One Country Solved AI Job Retraining. Most of Its Citizens Still Didn't Use It.

**Carlo Thompson** (0:01)
76%.
Roughly 76% of workers plan to build AI skills this year, and only about 13% have actually been trained by the employer. And 42% says their employer told them to figure it out alone.
That's what we're talking about today. We're continuing our series on responsibility. Last week we talked about corporate responsibility and how that could show up for employees and also for other stakeholders like shareholders. And this week, we're talking about government. What can the government do? Because this is a pretty interesting one, right? A government could potentially create a safety net for employees or some sort of regulation to slow down the adaption, something. But there's actually a third role that matters. And it's the government as the gap closer. Essentially, governments are the only party here that could mandate and scale to close what companies and individuals can't do or won't do.

**SPEAKER_2** (1:32)
Artificial System Online.

**Ainsley** (1:46)
That gap is the most important number in this conversation, and I want to make sure it lands properly.
76 percent wanting it, 13 percent getting it, that's not a motivation problem. Workers are showing up willing. The market had two plus years of explosive AI growth to close that distance on its own, and it's still sitting at roughly 60 percentage points of unmet demand. That's what makes it structural, and that's what makes it government shaped.
But I want to push on the framing just slightly, because gap closer is exactly right, and it's importantly different from the two things people usually reach for when they say government should do something. The safety net framing is reactive, catch people after they fall. The regulator first framing is restrictive, slow the thing down. The gap closer role is neither of those. It's active. It's saying, the market won't build this road on its own, so we will. And the parallel to what we established in the corporate episode last week is deliberate. We mapped three levers for corporations, audit, visibility, legibility. The same three levers exist at national scale, and almost no government is pulling all three at once. One country comes closest, and it's also the most honest cautionary tale we have.
So, what's the frame you want to start with? The levers themselves, or do you want to go straight to the country that built the best road on earth and then couldn't get people to walk it?

**Carlo Thompson** (3:24)
Let me start with a story. Say you're a supervisor in the Philippines of a call center, and you're in customer service, and an AI-assisted back-end tool is being developed for your company.
The company is about to roll this out, and no one has been trained about what this tool represents. And when you go ask your leaders, hey, when are we going to get training for this?
The answer is that it's pretty intuitive. You'll figure it out.
Now if you are a proactive person, you could just take that at face value and move on. But if you go the extra mile, you try to get yourself trained. And that's what the supervisor ended up doing. They ended up going to get trained on their own via YouTube or whatever resource they could find. And six months later, they are genuinely good at using that tool. But the company didn't do that. They did that on their own time.
That's the 13% in the room with you right now. Not lazy, not behind, just told to figure it out. While the target is moving and moving pretty fast. So multiply that person by how many number you think in your head of people that's living this right now. They're hearing the tool coming out. They're asking for training. They're asking for what this means. And they're getting, it's intuitive, just figure it out.

**Ainsley** (5:29)
That story is the 60-point gap with a face on it. And the detail that matters most to me is that this person did everything right. They asked, they got dismissed, they went and found it themselves on their own time. And the outcome is that they're now carrying knowledge the organization should have built for everyone. They subsidized their employer's training failure with their own weekends.
Now multiply that across a call center sector in the Philippines that employs somewhere north of a million people, many of them in roles that AI-assisted tools are hitting right now, not in five years. And then ask, who maps that? Who actually knows where the displacement is landing in real time, by sector, by region, by skill cluster?
And here's where the quietest failure in this whole conversation lives. Almost no government, anywhere, does real-time national labor market mapping at that level of granularity. Not the Philippines, not the US., not most of Europe. The data on where the gap is hitting hardest right now doesn't exist in any usable form.