There’s a ton of talk about AI adoption.
It’s odd because the validation of “adoption” has many definitions dependent on the context and environment. The common pitfall is to measure adoption as ‘use of AI tools’ alone.
As we know with previous technology, usage alone doesn’t mean meaningful adoption.
Setting what adoption looks like in your organisation is not a task for the L&D team.
Yet, we have an opportunity to contribute to long term and meaningful adoption of AI across workforces as part of a wide collaboration in a community.
Lets talk about that…
It takes more than access
Let’s go beyond the veil of bullshit we see online.
Access to an AI tool alone means nothing, and putting on one hour lunch and learns to “make people learn AI” is a comical up-skilling strategy.
If you’re a long time reader, you’ve heard me become a broken record when I talk about what it takes to nurture meaningful and long-term change.
We have much to consider with context, culture and constraints in each environment. No two workplaces are the same, that’s why the cookie-cutter “adoption frameworks” make me laugh.
They’re a good point of inspiration but you shouldn’t follow them like a strict set of instructions.
Saying that, what is it we need to consider beyond tools?
Read on…
People, Systems and Tools
As you’ve probably guessed, launching new technology and tools alone rarely leads to meaningful adoption.
There’s a bigger ecosystem at play.
We have to consider:
1/ People
Where are people at today and how do we meet them?
Everyone will have a different understanding, maturity and receptiveness to something new and unknown. In AI’s case, we have a mix of emotions from “will this take my job” to “I want it to do all this stuff I hate doing”.
The most difficult part of a change process is people because we’re all so unpredictable.
2/ Systems
Quite simply, how we work today.
What are the tried, tested and trusted conscious and unconscious systems we have in place. This covers both how we execute tasks and how we think about executing those tasks (deep, I know).
We each follow different types of systems in our day to day.
Understanding what these are and how AI will impact those is key in this change.
3/ Tools
The part you’re most likely more familiar with.
Here, we should consider the tools in use today alongside new ones being deployed, and how to bridge the gap in both understanding and knowing when and where to deploy them.
Too many forget the ‘when and where’ part at their own peril.
Where you can add value
For us to recognise where we can provide support and drive value, we must note what’s changing.
I think this framework from BCG can help recognise the moments where performance support is most need with AI transformation.
They propose it for navigating AI transformation at scale, and through an L&D lens, I see this as a conversation point of what to map against when focusing on how best to support workforce’s.
It’s built on two key dimensions:
1️⃣ AI Maturity
It progresses from tool-based adoption by individuals, to workflow transformation, to full, agent-led orchestration. Most organizations, and even teams within them, operate across multiple stages at once, not in a linear path.
2️⃣ Workforce Impact
This spans how tasks are executed, to what skills are needed, to how teams are structured, to how organisational culture must evolve to support new ways of working.
While this covers the wider transformation AI brings across businesses, it acts as a roadmap for L&D.
A roadmap is often what we need because its not uncommon for senior leaders to treat “training” (as they call it) as a boomerang that’s thrown at will when they decide people need to know stuff.
The framework above provides a view to where the friction/pain points/ problems exists in the cycle of change. That’s where we should focus.
Map it out
I mentioned before to not blindly follow frameworks, and that advice is the same here.
This view from BCG is a useful foundation for each of us to think about “where can we add value”, but it will look different for each environment.
So, I’d recommend you map out what your organisational journey looks like today.
Explore the 3 pillars of tasks, talent and teams across your business and how/where AI is starting to and might impact these. It’s here you will uncover the friction and pain points where we can be of most service.
Some of that will be through tooling, no doubt.
Yet, I feel pretty safe in saying you’ll be spending a good deal of your time navigating changes within people and systems.
Final thoughts
There’s much to say, of course, but only so much attention span I can ask you to give.
I’m thinking of expanding some of this thought into a long-form video, if that sounds like something you’d like to see, let me know.
In the meantime, so additional resources to explore on this include:
- Build your AI confidence with this strategy
- The ultimate guide to using (or avoiding) AI
- How to meaningfully drive AI adoption
Before you go… 👋
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