August 15, 2025 • 10 mins
A growing body of research is pointing to the drastic changes artificial intelligence will bring to the workforce, with predictions of millions of jobs being created and lost. According to analysis of recent US labor market data, AI does not appear to be causing a slowdown in hiring. Many companies are racing to implement the new tech into their businesses, but are they employing fewer people as a result? Bloomberg Opinion columnist Parmy Olson joins host Stephen Carroll to discuss.
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Episode Transcript
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Speaker 1 (00:02):
Bloomberg Audio Studios, podcasts, radio news. 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.
Speaker 2 (00:20):
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.
Speaker 3 (00:32):
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.
Speaker 4 (00:42):
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.
Speaker 1 (00:54):
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
(01:17):
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.
Speaker 5 (01:35):
First.
Speaker 1 (01:35):
Who is thought to be most exposed?
Speaker 5 (01:37):
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
(02:00):
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
(02:22):
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
(02:43):
actually quite exposed to this new technology.
Speaker 1 (02:45):
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.
Speaker 5 (02:54):
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
(03:15):
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
(03:37):
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
(03:58):
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
(04:19):
can be used instead of a human Do we.
Speaker 1 (04:21):
See much difference between countries or industries when it comes
to the effect that it's having.
Speaker 5 (04:27):
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
(04:47):
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
(05:09):
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.
Speaker 1 (05:22):
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.
Speaker 5 (05:27):
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
(05:48):
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
(06:12):
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,
(06:39):
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
(07:01):
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
(07:23):
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
(07:47):
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.
Speaker 1 (08:06):
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.
Speaker 5 (08:27):
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
(08:47):
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.
Speaker 1 (09:00):
Sort of the.
Speaker 5 (09:01):
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
(09:24):
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?
(09:44):
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
(10:04):
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.
Speaker 1 (10:14):
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
(10:35):
here's why. I'll be back next week with more. Thanks
for listening.
Bloomberg Audio Studios, podcasts, radio news. 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.
Speaker 2 (00:20):
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.
Speaker 3 (00:32):
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.
Speaker 4 (00:42):
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.
Speaker 1 (00:54):
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
(01:17):
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.
Speaker 5 (01:35):
First.
Speaker 1 (01:35):
Who is thought to be most exposed?
Speaker 5 (01:37):
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
(02:00):
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
(02:22):
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
(02:43):
actually quite exposed to this new technology.
Speaker 1 (02:45):
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.
Speaker 5 (02:54):
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
(03:15):
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
(03:37):
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
(03:58):
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
(04:19):
can be used instead of a human Do we.
Speaker 1 (04:21):
See much difference between countries or industries when it comes
to the effect that it's having.
Speaker 5 (04:27):
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
(04:47):
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
(05:09):
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.
Speaker 1 (05:22):
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.
Speaker 5 (05:27):
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
(05:48):
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
(06:12):
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,
(06:39):
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
(07:01):
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
(07:23):
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
(07:47):
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.
Speaker 1 (08:06):
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.
Speaker 5 (08:27):
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
(08:47):
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.
Speaker 1 (09:00):
Sort of the.
Speaker 5 (09:01):
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
(09:24):
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?
(09:44):
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
(10:04):
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.
Speaker 1 (10:14):
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
(10:35):
here's why. I'll be back next week with more. Thanks
for listening.
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