The industry and the bigger picture

1. From your perspective, what is the biggest challenge facing learning and development today?

The biggest challenge for L&D teams at the moment is to mobilise thinking around the destination rather than just obsessing about the vehicle. 

What do I mean by that? 

In the latest Digital Learning Realities survey AI is seen as the number one priority for learning strategy in the year ahead – way ahead of anything else.  And whilst AI is inescapable and massively disruptive it is not an end in itself. 

What matters most is where we want to go, and the journey of how we get there and, in that respect, the biggest challenges we see across all L&D organisations are:

• Supporting organisations, managers, teams and individuals in the future of work.  
• Innovating L&D operations to deliver better and more valuable learning as well as bigger and faster outcomes across the PLASMA learning cycle - including knowing what learning really works to drive performance and in what context. 
• Influencing and mobilising stakeholders around L&D’s role in powering high-performance organisations through capability and culture building.
• Becoming intelligence led – using business and people intel to both target and deliver personalisation on the people growth that matters, but also
  evidence success and the value of L&D.
• Articulating value so you can combat relentless cost cutting.

2. What has fundamentally changed for L&D in 2026 and what are organisations still treating as if it’s business as usual?

Everything has changed and is still changing - that is the problem. Look at any aspect of the learning operation; its team, its relationship with suppliers, the expectations of what learning teams should produce and deliver. It’s all being disrupted. Everything from the basis of how we engage with stakeholders, designing learning / transformation journeys, and learning experience - how we deliver, verify and measure outcomes. 

The sand is shifting under our feet, and that makes it tough. 

That’s not to say that everyone is changing, but if anyone thinks there is such a thing as business as usual – don’t be surprised if the ground opens under your feet over the next few years. This is not a time to stand still. 

3. Where do you think the gap is currently widest between what L&D leaders want to achieve, and what they are actually able to deliver?

The biggest gaps - what is holding most L&D leaders back - are the data connections, the capabilities of platforms and their learning teams, and potentially their own imagination and strategic influencing skills. These are all interlinked. If you want to transform learning, you need a vision and the data to influence everyone around that destination. Then you need the capability to bring that to life. 

From the survey we know that only a third of teams think they have the skills needed to be successful over the next two to three years. That’s the gap and that’s what will be the limit on what they can deliver.

4. What are the best-performing L&D teams doing today that the rest of the market hasn’t caught up with yet?

The best performing teams are making connections across HR and their organisation and leaning into innovation. They are closely aligning themselves with the key business transformation initiatives and using those projects to power and fund innovation in what they do. 

That means they are experimenting and partnering around skills projects and developing learning that build skills. 

They are leveraging business metrics to evidence outcomes, but more importantly using data to diagnose needs and then starting to apply AI agents to design, build and deliver targeted learning interventions, people touchpoints, and content interactions as bridges to turn needs into measured outcomes.

It’s bleeding edge, it’s experimental, but it is here. And that combination of business alignment, purposefulness, innovation and measurement is what makes them stand out.

5. Looking across the UK and wider European L&D market, which trends are getting far more attention than they deserve, and what should leaders be paying attention to instead?

There are so many contexts and L&D operations working against different funding models and legacy platforms and business maturities, I’d prefer to emphasise not the trends, but the drivers. There is far too much followership, and not enough value-centred thinking. And whilst I can get even more excited by shiny toys than most, what is deeply and truly important to focus on is VALUE. What would deliver the most value to your stakeholders and customers – to help them deliver high performance today, and help them build even greater performance tomorrow?

All the hype has been around generative AI content, AI coaches (which often lack any context), and skills-based organisations, AI-assisted search, chatbot support. These do not matter in themselves – it’s what value they enable you to generate which needs our attention. Why what we do matters, and how much it matters, and how we’ll prove we’ve made a difference - is what we need to obsess about.  It’s something that will never go out of fashion.

 

L&D strategy and resourcing

6. What are the main forces putting pressure on L&D teams today and are organisations adapting quickly enough to keep pace with them?

Cost is possibly the biggest pressure on L&D teams today. The expectation is that AI will drive more efficiency in L&D operations and largely we are seeing that in a stagnating if not declining L&D headcount. 

If you look at the digital learning team, pressures on L&D team headcount are growing, and the 10-year trend sees a significant post-COVID-19 hangover that organisations don’t seem to be able to shake. The pressure to decrease investment in internal digital learning has grown and grown. Just short of one in five learning teams expects their budget for the internal digital team to fall.

And looking out to 2027 – we could see internal digital learning team budgets decline to such an extent that those digital learning teams looking to decrease their headcount is bigger than those expecting to increase it.  Again – it’s a decline that unprecedented in the previous 30 years. 

How do you keep pace with adapting? Some of this change is because of wider economic pressures, some of it is organisations building the tension and stresses needed to prompt innovation. 

There are no easy solutions, but it does come back to being evidence focused, intelligence led and being able to clearly articulate the true value of what you do, to people metrics, change metrics, business outcomes. It’s not an antidote to cost cutting, but it might provide some shielding.

7. Is the traditional L&D function still fit for purpose and what needs to change about the function itself?

I’d have to say that the traditional L&D function has been the walking dead for possibly the past decade. The L&D function that had a catalogue of learning content, which ran vanilla training programmes and measured its success in training hours and days has been on borrowed time for quite a while.  The one size fits all, sheep dipping learning has passed its sell-by date. 

What needs to change is L&D mindset. And my suggestion has been to follow these seven principles to get yourself fit for the future:

• Be agile – deliver value fast – iterate.
• Be intelligence and data driven – understand and focus on the best opportunities.
• Be relationship focused – don’t just point people to content, connect and build the behaviours and a learning organisation.
• Deliver the ‘Uber’-experience – do the things that delight because they really help, with the last friction, at every step of the journey.
• Energise the workforce with what you do – know it really does make a difference and people love what you do.
• Offer radical cost efficiency – not to be the cheapest but the best value for money.
• Deliver and focus on exceptional value – maximise and articulate your value add.

If you can embrace that identity as a L&D team I honestly believe you are more likely to flourish in the next few years.

8. What is the research telling us about L&D budgets and investment - and where are organisations choosing to prioritise their spending?

The past four years have been tough with negative momentum for L&D budgets all over, with 2026 continuing the trend of decline. This year most learning teams saw continued budget stagnation, but the underlying trend is for a decrease in L&D spend.

One in four L&D teams experienced budgets cuts this year. At the current rate of change, by 2027 those who have a decreased budget look like they could exceed those expecting budget growth.

The bad news about that projection is that this would push the balance of investment in learning into the negative at a time when the need for learning is growing. We are in the new normal. The promise of AI has raised expectation of teams doing more with less, and this has led to continued learning budget stagnation, at best. And given the wider economic pressures this decline shows little signs of abating. As a result, the need for L&D teams to articulate their value to counter budget cuts has never been higher.

Learning content - The long-term trend shows a 10-year decline in investment in learning content budgets, and the advent of generative AI has just accelerated that trend. We have entered a period of stagnation that shows no immediate signs of changing. In fact, the future demand trajectory doesn’t look good for digital learning content providers. This year saw the highest level of L&D teams who reported a decrease in investment in digital learning content. The bad news is that if this trend continues the market pressure this creates on suppliers is going to be significant. By 2027 we might even see the digital learning segment shrinking for the first time in three decades.

So, what’s happening with learning platforms, AI content and outsourcing?

Learning platforms - The appetite for investing in learning platforms has weakened significantly over the decade. Over that time the number of learning teams expecting to increase systems spend has fallen by nearly a third. Whilst we are far from a stagnant market, solution spend is not the vibrant space it once was. That’s unless you are buying into enhanced AI capabilities that target skills, AI content generation or that extend learning into just-in-time performance support. The challenge for learning systems is their ability to transform themselves with a fresh mentality around how they support learners and their learning journeys – and that seems to be a significant challenge for many of them.

AI content authoring - With only 4% looking to reduce their AI content authoring spend, this continues to be the growth segment for learning team budgets. And the overall trajectory over the past three years is strong with 63% expecting their investment in this area to grow. AI is seen as the silver bullet to doing more with less, which in turn is commoditising the digital learning content market. And that looks like a trend that is going to last.

Learning outsourcing - It’s difficult not to see AI as a spectre which haunts most of the trends around digital learning and learning teams – and with outsourcing that feels even more true. If outsourcing was essentially about efficiency and cost management then today AI is increasingly playing that role. And it’s hard to see outsourcing partners winning unless they are the most advanced AI users, and they can act as organisations’ ‘learning hyper-scalers’. So, internal learning teams be warned. The race for the use of AI in learning is on! It’s not only AI which is a disruptor for you, it’s those who apply it most effectively who also want your role.

9. As the role of L&D continues to evolve, what skills and capabilities will be most important for L&D professionals over the next few years?

If what has been happening in programming comes to learning teams, possibly the most significant change to L&D teams is going to be the growing role of L&D as AI orchestrators. Orchestrating and managing teams of AI agents across different stages of L&D operations. Setting up automated workflows, managing agentic outputs and monitoring the quality and impact – as a result of agents designing, authoring and delivering learning journeys. It’s already starting to appear as a role in some HR teams and that momentum is likely to come to L&D over the next few years.

In this year’s research, except for gamification and VR/AR, all areas of learning technology are themes of capability growth for learning teams.

As with our results from 2025, the message remains the same. Learning teams who fail to seamlessly connect learning across the employee experience risk becoming marginalised. That’s because in the new world of work it’s contextual data that informs the most valuable learning decisions. And that important data for learning resides in the systems of work, employee listening, performance, workforce intelligence and business results.

Real personalisation is not driven by learning preferences – it’s driven by understanding people in their work contexts. As a result, L&D teams are prioritising building out expertise in systems integration, because accessing business data sources is make or break for the learning experiences of the future. And it’s then the use of that data for adaptive personalisation, skills development and understanding the value of learning that enables learning teams to thrive – by delivering development at the right time, on the right skills, with clear measures of success.

 

AI and value 

10. What does your research reveal about where AI is genuinely changing the economics or operating model of L&D, rather than simply making existing processes faster?

The world of learning content is at a significant crossroads. The model around how it is designed and authored, and the models around how it is delivered have been the most disrupted.  The economics are embedded in speed and scale, and having AI, summarise and distil a learning programmes design has and will continue to be transformative. It is putting suppliers in a challenging space as some of their historic revenues channels have started to dry up. 

The ability of individuals to ask their own business AI to analyse their role, emails, and feedback to recommend development goals, and learning objectives – independent of any L&D function – is just one illustration of how significantly L&D’s historical operating model is on the edge. And that’s in an organic way outside of their own function. 

Data is so influential to shaping a relevant and personalised learning experience – that in many ways – L&D teams risk becoming marginalised if they cannot connect the dots between the resources they manage, and the deep understanding of people at work. If AI can monitor sales conversations and understand your pacing, use of language, ability to overcome objections and close… then it’s also perfectly placed to help each salesperson build the expertise they need to be better salespeople…  And with generative content – authoring that is the least of your worries. 

So, who can support learning is changing, the learning experience is changing, the economics of learning is changing. So where does that leave L&D? I’m not sure we really know, but if you weren’t pushing that sort of innovation as a L&D professional – then you are likely to be an economic victim of it.

11. Where are organisations currently seeing the most promising applications of AI in learning and where are they overestimating what AI can deliver?

One of the key takeaways of our wider research is the importance of looking outside of the usual L&D swim lane. The best L&D teams make connections and build strong relationships with the sources of change. Ultimately the drivers of learning are new systems, new products, new processes and ways of working, new leadership and management roles, new regulations, and new starters or redeployments.

So, as an example – strategic workforce planning – should be one of the best friends of the learning leader – helping them understand the capabilities and organisational design that’s coming over the coming year. What tasks are at risk from automation and the implications for the workforce in terms of upskilling, deskilling, reskilling or offboarding. How learning then supports that organisational change becomes and springboard to their strategic learning goals for the year ahead. 

This entire discipline of strategic workforce planning is one of the most promising applications of AI and starts the dominoes falling linked to that on career directions, trending skills and capabilities and supporting individuals navigating into the new world of work - through, for example, the use of coaching bots to support self-assessment and alignment to future work and the co-creation between bot and person of their development to get there. 

It’s emerging – but a promising use of AI to support and accelerate the kind of reflections / and manager support that serves personal development, organisational change at scale.  People talk about workforce readiness – but this is AI informing, connecting and accelerating strategic change from the roots up.

Where we might be overestimating AI’s ability might be in the willingness of people to have extended learning interactions with what is effectively a text prompt or a synthetic talking head. There is still more work to be done to prove effectiveness and that’s why tracking effectiveness and quality of outcomes and our ability to sustain them is going to be crucial moving ahead.

12. What will separate L&D teams that successfully scale AI from those that run lots of pilots but struggle to create meaningful value?

The answer is in the question. I think it comes down to focusing on the projects that matter. The ones that are important and high value. Delivering for the right stakeholders with the right problem is what getting AI right is all about. This is not a rush to adopt the most AI – it’s a race to deliver sustainable and exceptional value. If you know where those high value projects are and you’re involved – you’re on the right track.

 

Learning ecosystems and the future

13. The learning technology ecosystem has become increasingly complex. What does an effective modern learning ecosystem actually look like - and how can organisations avoid simply adding more technology?

That is probably the trickiest question to answer, because there isn’t really a generic answer. There are so many variables and contexts, and whilst it’s nice to think about a nice theoretical scenario of the perfect solution, we all know that the world is far from perfect and the devil is in the detail. Often, we don’t get to choose the landscape / ecosystem we live in – we inherit it and live within the boundaries given to us by those with more power, or just accidents in time.

If you are trying to piece together a modern learning ecosystem, I’d suggest you think through the lens of what drives performance now and what delivers transformational performance in the future. And whether that requires a tactical addition to your ecosystem or a strategic addition all depends on the time to value you need to provide and how long you need to wait for features to appear. An effective ecosystem might mean having short-term solutions – if you need to deliver high value outcomes now.

As a minimum the modern ecosystem now has MCP (Model Context Protocol) out of the box and is connectable to whatever your organisation’s core AI solution is – in its entirety – whilst ensuring the right protocols for permissions and rights to ensure data stays protected. In an AI world that is now the price of admission for most organisations.

But, would you need MCP for an adaptive learning solution which is supporting specific rehearsal and scenario practice? Not really. So, what features belong where, and how do you connect them?  If you want to get some input on innovating your ecosystem you’ll have a far better answer if we have a one-on-one conversation with our specialist analysts - Myles Runham and Fiona Leteney – to uncover that in your context.  I’ll just wrap myself in knots if we try to give a generic answer. 

14. If you could give every L&D leader one piece of advice based on this year's research, what should they focus on over the next 12 months?

My first piece of advice - independent of the research, focus on the high value opportunities. Seek them out. Get close to those projects. Bury yourself deep inside them. Be seen as essential in delivering their outcomes. And use those projects to power your innovation. 

As for advice based on this research?

The research is really broad, and we ask lots of deep-dive questions and that fuels the independent unbiased advice and guidance we provide to corporates and suppliers.  There are so many angles and insights we gather from this and all the work we put into assessing solutions and providers and the impact of AI on learning – we have a goldmine of independent unbiased understanding.  So, my second piece of advice would be – talk to us. If you want a critical friend to help you qualify what to do next - you won’t get a better conversation.