• Event: Learning Technologies UK 25
• Date: 23 April 2025
• Speakers
  • David Perring, Chief Insights Officer, Fosway Group
  • Myles Runham, Senior Analyst for Digital Learning, Fosway Group
• Chair: Lavinia Mehedintu, Co-Founder and Learning Architect, Offbeat
• Estimated read time: 9 minutes

 

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Quick read summary

This session explored how learning teams are navigating a period of intense technological change, economic pressure and rising expectations. It examined where innovation in learning is genuinely delivering value today, where it is mostly improving efficiency, and what this means for operating models, capability and decision making in L&D.

The discussion matters now because AI is no longer experimental. It is already reshaping how learning is designed, delivered and resourced, often faster than teams can adjust their ways of working. At the same time, many learning functions still struggle to evidence impact and value.

Readers will gain a grounded view of how innovation is actually showing up across learning systems and practices, what trade offs leaders need to make, and how to focus on value rather than hype.

 

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A clear shift in what learning teams are being asked to deliver

One of the strongest signals from the session was that learning teams are experiencing a shift in organisational expectations. For the first time in Fosway’s digital learning reality research, upskilling and reskilling have overtaken compliance as the top priority.

This is more than a change in workload. It represents a change in identity. Learning is increasingly judged on its ability to support workforce performance, adaptability and competitiveness, rather than on delivery volume or coverage.

At the same time, confidence remains low. Only a small proportion of organisations believe they are very effective at supporting skills development, and even fewer feel advanced at measuring learning impact on performance and productivity. That gap between ambition and capability is where much of the current innovation pressure is coming from.

 

What being “fit for the future” really means

Rather than focusing on individual tools, the session framed innovation through the lens of learning team fitness for the future. This included several interconnected dimensions.

Learning teams need to operate with agility, prioritising rapid delivery of value over perfection. They need to be more data informed, using insight to improve relevance, accuracy and personalisation. They need to design learning as a social and relational experience, not a solitary activity. They are under pressure to radically improve cost efficiency, while still demonstrating clear business value.

Innovation, in this framing, is not about novelty. It is about whether systems and practices genuinely help teams meet these demands.

 

Where innovation is actually landing today

Across the learning technology market, most live innovation is concentrated on improving efficiency rather than reinventing learning experiences.

AI is being widely used to accelerate content creation, translation and media production. These capabilities are already good enough that many teams would struggle to justify not using them. The result is faster turnaround, lower production cost and the ability to clear long standing content backlogs.

There is also growing use of AI to support subject matter experts in creating learning themselves, something that previously struggled to scale. The combination of AI assistance and SME input is being positioned as a pragmatic response to limited budgets and rising demand.

By contrast, innovation that directly supports application, sustained behaviour change and performance in the flow of work is far less common, despite being frequently discussed. This imbalance reflects both market maturity and the economic climate.

 

Process innovation versus product innovation

A useful distinction running through the session was between process innovation and product innovation.

Process innovation focuses on speed, automation and efficiency. It helps teams do existing work faster and at lower cost. Product innovation introduces genuinely new value, new experiences or new outcomes.

The current wave of AI adoption in learning is heavily weighted towards process innovation. That is not a criticism. In a constrained environment, efficiency gains are both rational and necessary. But it does shape expectations. Organisations tend to get the learning they ask for, and right now many are asking for savings and scale before they ask for transformation.

 

The changing role of learning systems

Another emerging shift is the role of the learning platform itself. Traditional learning management systems may become less visible as primary interfaces, while conversational AI and search based tools become more common entry points to learning, knowledge and performance support.

If people increasingly turn to conversational tools for answers and guidance, the learning function’s role shifts from owning the interface to curating, governing and connecting learning content and data across the organisation.

This challenges long held assumptions about where learning “lives” and who controls it.

 

Data as the real constraint and opportunity

Throughout the discussion, data emerged as both the biggest limitation and the biggest opportunity for learning innovation.

Learning teams have historically worked with narrow and shallow data. Most meaningful signals about performance, capability and behaviour sit elsewhere in the organisation, in operational systems, feedback tools and workforce planning data.

As AI makes content easier to generate, the differentiator becomes access to the right data and the ability to connect learning activity to real outcomes. Without that, personalisation remains superficial and ROI remains hard to evidence.

 

Practical application for learning leaders

Questions leaders should be asking

• Where is AI genuinely saving time and cost today, and where is it simply adding noise?
• Which parts of our learning cycle are over invested and which are under supported?
• What data do we need access to in order to link learning to performance outcomes?
• How clear is our value story to the business, beyond activity metrics?

Signals to watch in the organisation

• Growing reliance on SMEs and internal talent to create learning at scale
• Increased scrutiny of learning spend relative to productivity and performance
• Shifts in how employees access knowledge and support, away from formal platforms

Common pitfalls

• Treating AI adoption as a technology project rather than an operating model change
• Over focusing on content efficiency while neglecting application and sustainment
• Measuring success by usage rather than by business impact

What good looks like in practice

• Learning teams acting as strategic partners, not just content providers
• Clear alignment between learning priorities and workforce strategy
• Transparent measures of value that resonate with senior stakeholders

 

Key takeaways

• Innovation in learning is currently driven more by efficiency than by new value creation.
• Upskilling and reskilling have become the dominant priority, but confidence remains low.
• AI is reshaping how learning is created and resourced, not just how it is delivered.
• Data access and integration are now more critical than learning technology features.
• Learning teams that cannot articulate value will struggle in a constrained environment.

 

Quote of the session

“Organisations get the learning they ask for.”

David Perring, Chief Insights Officer, Fosway Group

 

Final thoughts

The current wave of innovation in learning is both an opportunity and a test. Efficiency gains from AI are real and necessary, but they are not the end goal. The real challenge for learning leaders is to use this moment to reposition learning as a value driven, outcome focused capability.

Those who invest in partnerships, data and clarity of purpose will be better placed to move beyond optimisation and towards genuine workforce readiness.

 

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Speakers

David Perring, Chief Insights Officer, Fosway Group. Leads research and insight on HR, talent and learning systems across Europe.

Myles Runham, Senior Analyst for Digital Learning, Fosway Group. Focuses on digital learning strategy, platforms and vendor analysis.

Lavinia Mehedintu, Co-Founder and Learning Architect at Offbeat, specialising in modern learning design and facilitation.

 

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