Latest / The DEX Show: A Show for IT Change Makers / From Coding to Creativity: The Changing Landscape of Tech Jobs (w/ Alexandra Levit)

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From Coding to Creativity: The Changing Landscape of Tech Jobs (w/ Alexandra Levit) · The DEX Show: A Show for IT Change Makers

0:01
Welcome item change Makers to the Deck Show with Tim Flower and Tom McGraw.
0:07
Let's get into it. Hello, change Makers, Welcome back to the Deck
0:11
Show. It's my great pleasure to welcome Tim Flower back where he belongs in
0:16
the driver's seat with me. How you doing, Tim, It feels like
0:19
it's been ages since we recorded. It's been a while. Yeah, it
0:21
took a little time off, a little time in a motorcycle seat. But
0:25
glad to be back. Love to hear it, love to hear it.
0:29
And we have an absolutely fantastic guest to help welcome Tim back. If you
0:34
will, she's Alexandra Levitt. She's a CEO of Inspiration at work. She's
0:40
a nationally syndicated columnist for the Lights of a Wall Street journal, and she's
0:44
authored several books, the most recent of which is Deep Talent, How to
0:48
Transform your organization and empower your employees through AI. One of the books you've
0:54
written. One of the things you've written, Alexandra, which caught our eye
0:57
and made us want to invite you onto the show, which to have you.
1:00
How are you today? I'm doing well. Thanks so much for having
1:03
me. It's really great to have the opportunity to chat with you both great
1:07
pleasure and maybe just introduce ser I give you a little introduction, but anything
1:11
you would add for your audience aldant to fill out that portrait a little absolutely
1:15
well. First of all, I'm sometimes called a workforce futurist, and when
1:19
people hear the term futurists, they tend to be a little perplexed. What
1:25
does that actually mean? It sounds like something out of science fiction, something
1:27
you made up. And I would just like to clarify right at the start
1:30
that a futurist is just someone who looks at signs and signals that are percolating
1:37
up through the larger market, through a specific segment, through society in general,
1:42
and tries to make an educated guess about what has the greatest potential for
1:47
disruption, and in doing that, like five or ten years out, hopefully
1:52
you can be in a position to be better prepared for the outcomes that are
1:55
most likely. So it's not a crystal ball, it's not even necessarily prediction.
2:00
All our educated guess is forecasts, and uh, it's fun to see
2:05
how you do over time. I think the only way to know if you're
2:07
a good futurist is to wait a couple of decades. That is funny.
2:15
You did make it sound a bit like an astrologia when you were laying or
2:20
she's an it nostradamus. Well, the difference is that the information that I
2:23
get isn't from things like the stars. I mean, it's from media cupboards
2:28
that's already out there. It's research that's already so much important qualify that.
2:32
Yeah, we're not we're not reading the TV. Real well, if you're
2:38
willing to look to do a really deep dive and look at what's being what's
2:44
happening around you and the trajectory of those developments, I think it's something that
2:49
it just takes a little bit of practice. But really, anyone who schooled
2:51
in a particular discipline can can do it. Love it, love it,
2:55
And I mean, I think this is we have been you know, I
3:00
think we're I'm starting to get worried him, but our audience is becoming a
3:04
little bored of AI. We have been obsessed with it. Everybody's obsessed with
3:07
it, and everybody simultaneously a little bit bored about it, like because it's
3:12
so ubiquitous at the moment as a topic. But I think what you've managed
3:15
to do Alexandre is really hone in on something that touches us all quite personally
3:22
and directly, which relates to anxiety about the future of AI, the future
3:27
of the workplace, of future of all of our careers. So maybe set
3:31
the scene for us to beginning for all the sort of intense discussion and interest
3:36
around AI. What do you think is effectively being overlooked in terms of how
3:39
we expect it to impact work and careers. Yeah, this is a great
3:46
question, and I think there is a lot of hype. A couple of
3:49
years ago, we saw similar phenomena with the metaverse, where everybody was talking
3:53
about it generally speaking, is more of a philosophical question, but no one
3:58
was being ultraspecific on how they're going to get to point A in point B.
4:01
And then the metaverse was rather summarily dismissed as a topic of interest,
4:06
which I find very interesting because at all I think it's just a matter of
4:13
time before that is the majority of where we're going to be doing our work.
4:16
So that's an example of where I think generative AI is right now.
4:19
It's very much in the hype cycle, and you have a lot of anxiety
4:25
around Oh, we needed to do GENAI pilots yesterday. We need to be
4:30
incorporating AI into every piece of operations within our business. And the truth is
4:35
is what we're really lacking are very clear use cases where particular problem is solved
4:44
and the output using an AI partner is better. It's more strategic than what
4:50
we would have done without that partner. That we have mastered in at least
4:54
that particular process, how to have proper human oversights so that the tool does
4:59
not run am uk, we're able to derive reputable and valid insights from data.
5:05
I think that these are all challenges that most organizations that are talking about
5:12
generative AI aren't quite at the stage where they are doing it extremely well and
5:17
in a way that can be repeatable into other processes. So that's the one
5:21
thing that I would say, just talking about it isn't going to like transform
5:26
your business. So there's two things, right. You want to look for
5:30
ways to make it very tangible, which will in my opinion, involve small
5:34
pilots throughout the organization and a lot of experimentation. But you also want to
5:41
not get too worried about being behind because I think it's this is the kind
5:45
of thing it's better to do slow. It's better to do it sensibly and
5:47
do it right than to just kind of jump on on the bandwagon. And
5:51
the other thing I'd say about AI and the hype is that generative AI in
5:56
particular isn't in large language models are necessarily the huge leap that I think people
6:02
think that they are. I mean, really, it's just a logical progression
6:05
of how smarter technologies have been getting over the last couple of decades. But
6:13
until we have something like artificial general intelligence, where these algorithms can then start
6:17
making independent decisions and changing things without input from a person or a data set,
6:25
that's when we, I think, really are going to see a transformation
6:28
within society. But we're not there yet, so we still have to put
6:31
a lot of guardrails around this stuff and make sure that it's being used for
6:38
the business purpose for which it's intended, and we don't allow it to run
6:41
amook. I mean, mistakes us pretty near some of your ideas in Deep
6:46
Talent, and I wonder if we could relate them together to specifically to technology
6:50
workers. You know, how have you seen traditional tech roles evolve in the
6:56
past decade and in the light of these changes, what skills do you see
7:00
is becoming increasingly important? This is one of my favorite questions because actually,
7:05
when about ten years ago that I started talking about tech workers specifically, and
7:12
what I thought was fairly obvious. I mean, maybe that isn't true for
7:15
everyone, but I thought it was fairly obvious that things were going to shift
7:18
fundamentally in the technology world when you have a population that has been highly employable,
7:27
highly marketable, highly sought after for decades, that has basically been able
7:31
to like rest on their laurels and a certain number of certifications, know a
7:39
certain number of programs, and they were going to be good to go.
7:42
They could command anything they wanted really in the work world when it comes to
7:46
employment. And it came pretty obvious to me early on, as I said
7:49
that at some point they're going to be the first ones to be automated,
7:54
because those are some of the tasks that are most to give over to machines,
8:01
is like the creation and management of machine partners. And I worried a
8:05
little bit about tech workers because I thought, are they not keeping their human
8:11
skills up to par while they are resting on their hard technical skills. And
8:16
when I say human skills. I'm referring to things like intuition, empathy,
8:20
judgment, problem solving, creativity. I mean, these are things that a
8:24
lot of IT folks haven't had to develop. It's not that they don't have
8:28
them or they're not interested in having them, it's just that that hasn't been
8:31
the focus. And now you start to see that they're first on the front
8:37
lines to be automated, and you start to ask yourself, Okay, well,
8:39
what else can they do? How can they add value to these roles
8:45
in the realm of oversight? Talked about that, I mean, whenever you
8:48
I'm very fond of using this expression, whenever you insert a machine into a
8:54
traditionally human driven process, you still need a person to design it. You
8:58
need a person to oversee it, you need a person to fix it when
9:01
it's broken, figure out how to redeploy it, and then communicate its insights
9:05
to business leaders. That's a lot of jobs that IT people who were previously
9:11
just programmers could take over and step up into the light and take those roles.
9:16
So the long answer, that's the long answer to that short answer,
9:20
is the roles are evolving to be much more well rounded, and it folks
9:24
can absolutely have the opportunity to be gainfully employed as long as they want,
9:30
if they're willing to take on some of these additional skill sets that perhaps were
9:33
not as necessary for them in the past. So Alex Ginger, let's explore
9:39
that a little bit. Having managed quite a few diverse teams myself, one
9:43
of the most difficult things is guiding people, especially technology people, through change.
9:50
And it can be hard enough when change is evolutionary, but I want
9:54
to explore a little bit when the change feels revolutionary. Right right now,
9:58
we're in such a place of what feels like big change, and I love
10:05
the concept your concept that you put out there of AI is an ally,
10:09
not a replacement. Right, we can get away a little bit from the
10:13
scary place of everyone's losing their jobs and look at it as an ally.
10:16
I saw a great Gartner keynote and the speaker really reinforced in authorship and music
10:22
creation and the creativity part. You're not going to get rid of the human
10:26
element of that, but you're going to We're fine with a human collaborator,
10:30
a human editor. We need to get used to having a digital collaborator and
10:35
a digital editor. And I think that's a real important distinction. But my
10:39
sense is that employees, especially if employees are going to struggle with us a
10:43
bit, so talk about a bit about some effective strategies for upskilling and reskilling
10:48
to boost those capabilities, because it's more than just sending them to a tech
10:52
course, right, They have to change how they think, right. I
10:56
mean there's kind of two things going on there. First of all, you
10:58
have the general population that needs to develop greater IT skills because you have all
11:05
of a sudden, regular individual contributors from a variety of functions being empowered by
11:11
AI based technologies to make decisions that would previously had to be routed all the
11:16
way through the organization. Now you have people who can work with technology in
11:20
order to do their jobs and in some cases beyond their jobs more efficiently and
11:24
effectively. And I actually call those applied technology skills. So you're a marketing
11:30
person and you know that you can use software X in order to derive some
11:35
key analytics about your campaigns. That's an example of applied technology skills. You
11:39
know what tech is out there to allow you to do your jobs better,
11:43
so that you have that on the one side. And then you have the
11:46
IT folks that need to learn to do their jobs a little bit differently.
11:50
And so I think a really comprehensive, robust learning program that is offered in
11:56
a variety of different formats. Some maybe video based, might be short form
12:01
written or in person courses. It can really be offered kind of across the
12:07
gamut. But we need to do two things. We need to make sure
12:11
everybody in our workforce has basic AI understanding and knowledge, at least as far
12:16
as we have it in general and society. You need to be communicating that
12:20
to your organization. And you also need to have a structure in place for
12:24
making sure that your IT folks are really homing in on those human skills that
12:31
are so important in order for them to add value in their jobs going forward.
12:35
And by the way, this is especially important for the new generation of
12:37
tech workers in Generation C because of the research that we've done. Again,
12:43
we don't want to stereotype it, say everyone in Gen Z is the same,
12:45
but there are trends that we see where these folks, a lot of
12:48
them entered the workforce with no actual context for working remotely because they had never
12:52
worked in general. So they're off doing these isolated things from home offices and
13:00
have no idea how to build relationships or how to manage change management for the
13:07
deploying of a new technology, as an example, your tech folks who are
13:11
entry level won't have learned that, and so we really have to take an
13:13
extra step to make sure that the young tech workers, the members of Generation
13:18
Z, are getting those kind of fundamentals, the basics down so that they're
13:24
able to kind of lead. And another thing that I'm seeing, by the
13:26
way, this isn't exactly what you ask, but I'm seeing a lot of
13:30
fear among IT leaders right now because they feel like this is getting a little
13:35
bit out of control, that all of a sudden, you have different areas
13:37
of the business being like I'm going to build this AI and I'm going to
13:41
do that, and they worry about privacy security, their ability to have reliable
13:46
and valid data from all these different systems that are collecting data in different ways.
13:50
So I think that stress management is another area that is not always talked
13:56
about with tech workers. But their jobs are a lot more complicated than they
14:01
used to be. I mean, they used to have complete jurisdiction over everything,
14:03
and those days are quickly finding themselves in the past. Now that's an
14:07
interesting point shadow it just got incrementally more complicated as different segments of the business
14:13
go off and do their own thing because it's so easy. It's definitely an
14:18
area to explore. But I think it's you know, it's more than just
14:22
upskilling. You're touching on a little bit of that now. And we're at
14:26
an interesting parallel right now because next Thing just released our product called Adopt,
14:31
which helps employees and it release new products and helps employees adopt those. So
14:37
it's more than just for employees. It's more than just getting the skill.
14:39
They have to actually adopt those skills into their role and then adopt adapt into
14:46
their evolving role. And it's more than just the it's more than just the
14:48
employee. How can companies support their IT teams on that journey? I mean,
14:54
I think being very proactive is important. You know, there's always these
15:00
the research that I do, I constantly see this tension between employers and employees
15:07
regarding whose responsibility is it to make sure you have the right learning for your
15:11
job. Employers would like to say it's the employees's responsibility. Especially with the
15:16
democratization of a lot of content, now you can kind of go onto MIT
15:20
and take a course in data analytics if you want, Like, there's no
15:24
barrier to doing those things. So companies would like to have employees taking more
15:28
of the bonus on themselves, and employees feel the opposite. They're like,
15:31
if I'm working for your company, you should be telling me what I need
15:33
to do in order to upskill and do my job more effectively. And so
15:37
if you're a company, you're the one whose reputation is on the line.
15:41
So I think that taking the responsibility for making sure your employees are learning what
15:46
they need to learn and doing things the right way is very important. And
15:50
that's for tech workers and non tech workers, I mean, just the way.
15:54
One of the things that's all the rage now is we're going to have
15:56
an AI academy. We're going to train everyone in the basics of AI,
15:58
which, as I said, is necessary, but again, you need to
16:02
have that component of the tech workers may already come to the table knowing a
16:06
lot about AI and things like that, but what don't they know is how
16:10
to adapt their roles to work with these smart technologies so that they're not rendered
16:14
completely obsolete. And that I think is I do not see that happening very
16:18
much. I think that is a massive need that will save I think not
16:26
only save a lot of tech workers' jobs, but save a lot of organizational
16:30
reputations because what I see happening is that these technologies are going to be deployed,
16:34
They're not going to have proper oversight. There's going to be a big
16:37
booboo that's made and all of a sudden everyone will be pointing the fingers at
16:41
each other. But really, the IT stewards had been there in a proper
16:48
oversight role, that maybe that wouldn't have happened. So I think the role
16:52
of IT workers has never been more important, and it's only going to get
16:55
more strategic and more important as these technologies grow more sophisticated. So when I
17:00
was in Enterprise it a large financial services company, the headline for the learning
17:07
plan was if it is to be, it's up to me. And it
17:11
worked for some people, but others it didn't go over too well. You
17:15
really need that balance that the company supporting you on that journey. So let's
17:18
talk a bit about kind of employee digital employee experience specifically, how are what
17:25
are some examples of how organizations are successfully implementing those upscaling programs. You really
17:30
need to boost the digital employee experience, but how are organizations executing. Yeah,
17:37
having that digital employee experience I think makes all the difference between whether you're
17:41
able to have a successful hybrid or remote workforce and whether you aren't, because
17:48
that's really people's lifeline into the organizational culture. If they're not being immersed in
17:55
it on a daily basis in a physical office, then that digital employee experience
17:59
becomes very, very important. And I think that we had done kind of
18:03
a good job many organizations of creating these experiences that were also tied to to
18:07
your point to learning management systems. So you would go in to your portal,
18:14
you would get all the information relevant to your current job, what's going
18:17
on in the organization this week, But then you would also have kind of
18:19
customized learning platform where that hopefully would be at this point infused with AI based
18:26
technologies that would tell you, okay, based on what you took last month,
18:30
you might take this, based on the fact that you want to get
18:33
into this career path or make this lateral move, you might take this class.
18:37
Hopefully a lot of them are infused with that technology at this point,
18:41
but having people given specific guidance and then the option to kind of consume that
18:48
learning when and where is convenient for them, I think is a really important
18:52
point there. And the other thing I would say about digital employee experience is
18:57
I've been beaten on this drum for or probably a couple of decades now,
19:02
but I noticed that the digital employee experience tends to be kind of a one
19:07
size fits all thing, and it's very much in many cases not customized to
19:14
the needs of a particular group. And I'll give you an example, and
19:15
that's the contract workforce. I've been a contractor working with different companies for over
19:21
twenty years, and in many of those cases, I was client facing,
19:25
so I was actually engaging with customers on behalf of that organization. And I
19:30
never received any onboarding, any digital employee experience anything. I was on my
19:36
own to represent this organization. They wouldn't let full time employees do that.
19:40
So I'm not sure why contractors aren't considered a valuable enough audience to warrant their
19:45
own digital experience. And that's, by the way, employee experience in general,
19:48
not just digital experience. But I think digital experience is what we are,
19:52
we tend to be creating now, and so especially because it's technology driven,
19:56
that should make it a little bit easier theoretically. I really am encourage
20:00
organizations to think about all the different stakeholder groups that are working on behalf of
20:04
your organization and to make sure that you have provided the right kind of experience
20:10
for them. And I think you're right. AI plays a big role there,
20:14
or can play a big role, and once employees see the power,
20:17
I think it's really enlightening. I follow a chat GPT prompt social account and
20:22
they come up with some really fascinating ways to leverage it. And just yesterday
20:26
was a series of prompts to put together a learning plan for me. Use
20:30
chat GPT to create a robust learning plan with practice examples and details on how
20:37
I can learn X, y z, and it comes back with huge examples
20:41
and huge plans on how to upscale yourself. I think it's using AI to
20:45
help you upscal in that area. I think is a really cool concept.
20:52
And that was a beautiful example of applied technology skills. By the way,
20:56
I loved that you said that because the fact that you knew that you could
21:00
use information about how to develop prompts and chat GPT to accomplish this goal of
21:07
learning management plan. Just even knowing that you can do that is a skill
21:10
set because most people would either still hire a consultant okay, I need a
21:14
learning consultant, or you know, they would do research in a more traditional
21:18
way when this is in many ways a fast track. It's a fast fast
21:22
if you're going to Disney. But again, you need to you need to
21:26
know how to prompt it, and that's a skill set that I think pretty
21:30
much everyone has to learn. Unless you develop the chat GPT in the first
21:33
place, then you might know how to prompt it. So that's some of
21:34
our IT workers, But ninety five percent of people don't know how to prompt
21:38
generated AI. So you know, we need to all learn that. It's
21:41
a great example. You know, this thing to you, Alexandra, I
21:47
can't help. But I think on the one hand, we have technology workers
21:49
who are by necessity having to develop of their extra technological skill set. Right
22:00
on the other hands, you have traditional non technology workers who are increasingly enmeshed
22:06
and technology and whatever it is that we do. I mean, what is
22:10
if both sets of workers are kind of pulling together into the same kind of
22:15
middle ground. How would you define that middle ground? What is the nature
22:18
of human work as it relates to technology at large in your view, Well,
22:22
I think it'll be increasingly combined and not as separate. And as I
22:26
mentioned a couple of minutes ago, you had typically the IT department would make
22:30
all the IT decisions, and we're just seeing this type of technology and I'm
22:34
referring to generative AI in particular being far more democratized, where there's just no
22:40
reason to keep it centralized in a given function. Everybody can learn to use
22:47
it relatively intuitively, kind of like how everybody used the Internet. Well,
22:51
generative AI tools are going to be the same sort of thing. So as
22:56
to whether there will be a role for the IT function, I mean again,
22:59
I think like other functions, it's becoming more strategic unless hands on actually
23:06
writing the code yourself or you know, building analytics systems or databases. I
23:11
mean that stuff is going to be more and more automation. It's going to
23:14
be the larger strategy of how do we deploy these technologies in a way that
23:18
makes the most sense for the organization. And that's where I just see a
23:22
lot of wheel spinning now organizations are like, we have to get on the
23:26
GENII vandwagon. We got to have an AI program, an AI project,
23:30
and it's like, take a giant step back and think about whether you have
23:33
the basics and the fundamentals down. Culture is a great example, like you've
23:37
got to build culture from the inside out. You can't use an AI to
23:41
improve culture. You got to get it right by asking employees and really taking
23:45
the step to co create new norms in this post pandemic era. But that's
23:49
an example of just where we just think we're going to snap our fingers and
23:52
GENAI is going to solve all our problems. And so that attitude and that
23:57
skill set of being able to guide the implementation on kind of this practical,
24:03
real world level is really where I can see IT leaders and IT professionals stepping
24:08
into the light there, because they're going to know better than anyone how the
24:12
stuff can be deployed and what it's used for, and also what's practical for
24:18
your particular organization, which will be different than another organization. Can't be denied.
24:26
Alexandre, You've been pretty prescient in what you've been writing and thinking about.
24:30
I'm sure you've noticed more than anybody over the last few years. You
24:37
are a futurist after all. I mean, you know it must be how
24:41
you earn your futurist card, but we'd love to know that by what.
24:45
What are you working on presently? Do you have a new book you're considering?
24:48
What should we be aware of around the corner that we're not thinking of
24:52
right now. So one of the things that I did in twenty twenty,
24:56
right when the pandemic was getting going, I provided a forecast to the US
25:00
Department of Labor about what I thought would be some of the major fallout points
25:07
from At that point, we didn't really know how long COVID was going to
25:10
go on, we didn't know what kind of disruption it would be necessarily,
25:12
but I thought that inevitably there would be economic contractions as a result of this,
25:18
and probably a mental health escalation globally because we were going to all be
25:26
in survival mode for as long as this took, and then everyone would have
25:30
suffered a collective trauma. So the forecast was based on that and the fact
25:33
that what were we going to see happening in terms of unemployment and what could
25:38
we do with people who found themselves unemployed and suffering from mental health difficulties.
25:45
In this we were looking at twenty twenty four twenty twenty five, and in
25:49
the end we received a grant from the National Institutes of Health here in the
25:55
US and they gave us research funds to develop an inner to help people who
26:02
are newly unemployed with their symptoms of emotional distress from being laid off. And
26:07
our hope is to kind of just like generative ai as being democratized, we
26:10
would like to democratize evidence based mental health care to just your average worker,
26:15
not somebody who needs to have the money for an expensive therapist to go see.
26:21
And so that's what I've been working on. The most exciting thing is
26:23
is the data from this clinical trial, because we ran it against a control
26:29
group that just got garden variety career advice. We wanted to see, like,
26:33
is this incorporation of mental health care really going to be something that's valuable,
26:37
And so we did like a scientific study on this, and we're going
26:41
to have the data in the next couple of months and that'll inform what we
26:45
do with the intervention indext But the reason I bring this up is that I
26:48
think when people going very back full circle to the beginning, we talk about
26:51
what a futurist does. I think in an ideal world, a futurist uses
26:55
forecasting to actually develop solutions that can help with problems that are coming around the
27:00
pike, which and we do see unfortunately some of those forecasts coming to fruition
27:04
around unemployment layoffs and escalating mental health crisis. So it's only good to be
27:10
right if you can do something about it. And this is an example of
27:14
something that we were able to do well well, So beautiful project Alexandre.
27:18
It's been an absolute pleasure to have you on my Showutely fascination you guys woud
27:23
ask great questions, Thank you, thank you, thank you very much.
27:27
And where can people find you? Where can people learn about you? Any
27:30
any obviously we've already mentioned your latest book. Anything else you'd like to plug
27:34
any anywhere else you'd like our listeners to go well. I would love people
27:41
to check out the website, Alexandralevitt dot com, follow me on LinkedIn.
27:45
I'm still on x to a certain degree, so I would love to hear
27:48
people's thoughts, especially because many of my books are getting updated regularly. So
27:53
if there's something that you think I missed or something that you think we should
27:56
have considered. Then I'm always related to receive that feedback and also to hear
28:02
your forecast about what you think is coming around the pike in your industry,
28:04
because it's rare that I get to do a deep dive into a particular industry,
28:08
and so I love hearing it from the perspective of people who are in
28:11
the trenches. Fabulous, Alexandra, Thank you so much. You're welcome to
28:18
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