Felisha
Jackson

Every time a major technology shift happens, the conversation in Learning & Development follows a predictable pattern: fear first, adoption second, mastery third. We saw it with eLearning. We saw it with virtual facilitation. And now, we're seeing it with artificial intelligence.

Let me be direct. AI is not coming for your job as an instructional designer or corporate trainer. What it is doing right now is removing the low-value, time-consuming work that has always kept L&D professionals from doing their best thinking. That is worth paying attention to.

What AI is actually doing in L&D right now

Tools like Synthesia are allowing learning teams to produce professional-quality video content without a studio, a camera crew or a subject matter expert willing to sit in front of a lens. What used to take weeks of scheduling can now take hours. AI-assisted authoring tools are accelerating the content drafting process, helping designers generate first-pass scripts, learning objectives and scenario outlines in a fraction of the time it took before.

This matters because one of the biggest bottlenecks in instructional design has never been the design thinking. It's been the production. When you spend 60% of your time writing scripts and formatting content, you have 40% left for the work that actually requires your expertise: understanding the learner, diagnosing the performance gap and engineering an experience that changes behavior.

What AI still cannot do

AI cannot sit in a discovery meeting and hear the frustration in a manager's voice when they describe why their team keeps making the same mistake. It cannot read the room during a virtual facilitation session and pivot because the energy has dropped. It cannot look at a completed eLearning module and know from experience that a particular scenario won't resonate with a call center agent who handles 80 calls a day.

Context, empathy and operational understanding are not prompts you can write. They come from years of working alongside the people you design for. That is the irreplaceable core of what skilled L&D professionals bring to the work, and it becomes more valuable as AI handles more of the production layer.

The mindset shift that matters

The L&D professionals who will thrive in an AI-augmented environment are the ones who approach these tools strategically. Not every project needs AI-generated video. Not every script benefits from AI drafting. But understanding what these tools can do and where they fall short is now a core professional competency.

I've started building AI literacy into my own practice deliberately, testing tools, understanding their outputs and staying current with how they're evolving. Not because I feel threatened but because the learners I design for are going to be working alongside AI too. The least I can do is understand the landscape they're operating in.

The opportunity in front of Learning & Development right now is significant. Those willing to engage with it thoughtfully will be the ones designing the most impactful learning experiences of the next decade.

Early in my career, I sat through a training that covered everything the facilitator knew about the subject. Every policy. Every process. Every exception to every rule. It was thorough, well-organized and completely exhausting. By the end of the session, I remembered about 20% of what was covered and had to relearn the rest on the job.

That experience shaped how I think about the difference between presenting and facilitating. And it's a distinction that I believe is one of the most important — and most undervalued — in Learning & Development.

Presenting is about the information. Facilitating is about the learner.

A presenter has content to deliver. Their job is to get through it clearly, thoroughly and on time. There's nothing inherently wrong with this. Some information genuinely needs to be communicated efficiently and directly.

But a facilitator has a different goal entirely. A facilitator isn't trying to transfer information. They're trying to create the conditions under which insight happens. They're managing energy, not just content. They're watching for confusion, resistance and disengagement and responding to it in real time, not after the session ends.

The facilitator's question isn't "Did I cover everything?" It's "Did they get it? And will they be able to use it tomorrow?"

What facilitation actually looks like in practice

It looks like opening a session with a question instead of an agenda. It looks like building in moments of structured reflection so learners can connect new information to what they already know. It looks like using breakout conversations not as filler but as deliberate practice, because saying something out loud to a peer is a form of retrieval and retrieval is how memory works.

It looks like being comfortable with silence. With detours. With a learner who says something that challenges your content, because that challenge is information. It tells you where the gap is, where the resistance lives and where your design needs to do more work.

In virtual environments, facilitation requires even more intentionality. When you can't read a room through body language, you have to engineer engagement into the session itself: polls that prime thinking, chat prompts that invite reaction, breakout rooms that create accountability for participation. The tools are different. The principles are the same.

Why this matters for instructional designers specifically

If you design training that will be facilitator-led, the quality of your design is only as good as the facilitation it enables. A beautifully designed course falls flat in the hands of someone reading slides word for word. Building facilitation guides, real ones with discussion prompts, timing suggestions and guidance on how to handle common learner questions, is part of the design work. Not an afterthought.

And if you facilitate yourself, understanding this distinction changes how you show up. You stop measuring success by how much you covered. You start measuring it by what the room can do when the session is over.

That shift — from content delivery to performance enablement — is what separates training that is forgotten by Friday from learning that changes how people work.