For a long time, the direction seemed pretty clear: workplace learning was going digital. Accelerated by the pandemic, organizations moved training online because it was easier to scale, easier to track, and easier to make available to people whenever and wherever they happened to be working. eLearning became the default answer to the question, “How can we get this information to a lot of people?” There were good reasons for the shift.
But now we have AI.
AI can generate explanations, examples, scenarios, quizzes, practice activities, assessments, translations, summaries, and all sorts of other instructional content. It can respond to questions and adapt explanations to the person asking. It can produce, in a matter of minutes, the kinds of things that used to take instructional designers and developers days or weeks to create.
I'm not suggesting that eLearning is going away, or that everything should move back into a classroom. But I do wonder whether we're about to see a resurgence of live, synchronous, person-to-person learning experiences. That’s not because humans are better at delivering information, but because that's no longer necessarily the point.
I think we sometimes frame this discussion too narrowly. The question isn't whether face-to-face training is “better” than virtual training, or whether classroom learning is somehow more “human” than online learning. A virtual instructor-led session can be highly social and interactive. A classroom session can be a terrible experience if it consists of someone reading slides to a roomful of people. In my view, the more useful distinction is between content delivery and social interaction.
When people are together synchronously, something happens that is difficult to reproduce in a self-paced course. Someone asks a question that takes the discussion in an unexpected direction. A participant tells a story that makes a concept click for someone else. Two people disagree about how something should be handled. Someone realizes that the problem they thought they were trying to solve isn't actually the problem.
A good (note the emphasis) facilitator notices these things and works with them. Facilitation is not just content delivery: It's interpretation, discussion, comparison, and sense-making-- some of the things we need to gather for.
Of course, the changes brought to instruction by AI may mean the instructor's job becomes different. If AI can provide a pretty good explanation of a concept, I don't need an instructor simply to repeat that explanation. What I do need is someone who can help me think about what the concept means in my situation.
That requires a facilitator who is asking good questions, recognizing when a group is making an assumption that needs challenging, bringing different perspectives into the conversation, and knowing when to let a discussion run and when to intervene. It demands judgment. In other words, the value of the instructor may increasingly be in facilitating the work around the content rather than delivering the content itself. That's especially important for topics involving judgment and ambiguity. Think about topics like leadership, change, collaboration, AI adoption, ethics, decision-making, customer relationships: developing skill is not just simply a matter of knowing the right answer. Heck, often there isn't one.
People need opportunities to compare perspectives, test ideas, hear how others handled similar situations, and work through the messy parts. An asynchronous eLearning course can do some of that, but a good live learning experience can do a lot more.
I've been thinking about this in terms of social infrastructure: the networks, communities of practice, working-out-loud practices, and culture that help people exchange knowledge, develop expertise, build trust, and make sense of what's happening around them. We have often treated those things as peripheral to formal learning. The course is the “real” learning, and the conversations and relationships around it are nice extras. And I’ve been saying for years that in many cases we’ve got that backward.
Sure, a course can provide a foundation. It can give people common language and basic knowledge. But people often figure out what that knowledge means through interaction with other people.
They ask, “How does this work here?”
They compare experiences, discover exceptions, tell stories, see how someone else deals with the same problem, develop relationships that make it easier to ask for help later. That’s learning, too. A good live learning event can become a piece of that social infrastructure.
AI doesn't have to be the enemy of instructor-led learning. It could make it better. Imagine that participants use AI before a session to learn the basic concepts, identify what they don't understand, generate examples, or work through some initial practice. They arrive at the live session with the foundational information already available to them. Then, in the session, instead of spending three hours delivering content, the instructor can spend that time working with the group on the harder stuff. That time could be spent working through real situations, competing perspectives, ambiguous problems. As an instructor I’m always interested to hear what happened when people actually tried to apply an idea. And the fact is: Live training is often the place that surfaces organization-specific issues that generic courses don’t anticipate.
AI can still be there. It can provide examples, retrieve information, generate scenarios, summarize discussions, and help people explore alternatives, but the humans are doing something together that the technology isn't doing for them: They're figuring something out.
L&D folks spend a lot of time explaining this distinction. (Warning: I bet that’s about to get worse.) We may need fewer courses designed primarily to move information from one place to another. We may need fewer hours of people sitting through content that could have been explained more efficiently by AI. That doesn't mean, though, that we need fewer opportunities to learn. We may need more opportunities for people to gather, practice, question, compare, experiment, and make sense of difficult situations together. So AI taking on more of the information work may give humans more room to do the interpretive and social work.
The implications for L&D are clear: If our value is primarily that we can efficiently create courses, AI has a pretty compelling alternative. But if our job is to help people and organizations develop the capacity to understand what's happening, make good decisions, build expertise, and adapt, the opportunity is much bigger. AI has made information cheap and plentiful. And when information is abundant, there may be renewed value in something that has always been harder to scale: people learning with other people.
If this resonates, it's time to talk. Learn how InSync designs live learning experiences that go beyond content delivery.