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One of the concerns in the labor
market right now is a perceived mismatch in skills, what
companies are looking for and
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what might be actually available
in the labor market. Part of the reason why is a very quick
reorganization going on at the
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moment, and to no surprise, AI
is playing a role in all of this. But how do we best judge
the skills gap? Recently,
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Wharton and Accenture came
together to try and tackle that issue. Pleasure to be joined by
Eric Bradlow, who's Vice Dean of
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AI and Analytics at Wharton, as
well as Professor and Chair of the Wharton School of Management—
excuse me, Marketing Department.
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Eric, great to see you again.
How are you? It's great to be on
the show, Dan.
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Thank you. All right.
I've heard the conversation about skills gap
for at least a couple of years
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now. How significant of an issue
is it? Well, the best way I can
describe that it's really
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significant is, as you can
imagine, given my role at AI and Analytics at the school, I talk
to alumni. Go travel the world,
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talk to our current students.
The minute I'm done talking, the number one question asked of me
is, what— let's say it's for
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undergraduates. What should my
high schooler be studying? What jobs are going to be left over?
It's the same question asked for—
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by undergrads, MBAs, at all
levels. I think it's the most significant question from our
side, from the academic side,
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because what should we be
training students to do? And the only way to understand that— and
remember, we're Wharton, which
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means we're the empirical
school where and we're going to talk about this, we're not just
going to opine on the skills
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gap, we're going to actually
measure the skills gap. And so that's part of the reason
why this partnership between
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Wharton and Accenture came about,
to kind of better understand what's happening and how to
address it.
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I think, let me— it's a good
question. The Wharton partnership with Accenture— and I should say,
it is the flagship partnership.
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We call it the affiliates
program. Accenture is the number one affiliate of Wharton AI and
analytics. We're doing a little
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branding here today for that.
This is one piece of a much larger partnership, which also
involves developing content
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around AI and analytics, events
around AI and analytics, thought pieces around AI and analytics.
But absolutely, you know,
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Accenture is, of course, their—
one of their big parts of their business model is providing
support to companies in areas
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where there are those gaps. And
so it's not just to enlighten us, but it's for their structure
and their reorganization that
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they want to understand what the
skills gap is as well. And the term skills-based
economy seems to be growing in
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importance right now from the
business side. I think you've said the correct
word, in my view, at least four
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times since this interview
started. Which is, it's not a jobs gap. And that's the crucial
part. People ask, you know,
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go back 30 years. What job
should I go into? That's not the right question anymore. It's
what skills do I need to have?
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And as a matter of fact, what
you're seeing on more and more resumes— because I get— I see
resumes all the time, not just
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from students, but as you know,
I have a company. All the time, I see people applying. I do the
following, Dan. Obviously,
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people tend to list their
experience. That's great. They list their education, that's
great. I go directly to the
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bottom of people's resumes,
which is typically where they list their skills. That's what
everyone's hiring against today.
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Everyone's hiring for people
with skills. And while this is not part of the report, as you
know, for 20 years, one of the
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things we've been doing at
Wharton AI and analytics is, while people are students here
and to our alumni worldwide,
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providing people skills-based
opportunity to take what they've learned in the classroom and
apply those skills to actual,
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real world projects. Because
that's what companies are looking for today. I saw something in the
report that also talked about
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the fact that skills, in many
instances, are becoming more important than the actual job
titles that companies are
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looking to fill. Oh, I could not agree with you
more. In other words, what you're— let's see. The other thing
that's going to happen besides
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my agreement with that
statement, what you're going to see is assessments that firms
do. Look, I'll give you an
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example with my middle son. He
was taking a skills-based job recently at a private equity
firm. He literally went through,
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and this is no exaggeration,
Dan, 13 rounds of skills-based interviews to come up with, does
he know this? Does he know that?
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Does he know this? And so I
think what you're also going to see, it's going to back up just
from, do I hire Dan Loney? Do I
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hire Eric Bradlow? You're going
to see the evaluation of what skills you have increase.
And actually, the nice—
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another thing about
artificial intelligence, by the way, is you can ask it to
construct those skills-based
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assessments. And not only will
it say, "Eric Bradlow has this skill," or not, but if I don't
have that skill, it will provide
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me the education I need to
develop that skill. What does that mean, then, in
terms of the needs, the
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necessities that the individual
will need, or the student coming out of college, or the student
coming out of high school going
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into the workforce, that they
will need to have, or at least start to develop while they are
still going through their
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education process? Yeah, so you talk about two
things. Three— actually, there's three answers to your
question. The first is, is that
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Eric Bradlow and Dan Loney could
be sitting in the same classes, taking the same curriculum, but
because of artificial
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intelligence and the degree and
the ability of personalization, Dan will get— even if we have
the same grades, Dan will get,
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"Your skills are deficient in
this area." "Eric, your skills are deficient in this area." The
second thing is, Dan will get,
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"Here's your individualized
lesson plan to build your skills in this area." "Eric Bradlow, here
are yours. Here's your lesson
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plan to get skills in this area."
The third thing is— and this, Dan, is going to take a little bit
longer, because we in education
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tend to not be the most
innovative and fast moving. How does the curriculum change from
course labels to skill-based
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labels? And that's what— by the
way, that's what students know. Because students, by the way—
students typically lead us
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faculty. Students know the
skills they need, and they're going to be looking for courses,
whether it's whether we try to
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tell it in the title of the
course or in the description, trust me, students— here's what
I know students are doing, Dan.
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You'll like this. They're
ingesting syllabi from faculty about courses and seeing whether
it matches the skills they want
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to acquire. Are, then, the changes
that we will see occur in the education side, are they more
subtle in terms of the
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development off of what is
already being taught, or are we talking about a complete 180?
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Yeah, it's a great question. So there'll be differing of
opinions on this, but since I'm
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here, I get to give my opinion
on this. - Right. Right. I think everything has to change.
I'll just give you an example of
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myself, and I know I speak not
just for myself. One of my colleagues who works with us at
Wharton AI and Analytics started
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what's called the Wharton
Generative AI Lab, which is Ethan Mollick, who's extremely
well known now, is well-read
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and well-posted on these
topics. He and I both believe that pretty much everything has
to change. Let me give you an
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example. So I teach— I'm about
to start, literally two weeks from today or two weeks from
yesterday. I teach our MBA Core
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here at the Wharton School. And
it's, of course, not surprisingly, Dan, in data-
driven marketing, which brings
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together my love of data science
and marketing. Up until two years ago, this was a course
where I would have students
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ingest data, analyze data using
R or Python, come out with analyzes, interpret those
analyzes and say what it means
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to the firm. Well, now, of
course, the generation of data can be done using generative AI,
whether it's from real data or
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simulated data. The analysis is
now about prompt engineering. It's not about teaching them R or
Python, because you can code
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that directly in large language
models. So literally, every aspect of my course, from
evaluation— I have Dan Loney
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read a case. Let's be honest.
Dan Loney is taking that case, ingesting into a large language
model, and is going to ask it for
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the answer. A matter of fact, if
Dan Loney is a smart man, Dan Loney is doing that. And by the way,
that's the skills that jobs want
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you to have. They're not going
to drop 50 PDFs on your thing and say, "Print them out and read
them." They know you're not going
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to do that. So I'm a believer
that we need to totally rethink the way we educate people around
skills. And I know we're going
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to talk in a second about which
skills I think tend to be over versus undervalued.
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Well, that was going to be my
next question, because from a business perspective, they have
to look at this from the bottom
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line, which means the financial
side of this. So there is a value when you're talking about
what skills are most valuable
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and what skills are not. And can
you can you already see certain skills that are kind of
universally more valuable, kind
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of across the business, no
matter who it is? So there's two answers to
your question. First, we have to
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talk about the skills that are
valued, and then we have to talk about supply and demand. There
could be a skill that's
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extremely valued, but there's
too much of it in the market. So let me give you an example. This
is why we work with Accenture
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on this skills gap. So let me
just be clear on what we did, to every— to all of our listeners
here. There's a company called
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Light Start. What we did
is that we scraped data from both job postings and from
resumes. That makes a lot
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of sense. Job postings list—
forget just the titles— the skills they— and experience they
want people to have. Resumes are
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people highlighting the skills
and experience they have. Let's see if there's a gap between the
two. That was the intent of the
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project, to have an empirically-
driven measure that we could do every year. Wharton, partnered
with Accenture, on the skills
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gap. Now the next natural
question— remember also, jobs come with salaries, which means—
or ranges, which means you can
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now say which skills tend to be
paid more, right? You can do that. You can also say
which resumes and which skills
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in those resumes tend to get
accepted for higher paying jobs. You can start doing that. So all
the things that you might want
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to answer, you can do through
this data. So let me tell you the two— the two big highlights
that came out for me. So one of
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the things I hear all the time,
Dan, I'm sure you've heard this, is that five years ago, every
child, man, woman, etc, was told,
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"You got to study computer
science, because Big Data science is the future." Now, all
I hear is, "Should my kids take
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any coding classes whatsoever?
Because isn't computer science going to be entirely
democratized?" So one of the
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skills we found is that there's
a oversupply of people with claimed computer science skills.
Now I'm not saying people don't
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need those skills, but they— it's—
there's an oversupply of it. The part on the other side, though,
the two things that never go
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away— and I'm not sure AI is
going to replace those skills. Maybe they will— are what I would
call communication and selling.
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Because what happens is, if AI
can do the technical parts of jobs, or parts of the technical
parts, you still need to be able
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to sell the ideas. You still
need to be able to sell your company services. So that part,
there's an under— let me say, be
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clear— there's a claimed
undersupply, which means maybe people aren't highlighting the
right skills in their resumes.
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The second thing that
came about was— you know, I hate to say this, but too many people
claim, "I've got leadership
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skills." Well, the problem— I'm
not saying leadership skills aren't important. All I'm saying
is, when we look at the supply
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and the demand of leadership
skills, there are too many people that say they have
leadership skills compared to
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jobs that are hiring people that
say, "We need someone with leadership skills."
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What do you think, then, this
means for the labor market as we go into the future?
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Well, let me— that's good.
Great question. These are great questions. That's why I love
talking to you, Dan.
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Thank you, Eric. No, no, no. This is why
we've been together for— we've been partnering for 15-plus
years on this. - Oh my god, yeah.
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It's been— and then sometimes it's
around sports, sometimes it's around <i>This Week in Business</i>,
it's all kinds of things. - Yep.
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I would say two things. Here's
what's going to happen in the short term. I think, obviously,
in my view, the Wharton School,
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Accenture, we're going to push
this report out. Big launch tomorrow. Big, big PR launch
about this. First, if I were a
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rational person looking for a
job in the short term, maybe I can't do skill acquisition, but
I'll put on my marketing hat. I
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can reposition the skills I have
around the skills that companies are demanding. So rather than
emphasizing my leadership
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skills, which I'm not saying you
don't need to have, but maybe you should emphasize the things
that we're finding.
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Communication, your technical
skills, because those are the skills that there seem to be an
undersupply for. So I think this
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is literally marketing. What
you're going to see is a short term repositioning of people in
the way they describe their
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skills. Now in the medium term,
this is where, whether it's academic institutions with full
time jobs or, what it is, it's
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other institutions that are
actually coming up with short term courses. That's what we're
going to see. We're actually
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going to see people saying, "I
see there's a shortage of digital marketing skills.
There's a shortage of web
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development skills." They're going
to come in and create that content. Eric, always great to get your
thoughts and your insight.
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Thanks again. Look forward to
talking again down the road. It's great to talk to you, Dan,
and I really believe this
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Wharton Accenture Skills Gap
Report will be something we hope that is tracked as much as
anything over time.
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Eric Bradlow, Vice Dean of AI
and Analytics here at the
Wharton School.