The inevitable shrinking of L&D

Anyone else feel like working in L&D is like running on an increasingly fast treadmill, with anyone a fraction too slow falling off the back?

In the book Map It, Cathy Moore did a lovely job of breaking down what goes into successful performance improvement:

1. Knowledge
2. Skills
3. Environment

When those three categories are carefully considered, we can design solutions that give people what they need:

• Knowledge was always the easy one - meet with the SME and convert their great thinking into content.

• Skills required a bit more nuance - designing opportunities for people to practice. Who hasn't designed a scenario or two?

• And environment... well, that was always a bit of an afterthought, wasn't it? Take a Storyline module for example... how often did we spend months designing "the course", only to tack on some cheat sheets in the Resources tab?

Clearly, we've come a long way since then.

But the reason we're experiencing this accelerating treadmill feeling, is that the first of those three categories is disappearing. Our stakeholders don't need us to build content any more - they can chuck all the info into some markdown files and get their new starters to interact with a chatbot.

And so, reflecting on how much of our work used to sit within that knowledge category, it's no wonder there's more supply than demand.

So, where does that leave us?

Skills and environment.

Now, helping people build skills is as critical today as it's ever been. So, of course we can double down on that. But if we reflect on how much of our work has historically involved knowledge transfer, that's an insane amount of capacity switching its focus to skill building.

So, what else can we do?

Well thankfully, with the evolution of AI, we're seeing our employees and clients recognise the importance of the environment in which people operate.

Why?

Because it's the environment that determines how effective people are with AI.

After we've got past that reactive, ad-hoc "thinking partner" layer of AI usage (in which 99% of knowledge workers are currently operating), we're left with a tiny fraction of AI usage that's actually adding value to the business.

Think of it like this - what percentage of a typical employees AI use will still be adding value after they've left the company?

For most, the answer would be none. A few might have built a prompt library. One or two might've built an agent.

But most of us are using AI on the fly.

And the reason we use it like this is because the work hasn't been defined. No standards, no best practices, no measurement, no evaluation... How can people use AI in systematic, structured fashion, if they're all doing their work differently?

So, this is our opportunity. If we're willing to switch our focus to improving the environment, we can slow down the treadmill and keep on running.