Back to Basics

Photo by The New York Public Library on Unsplash

I went to Olympia London on Tuesday 4^th February for a wander and catchup at the World of Learning Summit Exhibition. A relaxed and enjoyable experience, in a familiar and inviting space, I visited some exhibitor stands, purposefully - and sometimes accidentally - met some of my professional pals and basically recharged my L&D batteries.

A recurring topic of conversation was that the AI in Learning hype seems to have quietened down, as the reality of the tools, it’s limitations and its benefits, have challenged the L&D profession to really question its efficacy and relevance. In my view this is a good thing.

I detected a more mature repositioning of L&D’s attitude to and use of Artificial Intelligence. It seems it has challenged us to look at ourselves and what we do, through the lens of a powerful tool that will only serve us if and when we get our own house in order.

Initially, AI will work best for us as a beast of burden, taking on our boring admin, content scraping and weeding, and freeing us up to be more creative and relevant in supporting our customers with better learning solutions.

And we can do that better by going back to basics.

We need to get to grips with proving impact – and for that, we need data. And data is the lifeblood of AI. The insights and evidence of our impact should then follow.

On Monday, Wesley Atkinson (https://www.linkedin.com/in/wesleyatkinson/) posted a short piece on LinkedIn which prompted me to think about how L&D could meet AI in that space.

“If you’re not organised and don’t track/plan ahead, proving the impact of an e-learning course is going to be hard.

To do this properly, you need:
- A business counterpart to collaborate with.
- At least two measurable data points to track.
- To figure out what to track BEFORE you launch the course.

Proving ROI on an e-learning course is about tracking the right numbers from the start.

Without a plan, it’s impossible to demonstrate business impact.”

Boom! (Thanks Wes.)

Three things for me here:

-        An engaged business stakeholder is essential to assist learning designers to ensure their solution is relevant to the organisation.

-        No data, no evidence of impact!

-        AI to evaluate evidence, assess the impact and suggest further refinements .

Is AI the kick in the pants that L&D needs to be better? Or am I oversimplifying here? I’d be interested to hear your thoughts on this take.