks eat up about 10 hours + of my week.

TL;DR:

AI summaries prevent wasted time on unnecessary deep dives, ensuring you focus only on the most impactful parts, and become better-informed vs overwhelmed with useless insights.

3/ AI in Data Analysis

We all deal with data in some form.

You don’t have to be an analyst to benefit from AI-powered support.

Whether it’s customer trends, sales numbers, content engagement, or HR reports, AI can help surface patterns that might otherwise take hours to uncover.

You can fire up literally any tools like ChatGPT, Claude, and Copilot to ask:

  • Explain this data to me?
  • How can I use it?
  • What are the key insights and what are the actions I can explore?

Beyond data crunching, AI can even help you think more broadly by highlighting blind spots.

Again, helping you think critically in the process by working with AI to uncover:

  • What you’ve missed
  • What else could I consider (aka devils advocate)?

TL;DR:

Mostly, we look at AI to provide answers, but it can unearth better questions too. As always, the tools are only as good as the human using them.

Final Thoughts

If you’re sitting there thinking, I’d love to start using AI, but I don’t know where to begin, start with your tasks.

  • ⏰ What tasks take up the most time?
  • 🥊 Which ones require effort disproportionate to the value they create?
  • 🤖 What processes could be improved with AI-assisted support?

Never forget, AI isn’t about automating everything.

It’s about enhancing your work so you can focus on higher-value, human-centred work.

→ 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
Artificial intelligence

How AI Is Reshaping Learning and Performance at Work

AI has been promising a lot these last few years.

Previously, we looked at how Google is attempting to evolve the education system with its LearnLM model, specifically trained on learning science principles.

While I’m keen to see how that develops, I know a lot of us are in workplace L&D teams.

In my opinion, it’s less about learning at work and more about performance.

I’m sure there’ll be a few eye rolls at that sentence, but most organisations are looking to L&D to build capability and performance, not help people learn.

So, how can new tech support this?

Josh Bersin coined the phrase “learning in the flow of work” back in 2018, yet we never really had the tech to realise that vision. In 2025, it’s a different story.

Today, we’re exploring how AI is reshaping performance support at work with multimodal tools that can see and speak.

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Since generative AI tools crashed into our lives, everyone from tech bros to social media gurus has declared that it’s going to reshape education and learning.

We’ve seen AI models built specifically for education, changing how students receive support in a previous edition covering when AI is trained on learning science a few weeks back.

But what about the workplace?

Performance is bigger than learning at work

Workplace learning is a multi-billion-dollar industry, and everyone wants a slice of that pie.

Unlike traditional education, a lot of workplace learning is focused on performance. It’s getting people the right support exactly when they need it.

I’m not talking about learning deep concepts or broad skills for life. That’s a different game entirely. Performance support is about immediate problem-solving.

It’s resources, not courses.

The reality is we face a series of small – mid-level performance blockers daily

Stuff like:

  • How do I use VLOOKUP in Excel?
  • How can I convert this PowerPoint into Google Slides?

Yes, basic things, I’m aware.

These micro-challenges fill our workdays, but the answers are often buried deep in Google searches or trapped in some long-forgotten company SharePoint.

Now this might not be what you class as ‘learning’ but they stop people from performing, and if we agree that workplace learning is actually enhancing performance, then these are big problems.

The different types of multimodal generative AI models

Multimodal AI Tools are reshaping our experience

For those unfamiliar with the term “Multimodal” it just means multiple inputs and outputs.

So you can have:

  • A text input and output
  • A text input and visual output
  • An audio input and text output

We’re no longer limited to just asking AI how to do X.

It can now see, hear, and respond in real time.

Voice and vision capabilities mean we can talk to AI tools, show them what we’re working on, and get on-demand help. Instead of scrolling through pages of search results, we can (actually) solve problems in the flow of work.

How you can try this at zero cost

I’m not going to assume everyone has a paid license to top of the range AI tools.

Instead, I’ll show you how this type of performance support can work with a zero-cost tool courtesy of those folks at Google.

In Google AI Studio, you can test multimodal features for free. You can talk to the AI, show it your screen, and work together to solve problems in real-time.

With this, you can:

  1. Talk with Gemini Live.
  2. Show it what you’re working on.
  3. Share your screen for real-time support.

It’s simple.

Head over to Google AI Studio.

Select your AI model (Gemini 2.0), choose your output format (audio, text, etc.), and start collaborating.

And…of course, here’s a step-by-step video on how to do that ↓

Note: AI isn’t perfect. You, the human, still need to apply critical thinking and validate results.

AI as a Support Tool, Not a Replacement

This is where on-demand performance support is heading.

We’re not talking about replacing human expertise, but rather evolving traditional job aids, FAQs, and knowledge bases into dynamic, AI-powered conversational support systems.

We can:

  • Help employees understand new concepts.
  • Troubleshoot technical issues in real time.
  • Set up hardware and software.

Not everything needs a full-blown training course.

Sometimes, we just need an answer now.

Plus, solutions like this can only help us focus more on the human stuff that matters. I mean, do you really want to keep buying and running Excel courses for teams in 2025? I’ll leave you to ponder that.

A high-level flow of AI voice and vision capabilities

Final Thoughts

This is still in its infancy.

ChatGPT, Google Gemini, and other AI tools are already capable of vision and real-time interaction. More will follow.

The key question is: How will organisations (and you) use this?

Perhaps. it’s time, once again to rethink how we provide support with today’s technology. It’s not a case of either/or. We have an opportunity to shape how this plays out.

This is just the beginning.

→ 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

Why Digital Intelligence Is The Critical Missing Skill in The L&D Toolbox

The term “L&D” is a weird one.

Although we have a whole industry named this, it means different things to different people.

No one person is an ‘L&D’ person, because L&D is not just one thing. It’s this huge universe of skills, tasks and roles. It’s messy, like most industries. You can have many different types of careers in our industry.

That’s what makes it so unique.

You can be an ‘L&D’ person but your thing is only leadership, or instructional design, or tech – you see where I’m going with this.

Despite the beauty of this diversity, I believe we have a core set of skills that’ll benefit each of us, no matter the role. I roll these up every year into my 7 skills every L&D pro needs.

There’s one skill that hasn’t had enough attention but is more critical than ever for us all.

Digital Intelligence.

Essentially, it is the art of being savvy, aware, and adaptable to new, current and emerging digital technologies.

To thrive and survive in the modern workplace, we need to do better here.

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Digital Intelligence = an essential Human Skill

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

I don’t believe anyone can refute that.

I’d say we live and work in a 70/30 split between digital and physical/human spaces. I sense it will increase more in the former’s column than the latter.

I’ve always been a tech nerd (I guess that’s obvs). Writing my first bit of code at 12, and then building my first PC at 13, opened my eyes to the power of being a tech-infused builder.

I’ve been in love since that day.

But I could never have predicted we’d be where we are today.

Despite my passion for all things tech, and focusing on ‘tech for good’ here, I always found myself an outcast in the wider L&D space. Only a small part of the industry seems to have any clue about utilising modern-day technologies, let alone understanding them.

What I discovered in my first few years of L&D life was that very thing gave me my advantage.

I’m only here writing these words, building products and working with companies because of my curiosity about digital technologies.

Now, things are very different.

I’ve spent too much of my career watching people shy away from tech. We just cannot do that anymore. I hate to sound like one of those morons on social media that says “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.

I know, it sounds so serious, but I can’t overstate this enough.

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

Defining Digital Intelligence

I can’t be somewhat controversial and not explain my reasons.

So, let’s keep this simple.

Digital intelligence is about being savvy, aware, and adaptable with new, current and emerging digital technologies.

You don’t need to be an expert. But you do need to be aware (note the difference).

I can say with 100% confidence that my ability to adopt and adapt to new technologies has given me an edge over many of my peers. What they see as dark magic is just another sandbox for me to play in. And that only happens when you invest in yourself.

To be a high-performing modern L&D pro, you need to be digitally intelligent.

As learning and performance continues to be devoured by tech, it pays to be fluent in the language of technology.

Why is that? Because the role of L&D is evolving.

You’re no longer just an instructional designer or a trainer.

You’re a learning architect.

Today, building a cohesive learning tech stack—aka the architecture of different technology solutions—is a core skill for L&D professionals. You don’t need to be a full-blown tech guru, but you must have a baseline understanding.

This gives you credibility and the ability to be a better business partner.

And no, keeping up with tech isn’t just a nice-to-have skill, anymore.

I’m so hot on DI that I included it in my 7 skills modern L&D teams need, 5 rare skills of high-performing L&D pros and a core skill in building modern L&D teams.

So, you could say, I’m obsessed.

A map of Digital Intelligence and the skill needed to build this capability.

The 5 Components of Digital Intelligence

These aren’t set in stone, fyi.

We’ll have sub-categories across these, no doubt.

👩‍💻 Technical Proficiency

Understand the basics of the platforms you use daily. I’m talking about foundational knowledge – what tools exist, how they work, and how they integrate.

🤔 Digital Literacy

It’s never just about ‘how to use’ tools, it’s about understanding the why behind them. If you don’t know what problem you’re solving, and why x tool could help, then no tech is going to help you.

🔒 Data Protection

It terrifies me how little the average person knows about protecting their personal data. Most people are bleeding data without realising it. Don’t be one of them. Especially in this fast-moving AI era. We all let social media companies take so much, let’s not repeat those mistakes.

🫶 Ethical Awareness

I know when you drop the word ‘ethical’ it all sounds so serious. In reality, it’s more about common sense and being a good human. Every tech advancement comes at a price. Understand the ethical implications of what you do online. Copyright laws, algorithmic biases, data privacy—this stuff matters.

🏃‍♂️ Agility & Experimentation

New tools and platforms emerge daily. Move fast, but don’t break things. (Yes, I’m looking at you, early adopters who don’t read the fine print.) Don’t obsess over everything though. Pick smart and go deep on what matters.

The principles of Digital Intelligence for L&D

Ok, I know what you’re thinking…

What’s it about and how do you craft it?

I like your style.

To keep up, you’ll need:

  • A solid grasp of technology: Not necessarily as an expert, but definitely as an informed user.
  • An understanding of how different platforms interact: Because compatibility matters.
  • Knowledge of what functionalities they offer: So you can leverage the right tools.

Keeping pace with technology helps you adapt, filter what’s valuable, and drive high-performing learning functions.

Or, as the wise Bruce Lee said “Absorb what is useful, discard what is not, and add what is uniquely your own”

How to improve your Digital Intelligence

1/ Experiment

Try new tools, even if you don’t need them right now.

It’s the best way to stay ahead.

It’s one thing to read or watch me talk about tools, it’s another to see if they can be used practically in your work. I can never give you that answer, but experimentation can.

This isn’t just reserved for new tools.

You’ll be using lots of tools daily that contain many features but you only use/know of 1 or 2. So, dig a little deeper, see what’s on offer and if it can help you. Often this approach is where I find some of my most valued features to date.

2/ Stay connected

Blogs, social media and newsletters (like this one) can keep you in the loop of the latest, greatest and most useful stuff you need to know. If you stay informed, you stay sharp. I’m sure Rocky would have said something like that.

Outside of here, these are my go-to sources to keep in the loop:

  • TechCrunch
  • The Verge (tech blog, not the band, for you Brits)
  • Google Labs
  • YouTube: No one in particular, the algo does the work for me.
  • Newsletters: I read ones from BCG, McKinsey and Microsoft. For learning tech specifically, I’d recommend Emerge, as they keep track of the big tech moves in our space.

I’m not the only one hot on this 😮

Although I’ve been hot on this for over a decade, it’s only now more research houses are pushing the same agenda.

Of course, this has been spurred on by our new best friend in AI.

It’s hard to take advantage of that if you can barely work your email app. I’ve said a lot during the last few years that it’s funny seeing a huge amount of L&D people position themselves as AI strategists when those same people can’t get around their organisation’s collaboration platforms.

Yes, the kids would call that “Shots fired!”

Anyway, in the World Economic Forums 2025 Future of Jobs Report, Digital Intelligence or “Technological Literacy”, as they call it, is a top 3 priority skill by 2030.

I’d say it’s the top 3 today.

Bottom line: Get smart with tech to go far.

Final Thoughts

While L&D is a bundle of skills, they mean little without the foundations in place.

Digital Intelligence is part of that.

If you want to thrive and survive in L&D, and beyond. Get on the tech train! Make it your partner, not a problem. There is no such thing as ‘not being a tech person’, everyone is, just at different levels of maturity.

I say this because I care about giving you an honest take on the skills that matter for now and your future.

→ 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
Artificial intelligence

What are AI agents? Your Complete Beginners Guide

Right now 99% of people use straightforward AI conversational tools like ChatGPT.

That’s great.

Some even build basic AI assistants in the form of GPTs – also good.

This is just the beginning.

Lots of big companies are working with teams from Microsoft, Google, OpenAI and more on their next-gen AI agent tech (yes another confusing mouthful).

What You’ll Learn 👀
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Assistants vs Agents: What’s the difference?

Two terms you might hear techies mention with AI products are ‘AI assistants’ and ‘AI agents’.

Here’s the difference in clear, simple terms.

Let’s start with what we know – AI assistants like ChatGPT.

These are tools that help us with tasks through conversation. They can write, analyse, explain, and give suggestions based on what we ask.

AI agents take this a step further.

Instead of just helping through conversation, agents can actually complete tasks on their own. They follow instructions, use different tools, and make basic decisions to get things done.

The key difference is simple:

  • AI assistants help you with tasks
  • AI agents complete tasks for you

Both are valuable, but they serve different purposes. An assistant works with you through conversation, while an agent works independently based on your instructions.

Use this info to impress the boss at your next meeting.

I’m not going to leave you with just this, though.

As I’m a tech nerd, I’ve filmed a quick video (see below) to show how agents work with examples from Google and Salesforce – enjoy.

What can AI agents do?

Imagine you have a personal assistant who doesn’t just follow your instructions, but takes the initiative to resolve problems independently.

AI agents are like that, except they exist in the digital world.

At their core, AI agents are smart programs designed to observe their environment, make decisions, and take actions using the tools available to them.

Unlike traditional software that waits for you to give it a command, like LLMs, AI agents can think ahead, figure out what needs to be done, and act – sometimes without needing constant human input.

Think of them as a self-driving car.

Instead of waiting for a person to steer, brake, or accelerate, the car analyses traffic, makes decisions, and moves safely toward its destination.

AI agents work similarly but in a digital space, whether it’s automating workflows, analysing data, or even assisting with creative tasks.

The magic of AI agents lies in their autonomy and problem-solving abilities. Even if you don’t give them step by step instructions, they can work out the best way forward to achieve a set goal.

They do this by following set rules and past experiences to decide the best way to complete a task.

This makes them incredibly useful for businesses, customer support, research, and even personal productivity.

How AI agents work

an explainer of what an AI agent is and how it works for beginners and non-technical people.
Source: Google AI Agents White paper 2024

You can seen an example of this in the image above taken from Google’s white paper on AI agents.

In this scenario, an agent helps a user plan, find, book and check-in for a flight.

The agent has access to all the necessary tools and reasoning power to complete this on behalf of the human. You can see me build something similar for HR onboarding in this demo.

AI agents are still evolving, they’re already transforming how we interact with technology. For now, just think of them as the digital teammates working behind the scenes to get things done!

Examples of AI agents in action

AI agents are becoming part of our daily lives, wether you’re aware of it or not is another question.

They perform tasks that range from the mundane to the complex.

Two notable, and easily accessible to every one, examples are OpenAI’s “Operator” and Anthropic’s “Claude” with its “computer use” feature.

OpenAI’s Operator

Operator is an AI agent developed by OpenAI that can autonomously navigate the web to perform tasks on your behalf.

I get that sounds both odd and spooky.

It interacts with websites much like you and I would by clicking, typing, and scrolling to accomplish various objectives.

Operator can fill out forms, book travel arrangements, or even create memes by remotely interacting with a web browser (a big use case for me). This allows it to handle tasks such as purchasing groceries or filing expense reports, and streamlining processes that typically require manual input.

Just think, to never have to go searching for bananas on your local grocery app again, what a time to be alive.

Computer Use with Claude

Anthropic’s AI model, Claude, has introduced a feature known as “computer use”.

Bit of a boring name, but you gotta start somewhere,

As you’ve (probably) guessed by the name, this enables Claude to operate a computer just like we would.

Again, all the functionality that Operator has like filling out forms, ordering food, or managing emails autonomously. It has raving fans already as as Asana, Canva, and DoorDash are exploring ways to integrate this feature into their workflows.

Maybe the end of the trusty mouse and keyboard is closer than we think.

In Sum

Your AI Agent Cheatsheet 📝

  • Assistants help you with tasks, Agents do tasks for you
  • Agents works independently based on your instructions
  • The magic of AI agents lies in their autonomy and problem-solving abilities
  • They’ll be incredibly useful for businesses, customer support, research, and even personal productivity.

Agents are here as the next level of meaningful use of generative AI technology.

They serve a specific purpose in the ecosystem of AI-powered tools at our disposal. As always, if you’ve found this helpful, please consider sharing it wherever you hang out online.

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

How 4,000 L&D Teams Are Creating Meaningful Business Value in 2025

Let’s be honest, we get a lot of stick in the L&D industry.

Senior execs query what we do and how we provide value almost weekly. CFOs are chomping at the bit to cut our budgets in half, and middle managers think we’re just delivering ‘nice to have and fun experiences’ and believe they can do it better for their teams.

Who knows, maybe they’re right?

90% of the time, I believe they’re wrong.

That’s not to say I think they’re liars or anything. I just think they’re misinformed and aren’t clear on how their local L&D team is delivering value.

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The problem is we’re not so great at defining the value we bring to organisations.

If we want the narrative and perceptions to change, we need to be clear and compelling on how we deliver value every year. I understand this is a ‘captain obvious’ statement to make.

So, I thought, why not ask the talented 4,500 readers of my newsletter about the areas they’re focusing on in 2025 to drive value for their organisation.

The killer question, data collection and analysis

Since November 24, I’ve run a one-question survey through the newsletter.

It’s closed as of last week. The only question I asked was “What areas do you think L&D teams should focus on to drive value in 2025, and why?”

I’ve had thousands of responses.

Analysing this was no easy task, as you can imagine. I’ve read a lot of the comments, but I can’t read them all. So, as you might have guessed, I turned to AI for some help. Data analysis is a great use case for AI collaboration, imo.

Over a course of a week, I’ve analysed, thought deeply and categorised thousands of comments into key themes.

I’m sharing the top 3 key themes that emerged with you today, along with my thoughts and valuable comments from respondents.

These are what I look at as 3 ways L&D teams plan to deliver value for businesses in 2025.

As always, context is everything. Our industry is huge, and while I have a few thousand responses as part of this survey, it won’t represent everyone’s specific culture, context and constraints.

Take these results as a pulse of what fellow pros are doing to drive value, and perhaps, let it be a source of inspiration for you to get clear on how you’re delivering value to your business this year.

The Top 3 Focus Areas for L&D in 2025

An image showing how 4,00 L&D teams are creating meaningful business value in 2025.

1. Leverage and humanise AI for work

Generative AI is being touted as a transformative opportunity for L&D and education, particularly in realising the ultimate dream of true personalised learning.

You knew that already, but just in case.

What warmed my little black heart about the comments on AI, was how few mentioned using it for more content. I like to think my constant parading about just using AI to create more (and often sub-par) content, which delivers little value is rubbing off on you. But, I also know you’re a smart cookie, so you have more wisdom than most in the industry.

If creating more content wasn’t on the mind, what was?

I’m happy to say the majority of comments focused on people learning how to use AI intelligently themselves and supporting their workforce to do that. Plus, I discovered repeat mentions of humanising AI for work, which feels incredibly valuable.

As one respondent shared: “I’m focused on enabling the use of AI and learning where it’s relevant rather than just being a buzz word. Conversations with senior IT stakeholders to get it moving. Present business cases. Address the barriers. Get the business to commit. Help people to learn where it benefits.”

Another highlighted the smart move to support humans to hone their craft with human skills alongside expanding capabilities with AI, or as they shared: “In a world where possibilities are endless, L&D should focus on prioritising humans alongside AI.”

In sum: What came through was a strong theme that a large portion of you are focused on not just how to leverage these tools for work, but helping the human find their place too.

2. Building the right skills for the modern world

One thing I never find helpful with the usual industry drool of “x priorities for this year” is the lack of specificity.

For example, many will list ‘Upskilling and Reskilling’ as a priority, but list nothing of what skills or why. I want to avoid this in my own insights from the survey comments. So, we’re going to be specific.

As you can imagine, skills or something skill-based related was mentioned A LOT.

We’ll focus on exactly what skills were mentioned in a moment, but what I can say is the overall theme of these comments focused on helping people build the right skills to navigate the modern world, not more skills.

There was a strong sense in responses that too much time is wasted on skills that are dictated by misinformed leadership and offer little real-world impact.

Again, probably from my influence of mentioning it every other week, many responses highlighted digital skills as a priority: “Digital skills – we’re at a time where we have vast differences in basic digital skills and those gaps only seem to be getting wider.”

Of course, AI literacy was mentioned several times as a priority skill, and we shouldn’t be surprised by this.

Another two skills that crept up many times were both effective communication (heavy on the effective) and the family of metacognitive skills with critical thinking and problem solving. I can’t help but think these are being driven by what teams are seeing on the ground with behaviour change with AI tools.

As one respondent superbly put it with communication:

“In a world full of uncertainty and ambiguity our brains are desperate to find some clarity. With the rise of social media and ever shorter modes of communication (reels, tik tok), most of us are less and less able to communicate well, or distil our thoughts into comprehensive structures that can easily be explained to others. Shorter attention spans mean we also don’t listen (active listening) as well as we used to. I’ve received a lot of “apparently” different requests for learning projects/interventions. When I try to dissect what the underlying theme is, it almost always boils down to how well people communicate – whether it’s about a line manager role, commercial role, senior leadership role, technical role. Not to mention that those who are effective communicators are also the ones who benefit most from AI – those who prompt the best are essentially communicating clearly with their AI tool of choice.”

Such a wonderful insight.

And another great note from this respondent on developing those human skills: “We’re focusing on meta cognition – helping them understand how they think, being able to problem solve by recognising what they don’t know so they can fill in the gaps. Practicing curiosity and thinking creatively – by creatively I mean the ability to problem solve.”

If we’re to sum up these priority skills, it looks a little like this:

  • Digital skills
  • AI literacy
  • Human skills – thinking, communicating, problem-solving etc

A pretty strong focus, imo.

3. Aligning Learning with Business Impact

This theme should surprise no one.

It occupies many of the ‘top x priority lists’ of industry lists for as long as I’ve been in the industry. So, it seems we’re still not getting it right!

On the surface, the message here is simple: Do things that benefit your business and you’ll create value.

Of course, it’s more complicated than that (isn’t it always).

I received the most comments on this theme, so I can see the passion that burns through so many of you when it comes to this. I found this theme was multi-layered with comments on showing impact, how L&D is integrated across a business and how we define significant challenges rather than taking one leaders word for it.

One respondent put it best as they shared:

“Starting with the problem to solve and really understanding it before jumping in with solutions! There are so many examples, from standard ‘mandatory’ training, to inspirational webinars to use of AI. We need to take a HUGE step back, pause and look at what the needs really are and how best to solve them. It’s so easy to get lost in all the day-to-day ‘to dos’ but we can be so much more efficient with a little better understanding of context / problem.”

Another recommended to align with the business, you must know it well, and I couldn’t agree more: “The focus should be whatever is the top business challenge facing their organisation. This requires them to actually go learn the business of their business.“

One of my first rules of L&D onboarding is always to know how your company makes money, otherwise, you can’t really impact performance.

This comment on L&D’s organisational alignment as a means of impacting the business got me thinking too: “L&D should be integrated into the business strategy, not function as a standalone entity.”

I don’t know many companies that consider L&D as a strategic imperative. Not the function in the business itself, anyway. Almost all leaders I meet with are clear on the benefits of improved learning and performance, yet they don’t see that coming from one department like L&D. Instead, they see it as a somewhat shared focus across every team.

While that’s lovely to think of, I always believe you need some kind of sherpa to lead the way.

Standout comments

Obviously, I can’t share every single comment.

Here’s a few more I didn’t include above, but certainly provoked deep thinking while writing this analysis:

  • In a world where possibilities have multiplied thanks to AI, it has become harder to say, “We’ll do this one thing and get it right.” There’s always a temptation to experiment, to test thousands of new tools. However, sometimes the “right” approach is to focus on that one “apple pie made with grandma’s recipe” and execute it properly—respectfully, with consideration for humans, listening to them, and understanding their development concerns.
  • Being able to measure the impact L&D has in the workplace and highlight is impact to show the value. Do not be an order taker- ask what is the problem the business is trying to solve? It may not be learning 🙂
  • Address significant business problems! I often see learning getting excited by the novelty of certain solutions and losing touch with the value release / relevance of their products
  • Develop solutions to help these employees achieve their objectives, as much as possible away from training and towards whatever the most effective solution can be (software, automation, repositories, aides, etc).
  • Behaviour/ performance improvement. Why? Because if there is no improvement, then the learning is nothing more than information provided.

Final thoughts

There you have it, my fellow learning nerd.

Some food for thought from our community. While there is never only ‘one way’, I hope this gives you a view of what the industry is thinking and even inspires how you’re driving value across your business this year.

Before you go… 👋

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