After four days and thirteen sessions, I’m not sure AI really was the story of the Learning Technologies Autumn Forum.
It was everywhere, obviously. But the more interesting conversations were about what happens to L&D when producing learning gets easier.
Day 4 reinforced that from four different directions.
Thrive talked about connecting systems rather than adding more of them. Arun Pradhan talked about the influence and political awareness needed to get anything useful done in an organisation. Articulate showed how people outside L&D can increasingly create learning themselves.
Then Don Taylor and Eglė Vinauskaitė asked the bigger question: if content production is no longer a distinctive value proposition, what does L&D become?
Their three routes are Skills Authority, Enablement Partner and Adaptation Engine. They are different models, but none of them is built around being the organisation’s training factory.
That was pretty consistent with the previous three days.
We kept coming back to performance, practice, context, workflow, judgement, evidence, governance and the conditions around the work. We talked about diagnosis before design. About knowing when skills are the issue and when they aren’t. About connecting expertise rather than trying to own all of it.
Of course training still matters – and so does content.
But they are parts of the job, not THE job.
The question for L&D is becoming less “what should we create?” and more “what needs to change, what is getting in the way, and what role should we play in fixing it?”
The timing is useful because I’m taking much of the same conversation into CIPD next week.
On Monday we have the first CIPD L&D Network session, looking at the role of L&D in supporting a performance-led skills strategy. Then at the CIPD Annual Conference on Wednesday, I’m involved in two more L&D sessions, including a panel on performance-led skills strategy.
They all come back to much the same thing.
If someone asks for training, can we explore the problem before accepting the solution? Can we distinguish a skills issue from something getting in the way of performance? Can we influence what happens next, even when the answer isn’t learning?
For me, that’s a much more useful place for L&D to be than asking what we should create next.