How L&D can create value: Leveraging technologies to organisational advantage

The digital opportunity

McKinsey’s report on the economic potential of generative AI reminds us that productivity enhancements could add trillions of dollars to the global economy. It also predicts that half of today’s work activities could be automated roughly a decade earlier than previously predicted.

With new jobs appearing and others disappearing, business leaders are reviewing their commitment to reskilling and upskilling the workforce.

The good news is that the modern L&D department is ideally positioned to ensure that individuals, teams and organisations are equipped, ready to learn fast and make a valuable contribution to both people and organisational priorities. And we are turning to technology to help.

Indeed, the Transformation Curve benchmark research in 2019 showed that high-performing learning organisations were investing more of their budget in a wider range of tools and technologies than their less mature peers. Our Learning at work research backs this up, finding that those L&D teams who were recognised by their business leaders for contributing business value were more likely to be using a broad range of technologies to support their learning offering.

Going back to basics

That said, the tools themselves do not create impact. It is how they are applied to the learning challenge at hand that matters. This means going back to the basic foundations of how people learn.

Increasingly, learning scientists have shown us that, to underpin personal and organisational productivity in the future, we need to understand that learning is so much more than just exposing people to knowledge.

Stella Collins, author of Neuroscience for Learning and Development, describes four elements of a learning framework that map to how our brains learn:

1. Guide: Use a scaffolded approach to help individuals be aware of what is important in the journey ahead and introduce new information in such a way that it doesn’t overwhelm or distract them.
2. Experiment: Create opportunities for individuals to consciously practise new ideas in a safe environment and find ways to connect information to real life.
3. Apply: Help individuals shift from theory to practice (a process at the heart of learning transfer), helping them create connection with the workplace and with others.
4. Retain: Remember the importance of recall, reflection and embedding learning into practice (the role of spaced repetition).

Is our go-to technology creating a gap?

Looking at the CIPD’s Learning at work research over the past four years, we see that the predominant use of technology is limited to the first area of guiding – producing content and introducing knowledge.

Figure 1 highlights that our investment in technological tools that help the way individuals learn is potentially limited.

Individuals are bombarded with content from all directions, and yet only 3–4% are using curation tools to target our learning content effectively. Few are exploring augmented and virtual reality, even though we know that individuals require opportunities to experiment and practise to shift behaviour and build skill.

When it comes to connecting individuals, and sharing and learning from each other (essential elements to help us transfer ideas back into the reality of work), we’ve seen an increase in collaboration tools, but the use of technology to digitally support and personalise coaching, or encourage peer-to-peer knowledge-sharing, has been static.

Since 2020, there has been little shift in L&D investment in the tools embedding and supporting learning in the heart of work, essential for building performance and retention. These technologies, while having the potential to turn new ideas into everyday practice and support performance at the point of need, are missing from many L&D kitbags.

Driving value through technology

In 2021, we started looking at different types of digital adopters:

• minimalists: L&D teams who use two or fewer simple content tools and administrative tools (48% of respondents)
• content advocates: L&D teams who use three or more content and administrative tools (36% of respondents)
• broad-range users: L&D teams who include three or more non-content-related tools (15% of respondents).

At the time, our analysis showed that organisations that adopt a more sophisticated, ‘broad-range’ approach to technology are moving beyond content to explore how technology can support the full learning workflow and are enabling workplace learning beyond the classroom.

So, what can the broad-range adopters teach us about driving better L&D value through technology?

Lessons from broad-range technology adopters

As shown in Figure 2, adopting a wide range of technologies creates more opportunities for L&D teams to improve their value-add.

Key lessons from these L&D teams include the following.

1. Align your strategy to organisational goals: Keep your eye on the organisation and people priorities, not just the technology. Too often, technology has been used to support the goals of the L&D department (delivering more courses for less money), rather than focusing on how we can use the tools to support organisational priorities of achieving growth targets, enhancing productivity, addressing skills shortages and improving staff retention. The CIPD’s How to choose the right technology for your business guide reminds us that successful rollout of any technology depends more on supporting people through the change than on the technology itself. Today, only 22% of L&D professionals strongly agree that we act based on our organisation and the commercial context and wider world of work.
2. Focus on performance: Employees are probably ahead of the curve when it comes to understanding their direct performance issues and using AI to find ways to address it. Marc Zao-Sanders researched how generative AI is being used ‘in the wild’ and found that, every day, individuals are using it to brainstorm ideas, explain things more simply, provide real-time help and enable critical thinking. Generative AI also provides L&D with the opportunity to analyse data more effectively to pinpoint specific performance issues. According to a recent study by Donald H Taylor and Egle Vinauskaite, 25% of a self-selecting group of L&D leaders were using generative AI to support analysis of qualitative data. One of those was James Swift, Director of Talent and Development at the international consultancy company Leyton. James worked with AI to analyse the behaviours of their top performers and distil those behaviours into eight skills. He then provided specific coaching on those skills and, within eight months, 80% of the effective practice behaviours were being exhibited in 80% of client calls.
3. Build skill, not content: Broad-range users of technology draw on their understanding of how individuals learn to inform their technology choices. Our study showed that they were more likely to enable user-generated learning and to be using chatbots and technology to support coaching and mentoring. And that was before the new version of GTP 4o (omni) was released on 13 May, which enables AI to rapidly reason and review across voice, video and text. This is potentially a game-changer, as the technology can now adapt to tutor individuals in a unique and personalised way to help them build new skills. In his new book, Brave New Words, Salman Khan shows how he has already embedded the AI tutor into the Kahn Academy, offering dynamic, specific and thoughtful encouragement and feedback to individuals as they progress from novice to master. While benchmarks on effective practice are yet to play out and, of course, we need to be mindful of the quality of training chatbots, advancements in generative AI provide a clearer route for L&D to shift GEAR – literally moving from guidance to experimentation, application and retention – more effectively.
4. Keep learning: Taylor and Vinauskaite’s study shows that generative AI provides ways for L&D to research, create, translate, manage and analyse. But it predominantly creates opportunities for L&D to keep learning. The CIPD’s advice for preparing your organisation for AI use includes recommendations to create space and time to try new things and experiment.

Conclusion

Generative AI tools, with their low barrier to entry, have the potential to change the game for L&D professionals and drive added value to both individuals and organisations. However, we need to be careful not to focus on tools centred only on producing content. Instead, we should look at how learning technologies can drive better business value by successfully embracing generative AI: keep our focus on business goals and performance outcomes, use our understanding of how people learn, master new ideas to inform our decisions – and keep learning.

What now?

• Let’s stop looking for ways to produce more content or looking at the problems that technology can solve.
• Let’s start building on the evidence of great practice and ask how technology can help us enable organisations to learn.
• Let’s continue to be digitally curious, experimenting with new ideas for ourselves to build confidence.

About the author

Laura Overton is an award-winning learning analyst with a 30-year career focused on learning innovation and business impact. For the past 10 years, Laura has been an Academic Fellow of the CIPD, playing an active role in its L&D research. She is the author of the CIPD Learning at Work 2023 report.