L&D’s Maginot Line Moment: Are You Still Preparing for the Last War?
Photo attribution: Canva
Santosh Kumar’s article, The 8 AI Fallacies Dismantling L&D: Why Our "Maginot Line" Won't Hold, draws a parallel between traditional L&D and the Maginot Line. (For those in the back, it was a massive line of fortifications France built in the 1930s [think: concrete, state-of-the-art bunkers, underground railways, air filtration systems…] cutting edge technology and engineering back in the day.) The point being, defending a field with technical prowess (for its day), but strategically irrelevant once the terrain shifts.
You’re probably noticing this, too, I hope:
Using AI to automate or optimize outdated workflows, rather than questioning whether those workflows still serve us well.
Celebrating course development wins and completions while operators and business units solve urgent skills gaps themselves without waiting for L&D to catch up.
Clinging to centralized control while Ops feedback loops and AI redraw the local learning landscape.
I’ve posted about these before. Some of which may have been a bit critical of ADDIE in light of more agile methods to build capabilities.
Don’t get me wrong, I love ADDIE. But not for a business problem that a job aid or a minimally viable course couldn’t have solved in a fraction of its time.
I maintain that the unit of learning isn’t always a course or a module.
That performance support — and whether a course is even required — should often be considered first. (Yes, dammit. That em dash is my addition.)
And that maybe our role isn’t to “teach” but to help the business adapt faster to what the frontline needs.
Now that AI’s at the table?
The terrain is shifting again. And faster.
So I’ll extend Santosh’s battlefield metaphor: if we’re still measuring success by courses developed, butts in the seat, and boxes checked, instead of how capabilities emerge and evolve… then maybe we’re still preparing for the last war while the landscape has shifted.
I don’t think the question is whether or not we’re using AI, rather if we’re using it to shed light on assumptions we haven’t thought to question.
You seeing it, too? Tell me in the comments.
