I’ve been to a lot of conferences. I’ve moderated sessions, sat on panels and had more hallway conversations about the future of work than I can count. And lately, nearly every single one of them circles back to the same topic: artificial intelligence. What it means, what it can do and what it means for the people whose job it is to develop other people.
Here’s what I’ve noticed, though. We’re very good at convincing each other.
We gather in these rooms L&D professionals, HR practitioners, talent leaders and we nod along as someone makes a compelling case for why AI changes everything. We workshop it. We debate it. We leave energized. And then we walk back into our organizations, sit down across from a CFO or a department head and … stumble. Because the language that lands in a learning conference doesn’t necessarily land in a budget meeting. And that gap between what we know and what we can communicate is one of the most pressing challenges facing L&D right now.
We’re an Insular Bunch. And That’s a Problem.
L&D, by its nature, attracts people who are plugged into the human side of work. We care about empathy, about behavior change, about the whole person. Those instincts are what drew most of us to this field. But they also create a kind of echo chamber. When we talk about AI needing to be deployed with empathy and thoughtful leadership, everyone in the room gets it immediately. Of course. That’s obvious. Why would you even need to explain it?
But put that same conversation in front of a FinTech team, or an engineering department, or a group of operations leaders and you might get blank stares. Or worse, polite nodding that masks complete disengagement. The concepts we treat as self-evident are anything but universal. And if we can’t bridge that gap, we risk losing the very people we need to bring along.
This is something I’ve been thinking about a great deal lately. It’s one thing for us to go to these conferences and strengthen each other’s convictions. But then what? How do we take what we know back to the broader organization and make sure the right things are actually happening?
Empathy Has a Branding Problem. So Does L&D.
In a recent conversation I had with Alexandra Hyland, an experienced L&D practitioner and keynote speaker, she put it in a way that stuck with me: empathy has a branding problem. The word itself can feel soft, abstract, or even irrelevant depending on your audience. And she’s right. If we’re asking business leaders to prioritize human-centered approaches to AI adoption, we need to meet them where they are in language that’s compelling to them, not just comfortable for us.
This isn’t just about word choice. It’s about framing. It’s about understanding what your audience is trying to solve and positioning the conversation accordingly. An elevator pitch that works for a CLO won’t work for a COO. The core message might be the same, but the entry point has to be tailored.
What Alexandra described the desire for practitioners to have language they can actually use with their leaders is something I hear often. And it points to a real opportunity for L&D to play a more strategic role. What if one of our key outputs, as a function, was giving HR and L&D professionals the tools to make the case for human-centered AI adoption in terms their business leaders would actually respond to? Not just the what, but the how specific, actionable language calibrated for different audiences and industries.
The ‘Empty Mandate’ Problem
There’s another dynamic playing out inside organizations right now that we can’t ignore. Leaders issue the decree: we’re going to use AI. It’s part of the workflow. It’ll be in your performance review. AI is the future.
And then … nothing. No guidance on what that means in practice. No clarity on what problems it’s meant to solve. No answer to the very reasonable question: what exactly do you want me to do with this?
I’ve seen this play out repeatedly. The top-down mandate arrives, people wait to see if it sticks and eventually as with many technology initiatives before it some just quietly wait it out. That’s not cynicism, it’s pattern recognition. We’ve all watched initiatives arrive with fanfare and disappear without a trace. Why would AI be any different?
This is precisely where L&D has to step in. Not just to build AI literacy programs, but to help organizations answer the harder questions: What are we actually trying to achieve? What problems are we solving? What does good look like in six months? Without that scaffolding, even the most enthusiastic adopters will flounder and the skeptics will feel vindicated.
Content Is Not Learning. This Distinction Matters More Than Ever.
Here’s where I want to be direct about something, because I think it’s a conversation our industry needs to have more honestly.
AI is extraordinarily good at generating content. It can take a subject matter expert’s 400-page technical document and spin it into a structured course in a fraction of the time it used to take. Platforms are emerging every day that make it easier and faster to produce e-learning at scale. And leaders are excited. Of course they are.
But there’s a distinction that L&D professionals understand and that business leaders often don’t: content is not learning.
Capturing institutional knowledge and presenting it in a digestible format is valuable genuinely valuable. But it is not behavior change. It is not skill development. It is not the thing that moves someone from knowing something to being able to do something differently. And if we let organizations conflate the two if we allow AI-generated content to be called “training” simply because it’s faster and cheaper we are failing in our core responsibility.
I sat in on a session at a recent conference where a speaker from a major organization talked about how AI-generated content was scoring higher on effectiveness metrics than content their team had previously produced. In the same breath, he mentioned they’d let go of roughly 80% of their instructional designers. He put it plainly: I just got rid of a bunch of people who do the job that you do.
That’s a sobering moment for anyone in this room. But here’s the thing the answer isn’t to defend the status quo. It’s to make the case, clearly and compellingly, for what instructional designers actually do at their best. Not capturing content, but translating it. Not organizing information, but engineering behavior change. That’s not something AI does well. Not yet. And that distinction needs to be part of every conversation L&D is having with organizational leadership right now.
This Is Actually an Exciting Moment. Here’s Why.
I want to end on something that I genuinely believe: this is one of the most interesting times to be in learning and development in a long time.
For years, L&D operated as an order-taker. Someone upstairs decided what training was needed and we built it. The function was reactive, often undervalued and rarely seen as strategic. AI has, in a strange and somewhat ironic way, changed that dynamic. Because organizations are looking at learning leaders and asking: what should we be doing? Where should we focus? How do we prepare our people for this?
We don’t have to wait to be told anymore. We get to write the playbook.
That means getting comfortable with a few things. It means being willing to push back when AI is positioned as a time-saving silver bullet because the research doesn’t fully support that framing and because time saved is only valuable if it’s redirected intentionally. It means helping leaders understand the difference between efficiency and effectiveness. And it means showing up to those conversations with language calibrated for the audience in front of you, not the audience you left back at the conference.
We’re in a period of rapid change where nobody not the technology companies, not the consultants, not even the most forward-thinking L&D teams has it all figured out. But that’s precisely the point. The organizations that will navigate this best won’t be the ones with the most sophisticated AI tools. They’ll be the ones with people who can ask the right questions, build the right capabilities and translate between the human and the digital in ways that actually move the needle.
That sounds a lot like what L&D has always done, at its best.
So let’s go do it.
