David James is CLO at 360Learning, host of The Learning & Development Podcast and former Director of L&D for The Walt Disney Company.
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Henry Ford once said, “If I had asked L&D what they wanted, they would have said faster courses.”
Okay, he didn’t say that. In fact, he might not have even said the "faster horses" quote I just riffed on. Nevertheless, it’s a useful comparison of how I’ve seen learning and development vendors responding to recent advancements in generative AI.
Things have moved so quickly, it’s hard to believe the public conversation about generative AI has only really been going on since the end of November 2022. Recently, Bill Gates said developments in AI could be the biggest advancement in computing since 1980. Does he really think generative AI is more transformative than watershed moments like search engines making the internet more accessible or mobile connectivity? Wow! And if so, what does that mean for work and, in particular, learning and development programs?
Current Conversations Around AI's Impact On Work
There’s already an enormous amount of noise about how generative AI is likely to disrupt work and industries. I explored this in an earlier article, predicting more than just a little disruption to instructional design. Little did I know that, between submission and publication, my predictions would come true!
Innovations like Microsoft’s new app Copilot have shown how tech powered by generative AI will operate alongside us to make our work easier, faster and better. These technologies can act like a super smart assistant who is eager to get involved, increases our productivity and wants none of the credit for it. What a team player!
L&D has also been abuzz with discussions of how generative AI will aid in our work. However, what I’ve seen has largely (and predictably) been frustrating. For as long as digital technology has been applied to this sector, it seems mostly targeted at scaling status quo L&D products. That makes sense, right? L&D runs courses, so put those courses on computers. Considering the workforce is more remote now, let’s run our sessions wherever people are.
But what the application of generative AI has highlighted is that L&D is so focused on faster courses, we’ve lost sight of the core question that should be driving us: "Why?"
The 'Why' Behind L&D
Let’s take a step back. Why do learning and development teams exist? What are we working to achieve in our organizations? We’re here to ensure people are ready to perform, improve over time in fulfilling their role's requirements and have the right skills to perform in new, effective ways tomorrow. So instead of thinking about how to create a faster course, what if we applied our attention and energy to integrating generative AI to address these objectives as directly and as efficiently as possible? In fact, what if a course wasn't required at all?
People may wonder whether adopting generative AI technologies to shape broader L&D courses is better than an individual using the same tools to address their more specific learning needs. The short answer is that L&D teams simply can't get as granular. So would we put ourselves out of work by assuming our broad-appeal, generic courses are going to be more useful—or any use at all—compared to the same tools being in the hands of those who are closer to their need?
What’s the solution here?
AI Can Help From The Inside
One of the most exciting elements of generative AI is its ability to draw on whatever data it has access to. This will be hugely valuable to L&D (and organizations at large) when seeking to understand their people and performance and capability issues in more granular detail. For example, where is the organization losing good people? Where is there an over-reliance on external hires? Could there be a pipeline for talent to move into crucial roles?
Seen through this lens, it's clear that generative AI's usefulness to L&D teams isn't creating all-encompassing educational products to address assumed needs. After all, our role is to highlight critical points of failure where we can apply our resources to make a meaningful difference. So by combining AI with relevant, recent and now instantly accessible data, we can be much more powerful in addressing the actual needs that are causing friction to our organizations and employees.
Once L&D teams are armed with intel, they can enlist subject-matter experts to correct and contextualize the generative AI-created resources to then address specific needs. This is great because one of the most impossible tasks we ask SMEs to do is unpack everything they know when completing a task or getting the right things done. But it’s always easier to refine someone else’s draft than to begin from scratch.
With all that in hand, we can provide highly specific resources to those who need them in next to no time at all. For example, instead of a 20-minute course, we might only need to provide a few sentences of guidance that can be accessed during a short pause in work and immediately applied. It's not about creating faster courses; it's solving problems in the most efficient way possible.
In short, generative AI application isn’t about us as L&D professionals. It's about the employees who need our help to perform in unfamiliar situations and as challenges arise. We can accomplish this task better, with less risk and in far less time with generative AI. So let’s enlist that extra team member to supercharge our efforts and not get distracted with attempts to create faster courses.
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