AI's First Victims Won't Be Its Last: The Hidden Impact on Early-Career Workers

Sometimes history whispers before it shouts.

That's what I thought reading Canaries in the Coal Mine? – a new paper from Stanford economists Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen.

Using payroll data from millions of workers, they found something striking: early-career workers (22-25 years old) in AI-exposed roles like software development and customer service have already seen a 13% drop in employment since late 2022.

Not across the board, but in the jobs where AI automates tasks rather than augments them.

For more experienced workers in the same fields? Employment is steady, even growing.

It's the first time we've seen large-scale, hard data confirming what many suspected: AI isn't just hype, it's already reshaping the labour market. And the first to feel it are those just starting out.

Why the Youngest Workers Go First

Here's the researchers' theory: entry-level employees rely heavily on codified knowledge – the kind of things you learn in a bootcamp, a degree, or a training manual. AI models are trained on that same knowledge base.

Experienced workers, by contrast, carry more tacit knowledge - judgment, relationships, context, the stuff that doesn't show up neatly in textbooks. That's harder (for now) for AI to replicate.

Which means the career ladder is starting to fracture from the bottom. The rungs are thinning out just as young people are stepping onto them.

And let's be honest about what this means in practice. Those fresh graduates who used to spend their first year learning the ropes, getting comfortable with basic processes, building confidence? Many of those foundational roles are disappearing. AI can now handle the routine customer inquiries, the basic code reviews, the initial data entry that used to be someone's first job.

What Happens When the Career Pipeline Breaks

Every wave of automation has started this way: machines take the easiest-to-systematise tasks first, then move up the value chain.

The risk this time is sharper: if the entry-level pipeline collapses, who grows into tomorrow's specialists, managers, or leaders?

Without pathways for younger workers, we risk a hollowed-out workforce - too top-heavy, with too few coming up behind. And then who will the managers manage?

Think about it from a business perspective. Your senior developers, your experienced customer success managers, your seasoned analysts - they all started somewhere. They built their tacit knowledge through years of handling the routine stuff, making mistakes, learning from feedback. If AI eliminates those learning opportunities, where does the next generation develop those crucial skills?

And this isn't a "tech sector" issue. Yes, coders and call-centre workers are the canaries. But finance, legal, healthcare admin, even parts of media and marketing will follow. Any job built primarily on codified tasks (including those in offshored centres) is fair game.

I've seen this pattern in my conversations with CEOs across industries. They're excited about AI's potential to streamline operations, but they haven't thought through the workforce implications. Who's going to train the next cohort of managers if there's no entry point into the company?

The Opportunity Hiding in Plain Sight

The story doesn't end with displacement. The study also found something hopeful: employment is growing in roles where AI augments work rather than automates it.

That's the crux. AI doesn't just substitute - it reshapes the balance between human and machine. Leaders who design roles with augmentation in mind create resilience. Workers who learn to wield AI as leverage grow more valuable.

But it won't happen by accident.

Here's where I see smart organizations getting ahead of this. Instead of letting AI simply replace entry-level roles, they're redesigning them. The junior developer isn't just writing basic code anymore - they're working alongside AI to solve more complex problems faster. The customer service rep isn't handling routine queries - they're managing the escalations that AI can't resolve, building the relationship skills that matter.

This requires intentional workforce planning. You need to understand which tasks in each role are prime for automation, which ones require human judgment, and how to combine them in ways that make your people more valuable, not less.

What Leaders Need to Do Right Now

If you run a company, this isn't just an HR problem - it's a future capability problem. You can't let the entry-level disappear without starving your own pipeline.

That means:

Redesigning Jobs for Human-AI Collaboration

So juniors aren't competing head-to-head with automation but building tacit skills alongside it. This is about more than just "adding AI tools" to existing roles. It's about fundamentally rethinking what value humans bring and how to develop that from day one.

Investing in Internal Career Pathways

So people can see where their role goes next - even if their starting point or next step looks different than it did five years ago. Career development can't be an afterthought when the traditional progression is being disrupted.

Using Skills Visibility to Plan Ahead

To plan for capability gaps before they become crises. Most organizations have no idea what skills they actually have or what they'll need as AI changes their operations. You can't manage what you can't see.

Full disclosure: this is the space I spend my time in - helping organisations map skills, career pathways, and opportunities inside their own workforce. Because the companies that get this right won't just survive the AI transition - they'll use it as a competitive advantage.

The Broader Workforce Strategy Challenge

What's happening to early-career workers is a preview of a larger challenge. As AI capabilities expand, the disruption will move up the value chain. The question isn't whether this will affect your industry - it's whether you'll be prepared when it does.

I've been working with CEOs who are grappling with this reality. They know AI is coming for their operations, but they're struggling to balance efficiency gains with workforce development. The temptation is to focus on the immediate cost savings and worry about the people strategy later.

That's backwards thinking. The organizations that thrive will be those that design their AI adoption around human capability building, not just cost cutting.

Listen to the Canaries

The data is still new, and like all early signals it will be debated. But that's exactly why it matters - these shifts are a preview of what's likely to come.

The early-career workers experiencing this disruption aren't just statistics. They're the leading edge of a fundamental change in how work works. And if we're not thoughtful about how we respond, we'll create a workforce that's increasingly polarized between highly experienced specialists and AI systems, with nothing in between.

The choice isn't whether to adopt AI - that ship has sailed. The choice is whether to do it in a way that builds human capability or undermines it.

As I've learned from years of working with organizations on talent strategy, the companies that invest in their people during times of change are the ones that emerge stronger. The ones that treat workforce planning as an afterthought usually end up scrambling to rebuild capabilities they let slip away.

The canaries are singing. The question is whether we're listening.

Ready to Build an AI-Ready Workforce Strategy?

Don't wait until the disruption reaches your organization. The time to act is now - while you can still shape the transition rather than react to it.

GoFIGR helps leaders identify AI risks, map career pathways, and design roles that combine human expertise with AI capabilities. We turn workforce planning from guesswork into strategic advantage.

Contact GoFIGR today to see how we can help you navigate the AI transition with confidence.

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