I’m fortunate that a lot of organisations reach out to me to support on their learning technology efforts.
As I’ve been exploring the AI-verse for the past 4 years and sharing what I know in public, the types of requests I now get are very different.
95% are all about AI enablement.
I feel like I’m in a Pokémon style evolution moment. I think it’s already happened as I now spend my days, outside of writing my newsletter, with organisations focusing on crafting AI enablement strategies for L&D teams to deploy.
This role didn’t exist 2 – 3 years ago and I think it’s one that’s going to gather pace as a key part of the modern workforce over the next 5 years.
They say (whoever they are) that life is about moving forward, learning and adapting to the times.
It’s hard to disagree with that.
We see it with bands, we see it in sports and we see a lot in TV and film as well. As humans we experience change every day, sometimes several times a day. It’s natural but it’s also something that a great deal of us struggle with.
That includes me.
You already know how crazy the past decade has been. We started it with a pandemic of crazy magnitude, which we haven’t seen in the last 100 years, and then we swooped right into the huge AI revolution.
So, it’s safe to say in 2026 that nothing is really the same but everything is the same too.
How I fell into this twilight zone of AI enablement
(Your age will dictate if you understand my little easter egg in the title here. Yes, I’m getting old.)
Of course I’ve experienced this in my own little slice of the world.
I’ve been in L&D for over a decade now.
I’ve been working with different types of technology in tech/HR/L&D focused roles for about 17 years so I’m used to change.
That’s the reason why my Steal These Thoughts newsletter exists.
I want to help L&D and HR professionals, or people professionals as they’re called nowadays, to truly understand and leverage modern technology in their work. The whole mission of that is to simplify tech as much as possible.
Of course I’m still doing all of that but it feels like there’s been an evolutionary jump in the last few years.
You see, there was a time when all people used to ask me about was LXPs and LMS’s.
- How do we build them?
- How do we deploy them?
- How do we make them successful in organisations?
That’s what I focused on from a technology perspective in our industry.
Now in 2022 when we started to see the emergence of generative AI and then quite quickly moving into large language models, a lot of that conversation completely changed.
No one asks me about LXPs or the LMS anymore.
This also changed a lot of my own journey because I became very curious, as tech nerds do, about generative AI and specifically looking at large language models and the potential applications of them in the L&D space.
I am continually high on what I call “The enormity of the possible”, and Gen AI has been my drug of choice to explore this.
So, I did what any good tech nerd does: I jumped in, I experimented, and I shared all of that stuff with the world.
That’s where I’ve been focusing my last few years.
This quickly shifted to how I can help L&D and people teams understand this technology, leverage it wisely, and then enable all of the teams in their organisation too. Of course if you read any of my work, I’m really trying to do that in a more human-focused way as possible as opposed to the AI bros that I like to poke fun at. All they seem to want to do is automate their life away with AI and sit on a beach somewhere and sip a pina colada.
Now with the huge economic and societal change that generative AI has brought, there’s been a shift, I suppose we could call it, in my own career identity.
I tell people I’m a learning technology strategist, but what I’ve come to find in the last few years, in particular, is that external people identify me as an AI influencer or AI expert. None of these things are actually true. Not in my mind, anyway.
I use AI every day. Maybe I know a little bit more than the average individual because I’m an early adopter, but I by no means know anything about how to create a LLM or do any of that stuff.
But what I do know is how to simplify technology for the everyday human and to help them leverage that.
I think that has always been a big part of what we do in L&D anyway.
Now add on top of that helping people, in general, to think through their skills, to think through the tasks they do, and to help them think about the workflows that they either partake in or they build themselves at an individual, team, and organisational level.
That’s where I do a lot of my best work.
What I’ve learned now is that has evolved into this kind of new role of what I call an AI Enablement Architect.
AI Enablement, not Adoption
About a year ago, I wrote an article where I basically went into Nostradamus mode and prophesied that AI architects, both from a technical perspective and a non-technical perspective, would be the next big role in the future of work.
It came about because, at that time, I’d been asked in a particular month so many times across LinkedIn direct messages, my emails, or through my newsletter, “Are you an AI architect?” I always said “no” because I don’t look at myself as a technical individual.
I am very much non-technical when it comes to the developer side of AI technologies but it kept coming up.
What this data showed me was that this was an emerging need which could become a role. You can read that article to get my view on non-technical and technical AI architects at that point.
Today though, where I find myself in this space is specifically working with L&D and people teams, and even teams outside of that from time to time, to specifically look at AI enablement.
Now, for me there’s a big difference between AI enablement and AI adoption.
AI adoption is about making people use tools.
It tracks vanity metrics like how many licenses are distributed across an org, number of logins and how many cat pictures Eric generated this month (damn it, Eric – think of the tokens).
AI Enablement is a different game.
It’s about equipping humans with knowledge, skills, and frameworks to use AI effectively in their work.
My fellow L&D teams can help with the latter in soooo many ways, but they’re being held prisoner by their organisation to the former.
Having access is not the same as delivering value with it, imo.
What does an AI Enablement Architect do?
The obvious question, of course.
What sorcery am I up to?
So while the main way I contribute to the world and the L&D industry is through researching, analysing, and bringing new ideas through my newsletter, I’m also being asked by a huge amount of organisations to support them with AI enablement.
When we say those words, it can seem a bit confusing, so let me break down what I actually do with organisations, in case you are someone that might want to work with me on this, but also if you’re an individual who is curious about what someone does who works in AI enablement.
Predominantly, my role is to work alongside teams, so I look at myself as an AI enablement architect that helps them with:
1/ Identifying where they are today
What I mean by that is, from an AI maturity perspective, before you can do anything with organisations, you need to uncover exactly where their teams are: what do they know, where are they struggling, and what are those pain points?
Some of the ways I do that is by generally doing a diagnostic assessment across the teams, departments, and even the organisation to get an understanding of their current skills with AI and their level of knowledge in their own human skills as well.
Usually, what comes out of that is that we’ll get all of this data, and I’ll spend some time with the organization to understand the results.
We’ll put together an action plan around that so they know where to focus their time and money to get the best ROI.
2/ Building the enablement strategy
Once we have the data that allows us to map the organisation’s current AI maturity, what I’m able to do is build a practical, step-by-step plan for how a company will roll out not just the AI tools themselves (that’s not really what I’m doing), but actually how we enable people to use those AI tools in their everyday work.
This comes in a variety of different approaches.
Mostly, that’s looking at the data that we’ve already got about AI maturity, but it’s also looking at workflow opportunities across the organisation.
What I mean by that is what are the workflows that people are using today in their physical space, and then look at them to understand how we could reshape them with AI, or how could we support them with AI.
What I will then do is look at what’s the best way to actually enable people in the organisation:
- Is it up-skilling internal L&D teams to do that?
- Is it bringing in outside help?
- Is it a mix of both, or is it building an entirely new solution?
The output of that is that I’ll build a clear strategy that maps out the entire enablement journey for whatever population of the organisation needs it.
That is bespoke on a local level in teams, departments, and organisations.
This is incredibly helpful because what it’s allowing you to do is get clear ROI on the efforts that you’re doing from an enablement perspective on the technology that the organisation has access to.
3/ The on-demand AI enablement Architect
What’s different here is that instead of running like a one-off workshop or a couple of workshops in an organisation, I’ll stay with them as kind of this embedded consultant while that full rollout happens that we’ve built from an enablement perspective.
I might have monthly or weekly check-ins. We might just do sound boarding calls every quarter. There’s also on-demand support as things shift as they always do.
What that gives organisations is access to up to date and relevant information, and my ability to provide direction, because I’m working with so many different organisations on enablement strategies.
I can give them the experience they may not have in-house right now to accelerate what they want to do and help them when the plan does change, because it will change with AI.
Ultimately, it helps them ensure that all of the new habits that we’ve done actually stick.
In not so much of a nutshell, that is what I do in this AI enablement space right now.
Like I say, I didn’t plan on doing this. It’s been completely accidental.
It’s been purely driven through requests from probably people like you, who might be reading these words right now or even listening to them.
It’s interesting to see how things are shifting. The reason why I share this is because I am really clear that in order for L&D to be successful, I believe that we need to move from production to enablement.
I think for L&D’s relevance and for its credibility, it needs to stamp itself in the organisation as the AI enablement function.
We’ve seen a lot of this already, and I’ve written a lot about this, with a lot of companies merging their people teams and parts of their product and technology teams to make overall AI enablement departments.
This is kind of like I say, a bit of an evolution in terms of the work that I’m doing. If it sounds interesting to you and if you’re looking for someone to help you with AI enablement in your company, obviously, reach out to me.
And I hope this has been helpful in terms of just giving you a view into the shifting roles and tasks that are out there now. There’s been so much hype about the AI jobpocalypse and all of this stuff going on, but actually what destroys stuff also can create stuff too.
I think this is one of the roles that is quickly emerging, and we’ll see departments created around these roles too.
The skills, mindset and behaviours most useful for this role
As L&D pros, I know this will be the question everyone asks.
Here’s how I see it right now.
- Digital intelligence. Specifically around generative AI technologies. A no brainer, of course. You don’t need to be an AI engineer, but you do need to understand fundamentally how the tech works so you can map that to your enablement guidance. It also goes without saying, you need to be well versed in the current AI landscape.
- Storytelling. I’m going to cheat here because I’m using this phrase as a catch-all for being able to market your ideas and capabilities, sell your proposed solutions and position stakeholders.
- Performance consulting. Yes, you still need this because performance is life. Without a clear “why are we doing this?”, expect everything else to fail.
- Workflow Design. This is where a lot of the gold is and is currently being underserved. Knowing how to help teams deconstruct the things they do on repeat to build a workflow and then analyse that to see if it can be redefined with AI at the core or enabled by it with automation instead.
- AI Fluency. A buzzword? Maybe…but, I think it’s one that has good meaning behind it once you get unstuck from the marketing wrapper. It’s not about using tools, but about how you choose to use tools and their outputs in an intellectual, ethical and common sense capacity.
- Human Instincts. I covered this in quite a bit of detail recently. I look at this as an advantage in all your work.
Of course, there’s more and the usual underpinning of human skills that you need just to navigate life in general.
Final Thoughts
My current thinking is this can and will be seen as a stand alone role, but it can expand to include AI enablement partners that form the human side of the team with the architect.
Of course, all enablement architects today will already be using agents within their team setup (as do I).
That’s it for now, folks. I hope it’s helpful, and I’ll talk to you in the next one.
Before you go… 👋
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