What If L&D's Biggest AI Opportunity Isn't About L&D at All?

Content

What if the most important thing learning and development professionals can do with AI isn't use it to write faster, build better courses, or prototype content more efficiently, but to help the rest of the organization actually implement it?

What if the most important thing learning and development professionals can do with AI isn't use it to write faster, build better courses, or prototype content more efficiently, but to help the rest of the organization actually implement it?

Content

Most of the L&D conversation about AI has been pointed inward. How do we use AI in our own work? How do we build AI literacy into our programs? How do we stay current? Those are legitimate questions, and none of them is wrong. But they may be smaller than the moment we're actually in.

Most of the L&D conversation about AI has been pointed inward. How do we use AI in our own work? How do we build AI literacy into our programs? How do we stay current? Those are legitimate questions, and none of them is wrong. But they may be smaller than the moment we're actually in.

Content

Right now, across most organizations, AI implementation is happening in a fog. Projects are launching without clear ownership. Workflows are changing faster than anyone has mapped them. Employees are confused, skeptical, or quietly using AI tools in ways nobody has sanctioned. And the people leading these efforts—IT, operations, sometimes a newly created AI function—are doing their best, but they are missing something. They lack the skills that L&D professionals have been developing throughout their careers.

Right now, across most organizations, AI implementation is happening in a fog. Projects are launching without clear ownership. Workflows are changing faster than anyone has mapped them. Employees are confused, skeptical, or quietly using AI tools in ways nobody has sanctioned. And the people leading these efforts—IT, operations, sometimes a newly created AI function—are doing their best, but they are missing something. They lack the skills that L&D professionals have been developing throughout their careers.

Content

That's the reframe. Not "how does AI help L&D?" but "how does L&D help AI adoption?"

That's the reframe. Not "how does AI help L&D?" but "how does L&D help AI adoption?"

Content

Consider what it actually takes to implement AI well inside an organization:

Consider what it actually takes to implement AI well inside an organization:

• Content

  Someone needs to understand how work actually gets done, at the level of individual tasks and decisions, before any tool can be meaningfully integrated into it.

  Someone needs to understand how work actually gets done, at the level of individual tasks and decisions, before any tool can be meaningfully integrated into it.

• Content

  Someone needs to identify which employees are ready, which are resistant, and which are simply overwhelmed—and then design experiences that meet each group where they are.

  Someone needs to identify which employees are ready, which are resistant, and which are simply overwhelmed—and then design experiences that meet each group where they are.

• Content

  Someone needs to translate what the technology can and can't do into language that a skeptical manager on the plant floor or a nervous team lead in customer service can actually absorb and act on.

  Someone needs to translate what the technology can and can't do into language that a skeptical manager on the plant floor or a nervous team lead in customer service can actually absorb and act on.

• Content

  Someone needs to build the performance support resources that help people use new tools correctly in the moments that matter, not just remember what they learned in a two-hour session three weeks ago.

  Someone needs to build the performance support resources that help people use new tools correctly in the moments that matter, not just remember what they learned in a two-hour session three weeks ago.

• Content

  Someone needs to measure whether any of this is actually changing behavior, not just generating completion data.

  Someone needs to measure whether any of this is actually changing behavior, not just generating completion data.

Content

That someone is us. It has been us for a long time.

That someone is us. It has been us for a long time.

Content

Think about what L&D professionals do on an ordinary day:

Think about what L&D professionals do on an ordinary day:

• Content

  We interview subject matter experts to understand the gap between what people know and what they need to do.

  We interview subject matter experts to understand the gap between what people know and what they need to do.

• Content

  We map workflows to identify where skills break down.

  We map workflows to identify where skills break down.

• Content

  We facilitate groups of people through difficult conversations about change.

  We facilitate groups of people through difficult conversations about change.

• Content

  We design for the person who doesn't want to be there, who is skeptical of the whole endeavor, who has seventeen other priorities.

  We design for the person who doesn't want to be there, who is skeptical of the whole endeavor, who has seventeen other priorities.

• Content

  We build resources that are genuinely useful within the workflow, not just comprehensive or well-intentioned.

  We build resources that are genuinely useful within the workflow, not just comprehensive or well-intentioned.

• Content

  We push back when someone says "just train them" because we understand that training alone rarely moves the needle.

  We push back when someone says "just train them" because we understand that training alone rarely moves the needle.

Content

None of those skills were developed for AI. But every single one of them is exactly what AI adoption requires—and most of the people currently leading AI implementation efforts don't have them.

None of those skills were developed for AI. But every single one of them is exactly what AI adoption requires—and most of the people currently leading AI implementation efforts don't have them.

Content

There is also something less tangible but equally important: the relationships L&D professionals have built across an organization. We have worked with people at every level, in every function, in moments when they were vulnerable enough to admit what they didn't know. That kind of trust is not something you build by sending an announcement email or scheduling a mandatory awareness session. It accumulates over years of showing up to serve someone else's success. And it is exactly the kind of foundation that AI implementation needs, because the organizations getting this right are not doing it through mandate. They are doing it through human connection, one conversation, one workflow, and one team at a time.

There is also something less tangible but equally important: the relationships L&D professionals have built across an organization. We have worked with people at every level, in every function, in moments when they were vulnerable enough to admit what they didn't know. That kind of trust is not something you build by sending an announcement email or scheduling a mandatory awareness session. It accumulates over years of showing up to serve someone else's success. And it is exactly the kind of foundation that AI implementation needs, because the organizations getting this right are not doing it through mandate. They are doing it through human connection, one conversation, one workflow, and one team at a time.

Content

None of this means abandoning the work of improving L&D with AI. Using AI to strengthen your own practice is real and valuable, and there is plenty of room to do it well. But if that is the only place we are looking, we are thinking too small about what this moment is asking of us.

None of this means abandoning the work of improving L&D with AI. Using AI to strengthen your own practice is real and valuable, and there is plenty of room to do it well. But if that is the only place we are looking, we are thinking too small about what this moment is asking of us.

Content

The organizations that navigate AI well over the next several years will be the ones that figure out the human side of implementation: the change, the capability-building, the trust, the sequencing, and the measurement of what actually changed. That is not a technology problem. It is a learning and performance problem. And we are the people who know how to solve it.

The organizations that navigate AI well over the next several years will be the ones that figure out the human side of implementation: the change, the capability-building, the trust, the sequencing, and the measurement of what actually changed. That is not a technology problem. It is a learning and performance problem. And we are the people who know how to solve it.

Content

The question is whether we recognize it and decide to act on it.

The question is whether we recognize it and decide to act on it.

Content

For a deeper dive, check out The AI Implementation Guide for L&D .

For a deeper dive, check out The AI Implementation Guide for L&D.