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.

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.

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:

• A 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 2026, reach out to me.

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