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I'm Stephen Carol and this is Here's Why, where we take one new story and explain it in just a few minutes with our experts here at Bloomberg.

Every one of our jobs, at every stage of our careers, at every company, in every country is going to get affected by how this technology is going to change work, and so we all need to lean into it.

No technology in the history of technologies has ever taken reduced jobs on net, but it does change who is working and who's not, and which skills are demanded.

Be aware of AI, adapt to AI, but also think about these problems of labor displacement.

You know, I think pure market capitalism can be pretty brutal here.

There's a growing body of research trying to predict how artificial intelligence will change the labor market.

But some say it's going to mean hundreds of millions of jobs are lost.

Others believe the technology will create far more roles than it ultimately destroys.

The change is happening quickly, but a report by the Economic Innovation Group think Tank in the US recently concluded that the effects of AI aren't showing up in labor market data, at least for now.

So here's why AI isn't taking your job yet, Blueberg opinion columnist to parme Olsen joins me.

Now for more, Parmi, let's start with the potential that AI has to shake up the labor market.

First.

Who is thought to be most exposed?

Well, I think because of the nature of the new generative AI tools that companies are so excited about the likes of chat GPT, they are very good at generating text, at processing lots of information.

So the people who are most exposed are the ones who do that kind of work, the so called knowledge workers, So people who work in the legal fields and media, in research, anything that involves any kind of information processing or generating information is exposed.

And that I mean, if you kind of look at what that means in context, that actually means people who are highly educated.

So one study showed that twenty seven percent of workers with a bachelor's degree are going to work in a job that's highly exposed to AI and potentially disruptive, whereas only three percent of people who don't even have a high school diploma are affected.

So that's a big gulf in terms of who's exposed and for many people that will seem quite ironic.

You spend all this money, you know, educating yourself to only find yourself actually quite exposed to this new technology.

The potential for change is absolutely huge, and the conversation is happening everywhere.

But what is the current data telling us about how AI is changing the job's.

Marcus So, I think it's quite hard to kind of get a clear picture of that yet, because there are so many other economic factors that are also affecting the job market.

You know, there's inflation, there's high interest rates, there's all the geopolitical stuff that's happening, and so I think, really, right now, what people can agree on is that AI is perhaps more of an accelerant than an actual cause to job disruption people losing their jobs.

There have been some studies that show there is a direct link between generative AI and layoffs, often because companies are attributing the layoffs to their use of greater use of generative AI.

There was one study that showed in the first seven months of twenty twenty four, ten thousand layoffs were linked to generative AI and something like in the top five causes of workforce cuts, AI is up there in those top five.

And the other effect we're seeing is of course like a hiring freeze on entry level workers kind of repetitive roles, particularly in software data management.

So I think we're also in this kind of wait and see moment where companies are still experimenting with generative AI to see how they can use it to become more productive, potentially cut down on costs, cut down on labor costs, and so they're not necessarily cutting jobs, they're just not hiring new jobs until they can see if AI actually can be used instead of a human Do we.

See much difference between countries or industries when it comes to the effect that it's having.

The greater difference is actually just between industries.

As I mentioned, the kind of knowledge work areas like finance and law and media and it.

Those are definitely industries that are very much affected, even creative industries who would have thought that, you know, a few years ago, whereas other industries which involve more human to human interaction or physical a physical trade like construction or you know, caregiving, those are a bit more insulated, but in much the same way.

You know, when you talk about countries, in much the same way that you know, people with degrees tend to be more are exposed.

So too are more advanced economies which rely on knowledge worker and the knowledge economy.

Countries in Europe and North America are perhaps more exposed to those in developing economies, which rely on more on manufacturing and on services.

So it's not like country by country, but certainly by regions.

I think there is also that difference.

You've been writing in particular about how young workers are being affected by this as well, what sort of things have you heard from them.

I think it's always tough for anyone entering the job market, for any young person entry.

I mean I remember when I was first looking for jobs twenty years ago.

It was really really hard and you had to trial sorts of creative ways to put yourself out there.

I almost feel like it is harder now for this current generation, and that is because companies are experimenting with AI, and the most exposed jobs aren't just the knowledge worker jobs, they're the entry level jobs.

And the reason for that is really simple.

Companies are being advised to treat AI and chat like an intern or a research assistant, and that's exactly what they're doing.

And they're doing that at the expense in many cases of real human interns or real human research assistants, because actually these tools do that work very very well.

That's where we're seeing some of the hiring freezes on the entry level work.

And one young people do get jobs at these companies in in sort of white collar jobs, they're expected to use AI on the job.

And that's a whole other kind of story because when you're using AI to do those first tasks, you're producing more more quickly than perhaps someone in your role would have done two years prior.

But are you being trained, are you really learning the business fundamentals, the industry fundamentals.

And I'll give you one example.

I spoke to one young man who was working at a fintech company.

He had an accountancy degree.

He was doing due diligence on companies.

And you know, three years ago, someone in his role would have been reading Moody's Reports and Companies House reports and analyst reports and just looking for those red flags to do the due diligence.

What he was doing was taking all that text and putting it into chat ebt and it was doing that analysis for him.

The great thing for his employer was he was producing something much more quickly than he would have done.

The bad thing for him is he's not gaining that skill kind of that those neural connections to spot or to read those reports and kind of know what to look for.

Young workers are in this weird situation now where they're actually not only being asked to do work more quickly, but kind of do more higher level strategic work because the AI is doing all this so called grunt work.

But I question whether you can make that leap without doing that grunt work first.

And what this next generation of office workers and professionals, what kind of grounding they have when they're letting AI do so much at the cognitive work for them.

That's a really interesting thing to think about as the technology gets rolled out into more areas as well.

I do want to think about as was citing this in historical context as well.

I mean, this isn't the first major technological shift that we've seen in the workplace far from us.

What have we learned from the past pivotal moments for our tech has gotten involved in the workforce That might give us an idea of how this is all going to pan out.

Well in the past, these kinds of transitions actually happened very slowly, which is odd to say, because I think right now this current transition with AI is happening very quickly, and I think it's going to happen more quickly than previous transitions had.

So, just for example the nineteen eighties, when companies who were previously doing everything on printed paper and faxes and telephone calls and handwritten notes, all of a sudden they were using computers.

That was a huge, very painful, very complicated transition to suddenly put everything in digital form on a computer.

Sort of the.

Same I suppose you could say with the move to cloud, and so that takes time because the company has all these different processes and ways of working and you have to transition that to this new environment.

And I think with AI we'll see something similar.

You know, It's funny because right now AI companies are just absolutely falling over themselves to make the biggest model, the smartest AI, and what they've failed a little bit at doing is really talking to their customers, their enterprise customers, and just helping them figure out how to use these tools in their own businesses and in their own processes and so there's been this difficult I think businesses have really struggled.

This is this incredible technology, how do we actually use it?

So even if AI didn't progress at all anymore, I think we'd still have another five ten years ahead of us for businesses just to figure out how to exploit, how to capitalize on this technology.

So I think we're in the early days of that, and probably like in the next three to five years or so, we'll see a bit more of an acceleration as companies really start to figure out how to use these tools and I hate to say it, but like replace some of their own workers with some of these tools and maybe even create new types of jobs that involve AI.

So much more to come on this topic, but for now, Parmei Elsen, Bloomberg Opinion columnist, thank you, and you can read more from Parmi at Bloomberg dot com Forward slash Opinion, and for more explanations like this from our team of three thousand journalists and analysts around the world, go to Bloomberg dot com slash Explainers.

I'm Stephen Carol.

This is here's why.

I'll be back next week with more.

Thanks for listening.