AI in L&D: The Race for Impact
We surveyed over 600 L&D professionals from over 50 countries and conducted a series of interviews, resulting in this 54-page report that shows in detail the innovative ways AI is being put to use today by Learning and Development professionals worldwide.
Two things are clear.
The first: our respondents are using AI in increasingly sophisticated and innovative ways. The main uses of AI remain focused on content, but they go well beyond simply creating courses using a Large Language Model.
Second: the old centre of L&D, creating and distributing content, cannot hold. It is no longer a differentiator for L&D. Innovative L&D professionals recognise this, and are moving towards three new ways of operating.
There is a choice to be made, revealed in the last part of the report, in the Transformation Triangle.
From the report introduction:
This is our third annual report on L&D’s use of AI and our fourth in total since the launch of ChatGPT. Having followed L&D’s attitude to AI over that period, it is clear there has been a major change in the past 12 months.
From small things, such as the words people use to describe their use of AI, to the growing complexity of the case studies we feature in this report, everything suggests an inflexion point.
For the first time, over half the respondents to our survey now say they are actively using AI. We would surely expect this: any valuable new technology will attract more users over time. What has changed is what people are doing with it. While the greatest single use of AI remains the production of learning content, our case studies show a core of L&D practitioners going well beyond that, imagining a new role for the profession, one with a wider range and more strategic influence across the organisation.
We discuss these new approaches in detail at the end of the report, in L&D’s future in an AI world, where we describe three new and radically different ways of imagining the role of the L&D department, all made possible with AI. These possible futures are not speculation; they are based on our extensive research over three years and on talking with the people doing the work. They are happening now.
It is inspiring to consider new futures, but AI is not a neutral technology. While it allows L&D to pursue a larger role with more impact, it also erodes the foundations of our traditional work. It is now simple for anyone in the organisation to create learning content. This content looks smart and can be created several orders of magnitude faster than using traditional methods. Is it all as good as the output of the best instructional designers? No, but in many cases, it is good enough. In addition – and this is crucial – it is also far, far cheaper. We look to the work featured in our case studies and ‘snapshots’ (short case studies) to inspire us to find new ways of supporting learning at work.
This is our longest report yet. That reflects the amount of work now being done with AI. You may want to start by reading the conclusion, the final section and then the case studies and snapshots in that order. If you decide to create a summary using an AI tool, please remember that it is always worth going to the original source when you can make time for it. Here, this means taking time to read the thoughts of the people who completed the survey and those who have shared their experiences in the case studies.
We would like to thank OpenSesame, The Regis Company and Speexx for sponsoring the report.
Donald H Taylor
Eglė Vinauskaitė
